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Brain metastases: systematic exploration of
prognostic and predictive factors
Doctoral thesis at the Medical University of Vienna
for obtaining the academic degree
Doctor of Medical Science
Submitted by Dr. Anna Sophie Berghoff
Department of Medicine I
Medical University of Vienna
Währinger Gürtel 18-20
1090 Vienna, Austria
Assigned Program:
Clinical Neurosciences (n790)
Supervisor:
Assoc. Prof. Priv.-Doz. Dr. Matthias Preusser
Department of Medicine I
Medical University of Vienna
Währinger Gürtel 18-20
1090 Vienna, Austria
Vienna, 14.05.2014
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Table of contents
1 Declaration 4
2 Abstract 5
3 Zusammenfassung 6
4 Introduction 7
4.1 Epidemiology of brain metastases 7
4.2 Pathobiology of the brain metastases 11
4.3 Clinical prognostic factors in brain metastases 14
4.4 Treatment of brain metastases 19
5 Aims of this thesis 24
6 Results 25
6.1 Brain Metastases free survival differs between breast cancer subtypes. 25
6.2 Brain-only metastatic breast cancer is a distinct clinical entity characterized by favourable median overall survival time and a high rate of long-term survivors. 33
6.3 Prognostic significance of Ki67 proliferation index, HIF1 alpha index and microvascular density in patients with non-small cell lung cancer brain metastases 39
6.4 Preoperative diffusion-weighted imaging of single brain metastases correlates with patient survival times. 50
6.5 Invasion patterns in brain metastases of solid cancers. 59
6.6 Characterization of the inflammatory response to solid cancer metastases in the human brain. 69
7 Discussion 83
7.1 General discussion 83
7.2 Conclusion & future prospects 86
8 Material & Methods 87
8.1 Materials 87
8.2 Methods 87
9 List of figures 93
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10 List of tables 93
11 References 94
12 Curriculum Vitae 111
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1 Declaration The present doctoral thesis was carried out at the Department of Medicine I (Medical
University of Vienna) and the Institute of Neurology (Medical University of Vienna) in
cooperation with the Center of Brain Research (Medical University of Vienna), the
Clinical Institute of Pathology (Medical University of Vienna), 3rd Medical Department
(Paracelsus Medical University Hospital Salzburg) Department of Neurology,
(Paracelsus Medical University Salzburg), Landes-Nervenklinik Wagner-Jauregg and
the Department of Neuropathology (University of Tuebingen). The tissue preparation
and the immunohistochemical stainings were kindly supported by Carina Dinhof
(Department of Medicine 1, Medical University of Vienna), Irene Leisser (Institute of
Neurology, Medical University of Vienna), Elisabeth Dirnberger (Institute of
Neurology, Medical University of Vienna), Bettina Jesch (Clinical Instiute of
Pathology, Medical University of Vienna) and Marinanne Leisser (Center of Brain
Research, Medical University of Vienna). Preparation of immunohistochemical
staining for integrins was performed in cooperation with Jens Schittenhelm
(Department of Neuropathology, University of Tuebingen). Analysis of diffusion-
weighted imaging was performed within the diploma thesis of Thomas Spanberger
(Department of Medicine I, Medical University of Vienna) under supervision of
Daniela Prayer (Department of Radiology, Medical University of Vienna). Evaluation
of immunohistochemical preparation, assessment of clinical data and interpretation of
results as well as preparation of the original papers was performed by Anna Sophie
Berghoff (Department of Medicine I, Medical University of Vienna) under the
supervision of Matthias Preusser (Department of Medicine I, Medical University of
Vienna) and with support of the mentors Johannes A. Hainfellner (Institute of
Neurology) and Peter Birner (Clinical Institute of Pathology, Medical University of
Vienna)
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2 Abstract !Brain metastases are an increasing clinical challenge in modern oncology and their
adequate therapy represent an unmet medical need. While new treatment options
significantly influenced the survival prognosis of patients with advanced extracranial
solid cancers, the prognosis of patients with brain metastases remains poor due to
the limited treatment options. Deeper insight in the involved mechanisms of the brain-
metastatic cascade and precise patient selection based on survival prognosis are
important for successful conduction of clinical brain metastasis trials.
In the frame of this doctoral thesis we investigated clinical, pathological and
radiological characteristics of patients with brain metastases. We identified
prognostically relevant radiological, like diffusion weighted imaging, and tissue
based, like KI67 proliferation index and microvascular density, factors in patients with
brain metastases. Further, we showed that patients with HER2 positive and triple
negative metastatic breast cancer develop brain metastases earlier during their
course of disease and that brain-only metastatic breast cancer might be a distinct
disease pattern associated with long term survival. We gained a further insight on the
invasion patterns of brain metastases into the surrounding brain parenchyma and
characterized the inflammatory response to brain metastases.
In conclusion, the results of the doctoral thesis provide novel insight into the
pathological and radiological characteristics of brain metastases and their clinical
relevance. Our data may provide a basis for future studies including prospective
clinical brain metastases specific trials.
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3 Zusammenfassung Hirnmetastasen stellen eine zunehmende Herausforderung in der Behandlung
onkologischer PatientInnen dar. Obwohl neue, vor allem zielgerichtete Therapien,
das Überleben von PatientInnen mit Krebserkrankungen im letzten Jahrzehnt
deutlich verbessert haben, gibt es nur wenige Innovationen im Bereich der Therapie
der Hirnmetastasen. Das Verständnis der involvierten, molekularen Mechanismen
sowie ein detailliertes Wissen über den Krankheitsverlauf bei Hirnmetastasen stellen
die Grundlage für die Etablierung neuer Hirnmetastasen spezifischer Studien.
In der vorliegenden Arbeit haben wir pathologische und klinische Faktoren bei
PatientInnen mit Hirnmetastasen untersucht. Wir konnten zeigen, dass zusätzliche
radiologische Parameter, wie die Diffusions-gewichtete Bildgebung, und Gewebe
basierte Parameter wie der Ki67 Proliferationsindex oder die Gefäßdichte zusätzliche
Information zur Überlebensprognose von PatientInnen mit Hirnmetastasen
beisteuern können. Des weiteren konnten wir aufzeigen, dass PatientInnen mit HER2
positiven oder triple negative Mammakarzinom früher im Krankheitsverlauf
Hirnmetastasen entwickeln und PatientInnen mit einer selektiven Hirnmetastasierung
ohne extrakraniale Metastasen häufig ein Langzeitüberleben aufweisen. Im Rahmen
von zwei Autopsie Studien charakterisierten wir die Immunantwort auf
Hirnmetastasen sowie drei verschiedene Invasionstypen.
Zusammenfassend könnten die durch die vorliegende Arbeit erworbenen Kenntnisse
neue Aufschlüsse über Prognosefaktoren sowie den klinischen Krankheitsverlauf bei
PatientInnen mit Hirnmetastasen generieren. Dieses neue Wissen kann in Zukunft
eingesetzt werden um klinische, Hirnmetastasen spezifische Studien zu planen.
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4 Introduction 4.1 Epidemiology of brain metastases Brain metastases (BM) are an increasing challenge in modern oncology. Despite
recent advances in the management of cancer patients, BM are still a devastating
complication with an enormous impact on overall survival and also on the quality of
life of patients.
Historically, BM are described as a rare and late complication in patients with
metastatic cancer. However, recent epidemiologic investigations show that the
incidence of BM is constantly increasing over the last decade [1-3]. Reasons for this
phenomenon are probably manifold and only poorly investigated. Patients with
metastatic cancer live longer mainly due to the increased control of the extracranial
cancer by improved systemic treatment strategies. Thus, patients who might have
died earlier to their extracranial, metastatic disease, nowadays live long enough to
experience the symptomatic manifestation of BM [4]. Numerous of the new targeted
therapies are postulated to be unable to cross the blood-brain barrier. As a
consequence, while the extracranial disease is controlled, the brain is a sanctuary
site for the cancer cells [5]. The lack of blood-brain barrier penetration is especially
evident in monocloncal antibodies like trastuzumab (anti HER2, breast cancer) or
pertuzumab (anti HER2, breast cancer) [6]. Therefore, a significantly increased
incidence of BM was described for some cancer disease after the introduction of the
new targeted treatment [7]. Although screening for BM is not recommended for most
solid cancers, patients with mild neurological symptoms receive high resolution
imaging at an earlier stage due to the wide availability of magnet resonance imaging,
resulting in the early detection of oligosymptomatic BM [4, 8].
The propensity for BM differs between the solid cancers. Lung cancer is the most
frequent cause of BM followed by breast cancer, melanoma, kidney and colorectal
cancer [2, 9]. Within the primary cancer, further subgroups defined by the presence
of certain molecular characteristics like receptor expression or gene mutation, with
increased propensity for BM development exist.
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Figure 1: Frequency of primary tumours causing BM (Vienna cohort, n=4124,
unpublished data)
In lung cancer, the histological subtype is the first most important risk factor for
development of BM. Patients with small cell lung cancer (SCLC) have the highest risk
for the development of BM, as up to 70% of patients develop BM [10]. Due to this
highly elevated risk, SCLC is the only subpopulation with a clear indication for
prophylactic whole brain radiation in order to prevent BM development [11].
Incidence among patients with metastatic non-small cell lung caner (NSCLC) is about
20% to 40% and differs according to the further histological and molecular
characteristics, which influence survival, treatment modalities as well as prognosis
and risk for BM development [12]. Patients with squamous cell carcinoma develop
BM less frequently than patients with non-squamous carcinoma [13]. A higher
propensity for BM and especially for the development of multiple, miliary BM was
described for patients with EGFR mutation [14]. Similar frequencies of FGFR
amplification, ALK translocation and ROS1 gene rearrangements were investigated
for primary lung cancer and matched BM samples, indicating that these molecular
aberrations do not increase the risk of BM [15-17].
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Depending to the molecular subtype, which is defined according to overexpression of
the steroid receptors (oestrogen receptor (ER), progesterone receptor (PR)),
amplification and subsequent overexpression of HER2 and the proliferation rate, BM
incidence varies from 5% to 30% among patients with metastatic breast cancer [18].
Luminal A subtype is characterized by the overexpression of ER, facultative
overexpression of PR and a low proliferation index and associated with infrequent
occurrence of BM [19]. The HER2 subtype is defined by overexpression of the HER2
receptor and BM frequently occur during the course of the disease [5]. The triple
negative subtype is defined by the absence of any receptor overexpression and
associated with the highest propensity of BM [20].
Melanoma is the third most common cause of BM, with a BM incidence of up to 40%
[12, 21, 22]. Risk factors for the development of BM in patients with melanoma are
thickness, ulceration and presence of mitosis in the primary melanoma as well as
location of the primary in the head and neck region and elevation of lactate
dehydrogenase (LDH) [23, 24]. Little is known on molecular characteristics
increasing the propensity of BM in melanoma patients. The most common and
clinically relevant mutation in melanoma, point mutation of v-Raf murine sarcoma
viral oncogene homolog B1 (BRAF V600E), was shown to have the same incidence
in BM like in extracranial melanoma, suggesting that the BRAF mutation might not be
involved in the brain metastatic cascade [25].
Renal cell carcinoma is the fourth most common cause of BM, as about 17% of
patients suffering of renal cell carcinoma develop symptomatic BM [26-28].
Characteristically, BMs are a late event in the clinical course. The first diagnosis of
BM can be years after the initial diagnosis of renal cell carcinoma [29]. Interestingly
enough, in contrast to the other common causes of BM, the incidence of BM in
metastatic renal cell carcinoma patients is postulated to be decreasing probably due
to the improved systemic treatment strategies including anti-angiogenic tyrosine
kinase inhibitors [27, 30]. So far, no molecular factors increasing the incidence of BM
in renal cell carcinoma were identified.
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BM are a rather infrequent complication of colorectal cancer with an incidence of 2 to
8%. However the incidence was reported to be rising over the last decade [8]. The
improved control of the extracranial disease is supposed to be the main cause for the
recent increase, as due to the longer survival, patients who would otherwise have
died to the extracranial disease, actually experience the occurrence of the late
complication of BM [31]. Risk factors for the development of BM are, left sited (rectal)
located primary tumour and long-standing pulmonary metastases [32]. No molecular
risk factors for the development of BM in patients with advanced colorectal cancer
have been identified yet.
Rarely BMs are caused by other primary, extracranial tumours like ovarian cancer,
prostate cancer, bladder cancer, uterus cancer or gastro-oesophageal cancer [8].
Frequency of BM in these entities is estimated to be about 1 to 2%. However, also in
these rare entities, the incidence of BM was reported to be rising over the last
decade. About 10% of BM patients suffer of BM from unknown primary tumours [33].
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4.2 Pathobiology of the brain metastases !The propensity of metastatic spread is a hallmark of malignant cancers [34]. A single
cancer cell has to overcome several critical obstacles before the successful
establishment of a macrometastasis. The “seed and soil” theory postulates that brain
metastatic colonization is not only influenced by certain characteristics of the tumour
cell (the seed), but also by the microenvironment of the brain parenchyma (the soil)
[35]. In terms of the “seed”, specific gene expression patterns of brain metastasizing
tumour cells were identified that significantly differ from the gene expression patterns
of bone metastases in breast cancer model [36]. The “soil”, the brain parenchyma,
the pre-existing brain vascular structures as well as astrocytes and microglia
influence the establishment of BM [37-39]. The understanding of the involved
molecular mechanism is the prerequisite for the identification of possible `druggable´
targets, especially in the prevention of BM.
The disconnection of a single tumour cell or a group of tumour cells from extracranial
tumour formations (either primary tumour or extracranial metastasis) in a process
called epithelial-to-mesenchymal transformation (EMT) is the first mandatory step in
the brain metastatic cascade. The process of EMT is characterized by the loss of E-
cadherin, an adhesion molecules, as well as the induction of motility [40].
The dissemination of tumour cells to the brain parenchyma does solely occur via the
blood stream, as the brain lacks lymphatic vessels. Therefore, tumour cells have to
manage survival and adapt to the changed microenvironment within the blood
stream. Several preclinical studies indicate, that tumour cells might aggregate with
platelets and leucocytes in order to survive [41].
The passage through the blood brain barrier is the next critical step in the brain
metastatic cascade. Here, tumour cells were shown to rest at vascular branching
points, presumably due to the reduced shear forces of the blood flow, and use similar
mechanisms as leukocytes in the adhesion cascade to cross the blood brain barrier
[40]. The involved adhesion molecules like selectins, integrins, chemokines,
heparanases and matrix metallopropeases, represent several theoretically targetable
molecules [42].
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After the successful passage of the blood brain barrier BM tumour cells have to
manage intraparenchymal growth. A real time mouse model of BM using a multi-
photon laser-scanning microscope through a chronic cranial window revealed
capacious information on the behaviour and properties of BM forming tumour cells
after the passage of the blood brain barrier [43]. Tumour cells were shown to stay in
close contact with the microvessels directly after the passage through the blood brain
barrier and induce either neoangiogenesis or growth via vascular co-option alongside
the pre-existing brain vascular structures. The angiogenic pattern differed depending
on the primary tumour subtype. BM from NSCLC were shown to induce early
angiogenesis in the outgrowth from micro- to macrometastases, which can be
inhibited by anti-angiogenic treatment. BM from melanoma presented with growth via
vascular co-option and anti-angiogenic treatment did not influence the outgrowth of
macrometastases [43]. The growth via vascular co-option is characterized by
collective tumour cell migration along pre-existing vessel and relies on integrin
signalling. In vivo experiments of integrin beta 1 inhibition resulted in prevention of
adhesion to the vascular basement membrane und BM outgrowth was attenuated
[37, 44]. In line, application of the alpha v integrin inhibitor Intetumumab in a breast
cancer BM rat model prevented BM formation and decreased the number of BM [45].
Induction of neo-angiogenesis relies on activation of the vascular endothelial growth
factor (VEGF)/hypoxia-inducible factor 1 alpha (HIF 1 alpha) pathway. Hypoxia,
induced by fast proliferation an insufficient corresponding neoangiogenesis and can
be measured using the HIF 1 alpha index, increases VEGF expression and in
consequence endothelia cell proliferation and blood vessel formation [46]. The
resulting vascular formations show pathologic features in their morphology as well as
in their growth pattern [47]. Vascular structures as well as vascular density were
shown to differ between the primary sites, as melanoma BM were shown to have a
lower number of microvessels when compared to carcinomas of the lung or breast
[48]. Besides the formation of new blood vessels, the VEGF/HIF 1 alpha axis further
influences blood vessel permeability and resulting peritumoural oedema as well as
treatment response [49, 50]. Further, high HIF 1 alpha index is associated with
resistance to radiotherapy and chemotherapy [51].
So far the time points of detachment from the extracranial tumour lesion, passage of
the blood-brain barrier and outgrowth from micro- to macrometastis are uncertain. In
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general, BM are considered a late complication in metastatic cancer. However,
screening studies revealed a high incidence of asymptomatic BM [52]. This finding
suggests that the detachment of tumour cells and the passage of the blood-brain
barrier actually occur early during the disease course but the tumour cells do not
grow from the micrometastasis to the macrometastasis status for a certain time. In
line, a real time mouse model of the establishment of BM showed that brain
metastatic cells are able to stay dormant in the perivascular niche and persist as
asymptomatic micrometastases over prolonged time periods [43]. Therefore
molecular characteristic involved in passage of the blood brain barriers and the
outgrowth of macrometastases are potentially `druggable´ targets in order to prevent
the occurrence of symptomatic BM. Understanding to these key regulators and the
time course of brain involvement are precondition to establish clinically applicable BM
preventive strategies [53].
Growth and invasion depends further on the interaction with the brain
microenvironment including astrocytes, microglia and the immune system. BM
tumour cells were shown to recruit astrocytes for their own advantage. Through
physical contacts astrocytes were postulated to lead to a chemoprotection of BM
tumour cells [39]. The central nervous system is considered an immunoprivileged
organ, what might inhibit the inflammatory response to BM. Data on experimental
metastases in murine brain suggest that activated microglia, which are the main
effector cells of the brain specific immune system, have tumour cytotoxic effects,
although some publications have also indicated pro-neoplastic microglia effects in
glioma [54, 55]. Microglia cells function involves innate as well as adaptive immune
responses [56, 57]. Interaction of the adaptive immune response, namely B- and T-
cell, and BM formation has not been investigated yet. However, density of T-cell
infiltration was postulated as a prognostic factor in various frequent primary tumours
of BM [58-61].
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4.3 Clinical prognostic factors in brain metastases Accurate and realistic survival estimation is mandatory for treatment decision in
patients with BM. Although survival prognosis of patients with BM is in general poor,
some patients do experience long-term survival despite the presence of BM. On the
other hand some patients experience fast deterioration and do not profit of intensified
treatment strategies. Therefore survival estimation in patients with BM is an important
requirement for adequate selection of patients for clinical trials as prognostic
homogeneity is crucial for the clinical utility of studies [62, 63].
Several clinical characteristics were identified from databases of the Radiotherapy
and Oncology Group (RTOG) BM studies and compiled in a prognostic score. The
first score, recursive partitioning analysis (RPA), includes the parameters age (< 65
years; > 65 years), Karnofsky performance status and presence of extracranial
metastases [64]. The second score, the graded prognostic assessment (GPA),
calculates a prognostic score out of age (> 60; 50-59: < 50), Karfnofsky Performance
Score (< 70; 70-80; 90-100), presence of extracranial metastases (present vs.
absent) and number of BM (> 3; 2-3; 1) [65]. The GPA was validated in a cohort of
almost 2000 patients, further analysis however revealed that the histology of the
primary tumour highly impacts the survival prognosis. Most included patients suffered
of BM from NSCLC and the subgroup analysis showed that depending on the tumour
of origin the clinical prognostic parameters differ.
The third score, the diagnosis specific graded prognostic assessment (DS-GPA), is
based on the survival data of almost 4000 patients included in clinical trials of the
RTOG. The DS-GPA was conducted in order to acknowledge the individual
prognostic factors for each primary tumour histology [66-68].
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Table 1: Diagnosis specific prognostic assessment (DS-GPA; adapted from [68]). DS-GPA class is calculated by adding the score for each characteristic. Score 0 0.5 1.0 1.5 2.0 Lung cancer Age, years > 60 50-60 < 50 Karnofsky performance status
< 70 70-80 90-100
Extracranial disease Present Absent Number of brain metastases
> 3 2-3 1
Breast cancer Age, years > 60 < 60 Karnofsky performance status
< 50 60 70-80 90-100
Subtype Basal Luminal A
HER2 Luminal B
Melanoma Karnofsky performance status
< 70 70-80 90-100
Number of brain metastases
> 3 2-3 1
Renal cell carcinoma Karnofsky performance status
< 70 70-80 90-100
Number of brain metastases
> 3 2-3 1
Gastrointestinal cancers Karnofsky performance status
< 70 70 80 90 100
In lung cancer (non-small cell and small cell lung cancer) the factors age (< 60; 50-
60; < 50), Karnofsky Performance Score (< 70; 70-80; 90-100), presence of
extracranial metastases (present vs. absent) and number of BM (> 3; 2-3; 1) showed
significant impact on survival prognosis. Estimation of median survival ranges from
3.0 month in the least favourable group compared to 14.8 months in patients in the
most favourable prognostic group [68]. So far, the DS-GPA does not separate
between small cell and non-small cell long cancer, although data from real life
cohorts postulate a prognostic impact of the underlying histology [69]. Actually
molecular subtypes of NSCLC like EGFR mutation, alk translocation or ROS1 gene
rearrangements are not included in the survival estimation. However, first data from
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real life cohorts postulates, that EGFR mutated NSCLC might have an improved
survival prognosis [70, 71].
In breast cancer the impact of the breast cancer subtypes (luminal A and B, HER2
and triple negative) on survival prognosis led to their inclusion in the DS-GPA
calculation. Therefore, the DS-GPA for breast cancer is based on the parameter age
(! 60; < 60), Karnofsky Performance Score (" 50; 60; 70-80; 90-100) and breast
cancer subtype (triple negative; luminal A; HER2; luminal B). Survival prognosis for
patients with BM from breast cancer ranges from 3.4 months in patients of the least
favourable group to 25.3 months in patients in the most favourable prognostic group
[68]. The presence of extracranial metastases was not included in the DS-GPA for
breast cancer, as no survival impact was found for this parameter. However, the DS-
GPA for breast cancer is based on a highly selected cohort of patients, eligible for
inclusion in a clinical trial. Indeed, approximately only half of the included breast
cancer patients suffered of extracranial disease indicating an inclusion bias.
The DS-GPA for melanoma BM and for renal cell carcinoma BM does only include
Karnofsky Performance Score (< 70; 70-80; 90-100) and number of BM (> 3; 2-3; 1).
Median estimated survival in the least favourable group is 4.4 months for melanoma
and 3.3 months in renal cell carcinoma compared to 13.2 months for melanoma and
14.8 months for renal cell carcinoma in the most favourable prognostic group [68].
Again, status of extracranial disease was not included in the prognostic assessment.
However, for the instance of melanoma evidence exists that BM as first metastatic
site might represent a distinct clinical entity with reduced survival prognosis [72].
In gastrointestinal cancer BM only Karnofsky Performance Score (<70; 70; 80; 90;
100) was identified as impacting the survival prognosis. The median survival in the
least favourable prognostic group is 3.1 months and 13.5 months in the most
favourable group [68]. However, number of BM and presence of extracranial
metastases were identified as prognostic marker in real life cohort, indicating the
importance of further investigation of prognostic factors [73]. In addition, the
definition of gastrointestinal cancers is rather inaccurate, as the clinical course and
management of the various cancer types originating in the gastrointestinal tract (e.g.
colorectal cancer, gastric cancer, oesophageal cancer, pancreatic cancer etc.) are
distinct. So far little is known on specific prognostic parameters in patients with BM of
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colorectal, gastric or oesophageal cancer. In these cancer types several molecular
and histological subtypes correlate with different survival and need to be investigated
also upon their impact on BM prognosis.
Although the DS-GPA is frequently used for the definition of inclusion criteria in
clinical trials and is based on a huge database, it has to be taken into account that
validation in real life cohorts of adequate size is urgently warranted. The included
patients were all highly selected for the inclusion in clinical trials, suggesting that the
clinical prognostic factors might differ in real life. For example, approximately only
half of the patients suffered of extracranial disease and over two thirds of the patients
suffered of less than three BM [68]. Validation and extension of clinical prognostic
factors in real life cohorts is currently on-going.
Table 2: Estimated survival according to DS-GPA class (adapted from [68])
DS-GPA Class I
DS-GPA Class II
DS-GPA Class III
DS-GPA Class IV
Lung cancer Score 0-1.0 1.5-2.0 2.5-3.0 3.5-4.0 Median OS (months) 3.0 5.5 9.4 14.9 Breast Cancer Score 0-1.0 1.5-2.0 2.5-3.0 3.5-4.0 Median OS (months) 3.4 7.7 15.1 25.3 Melanoma Score 0-1.0 1.5-2.0 2.5-3.0 3.5-4.0 Median OS (months) 3.4 4.7 8.8 13.2 Renal cell carcinoma Score 0-1.0 1.5-2.0 2.5-3.0 2.5-4.0 Median OS (months) 3.3 7.3 11.3 14.8 Gastrointestinal cancer
Score 0-1.0 2.0 3.0 4.0 Median OS (months) 3.1 4.4 6.9 13.5
At present estimation of survival prognosis is only based on clinical parameters.
However, radiological and tissue based findings might actually add valuable
information. Radiological findings represent growth and invasion of a brain
metastasis and can be easily assessed, suggesting that further investigation might
reveal further includable parameters.
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The size of the peritumoural oedema was identified as a prognostic factor in a well-
defined and homogenous cohort of patients with single brain metastasis and
neurosurgical resection as first line treatment [74]. Oedema of less than one
centimetre correlated with a median survival of 5 months, compared to 19 months
with a large oedema of over one centimetre and corsage of the midline. Size of
oedema showed correlation with microvascular density, as large peritumoural
oedema was associated with high microvascular density [74]. Therefore, the
peritumoural oedema might be a surrogate marker representing the angiogenic and
growth pattern.
Consideration of radiological finding might add additional value in terms of treatment
directions and survival estimation.
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4.4 Treatment of brain metastases The treatment of BM mainly relies on local strategies including surgery, radiosurgery
and whole brain radiation, while systemic therapies depending on the primary tumour
have a smaller impact in the clinical management of BM patients so far [75].
First line treatment decisions in patients with newly diagnosed BM mainly rely on the
primary tumour, number of BM, size of BM and Karnofsky performance score.
Patients with only one singular BM are candidates for either surgery or radiosurgery,
depending on the size of the BM. BM with a size over 3 cm have an increased risk of
radionecrosis and should therefore be treated with surgery [76]. Patients with
unknown primary tumour are candidates for surgery in order to obtain histology for
further treatment strategies [76]. Patients with one to three BM are candidates for
surgery in combination with radiosurgery or radiosurgery alone depending on size
and location of BM. A combined treatment might be suitable for patients with BM over
3 cm or in well accessible areas for neurosurgery [77].
The value of whole brain radiation therapy after the local treatment of one to three
BM is a matter of discussion. Only one prospective phase III study addressed the
matter and could not identify a benefit in terms of overall survival [78]. However, brain
progression free survival was significantly increased in patients receiving whole brain
radiation therapy.
The first line treatment approach in patients with over three BM is whole brain
radiation therapy [53]. However, the value of whole brain radiation therapy is matter
of intensive discussion, as it is associated with impairing side and long-term effects
like decline in neurocognitive function, memory loss, leukoencephalopathy and
resulting decline in quality of life [79-81]. Especially in patients with favourable
survival prognosis even upon the diagnosis of BM the value of first line whole brain
radiation therapy is questioned [63]. A first line systemic treatment approach using a
systemic compound with effect on BM might be more favourable as patients may
actually experience the long-term side effects of whole brain radiotherapy [62].
Hippocampal sparing whole brain radiation is a further option in order to avoid the
side effect of memory loss. The method of hippocampal sparing whole brain radiation
therapy was proven to be safe and valid, as BM are hardly ever observed in the
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hippocampal area. However, the hippocampal sparing method is technically difficult
and time consuming, making it only feasible in selected cases [82-84].
Systemic cytotoxic therapies are postulated to have only a minor impact in the
treatment strategy of BM patients due to the difficulty of penetrating the blood brain
barrier [85]. However, the blood brain barrier might be at least leaky in BM or even in
parts disrupted, so that systemic therapies might have at least partial effect [86-88].
Irrespective, patients with BM were systematically excluded from clinical trials in the
last decade and resulting little is known about the value of some systemic therapies
in BM patients. Recently, the urgent need for BM specific trials was pointed out by
scientific clinical committees like the EORTC (European Organization for Research
and Treatment of Cancer) Brain Metastasis Platform [62].
Although, lung cancer is the most common cause of BM, there is a lack of specific
lung cancer BM trials. As in theory, EGFR tyrosine kinase inhibitors are able to cross
the blood brain barrier due to their small molecule size. Some small studies
investigated the value of EGFR tyrosine kinase inhibitors based therapies [89-92].
Treatment with EGFR tyrosine kinase inhibitors was proven to be safe, also
sequenced after application of whole brain radiotherapy [14, 89, 93-96]. In the
extracranial disease a greater impact as observed for patients harboring an EGFR
mutation, with response rates up to 80%, indicating a therapeutic value of EGFR
tyrosine kinase inhibitors also in patients with BM [89]. A phase II study on
pemetrexed and cisplatin as first line treatment approach in asymptomatic NSCLC
BM patients revealed effectiveness with an cerebral response rate of 41.9% [97]. A
first line systemic treatment approach using premetrexed-cisplatin based therapy
might be feasible in selected NSCLC BM patients.
In view of the rising incidence of BM in HER2 positive breast cancer patients,
especially since the introduction of trastuzumab, systemic treatment of this
subpopulation with very favourable survival prognosis even upon the diagnosis of BM
has been in the center of research. Trastuzumab, although in theory unable to cross
the blood brain barrier, showed effect and impact on overall survival in patients with
BM from HER2 positive breast cancer [98, 99]. This finding underscores, that the
blood brain barrier is disrupted in BM and therapies with high molecular size have at
least partly effect [87, 100]. In terms of HER2 targeted therapies, some trials were
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conducted to investigate the value of the HER2 tyrosine kinase inhibitor lapatinib,
which in theory could better cross the blood brain barrier due to its small molecular
size. The LANDSCAPE trial investigated the combination of lapatinib and the orally
available cytotoxic drug capecitabine in newly diagnosed BM patients suffering of
HER2 positive breast cancer [101]. The combination therapy showed response rates
of 65% in the selective cohort of low to asymptomatic patients with multiple BM and
the whole brain radiation therapy could be postponed for 8 months [101]. This is of
clinical significance as patients with BM from HER2 positive breast cancer have a
median survival of 7 to 24 months upon the diagnosis of BM and are therefore at very
high risk of experiencing the late side effects of an up front whole brain radiation
therapy [68, 79].
Several new emerging drugs changed the treatment of metastatic melanoma
dramatically through the last decade. The identification of BRAF V600E mutations
and the possibly to selectively inhibit the mutated BRAF by the BRAF inhibitors
vemurafenib or dabrafinib, facilitate the first targeted therapy in metastatic melanoma
[21, 25, 102, 103]. BRAF inhibition was shown to be also feasible in patients with BM
from metastatic melanoma. Response rate of up to 40% were observed in BM for
single agent dabrafinib, suggesting that systemic therapy is valid treatment option in
patients with BM from melanoma, especially under consideration of the radio
resistance of melanoma [104]. However, the duration of response is limited and
patients experience progress in median after 4 months [104]. Recently, the addition
of a MEK inhibitor to the BRAF inhibitor was shown to reduce the BRAF inhibitor
induced side effects (especially the occurrence of secondary basal carcinoma) and
prolong the progression free survival [105]. However, no data on the combination of
BRAF and MEK inhibitor for patients with melanoma BM have been generated so far
in clinical trials.
An emerging treatment option in patients with metastatic melanoma is the application
of immune checkpoint inhibitors [21, 106, 107]. Immune checkpoint inhibitors can be
applied irrespective of the BRAF mutation status [108, 109]. Immune checkpoint
inhibitors, like the CTL4 antibody ipilimumab or the PD1 antibody nivolumab, boost
the host immune response by inhibiting the inhibitors signals of the T-cell response,
induced by the immunosuppressive properties of the tumour. Therefore, the “real”
immune response is unmasked by inhibiting the tumour immune inhibiting properties
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[110, 111]. However, no immediate tumour shrinkage is evident after application of
immune checkpoint inhibitors, as the immune response and the therapeutic effect
need several months to reveal the full potential. Therefore, patients with fast
progressing highly symptomatic disease and short survival prognosis are unlikely to
benefit of an immune checkpoint based therapy [108]. The response to immune
checkpoint inhibitors differs from the response to cytotoxic chemotherapy by the
observation that about 20% of patients experience a long-term response up to years
after the induction of the immune checkpoint inhibitor [112]. The right selection of
patients, furthermore the decision whether therapeutic benefit is expected from the
immune checkpoint inhibitor based therapy or a fast acting, tumour shrinking
treatment approach is needed, is currently the matter of intense research. In this
context, level of LDH, Karnofsky performance score and the presence of BM were
postulated as negative predictors for the benefit of an immune checkpoint inhibitor
based therapy [108, 113, 114]. Although, patients with melanoma BM have in general
a very impaired survival prognosis, some patients have a slow progressing,
asymptomatic disease and might profit from an immune checkpoint inhibitor based
treatment strategy. A phase II trial showed a response rate for up to 20% for
ipilimumab monotherapy in patients with not otherwise treated melanoma BM [115]. It
has to be taken into account that the majority of patients was asymptomatic and did
not need any steroid therapy or was symptom free and on stable steroid dosage. An
Italian population based experience on the extended access program of ipilimumab
supported these findings, suggesting that immune checkpoint inhibitors might be a
valid treatment option in selected melanoma BM patients [116]. In terms of predictive
markers for the response to immune checkpoint inhibitors several studies are on-
going. Currently, the immune score is based on the density of CD3 and CD8 positive
tumour infiltrating lymphocytes is investigation. Further, PD-L1 expression on tumour
cells is considered as predictive marker for response to immune checkpoint inhibitors
[60, 117]. However, none of these have yet been investigated in BM.
No BM specific trials have been conducted for the more infrequent causes of BM like
colorectal or kidney cancer.
Besides the tumour specific treatment, most patients need additional supportive,
symptom controlling therapies including steroids and antiepileptic drugs. According to
the current standard of research, no prophylactic antiepileptic treatment should be
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applied, especially regarding possible side effects. Only patients who experienced at
least some seizure should be treated for at least six months and than re-evaluated
[118]. The main symptoms of BM are caused by space occupation due to the tumour
surrounding oedema. Steroids are frequently applied for reduction of the peritumoural
oedema. However, steroid cause several severe side effects like iatrogenic Cushing
syndrome, myopathy, diabetes and psychological disorders. Due to this unfavourable
side effect of steroids, other systemic treatment approaches of oedema reduction
should be explored. Favourable results with the application of VEGF antibody
bevacizumab in patients lacking further local treatment options and suffering of large
peritumoural oedema were reported in case reports [119].
A promising and emphasizing new approach in BM research is the prevention of BM
[62]. Targeted therapies might be able to act on circulating tumour cells preventing
the crucial steps of the brain metastatic cascade rather than to be active in already
established BM, that are in least in part protected by the blood brain barrier [40]. This
theory is supported by several preclinical studies. NSCLC BM were shown to highly
depend on neoangiogenesis and application of the VEGF antibody bevacizumab
before the establishment of BM efficiently inhibited the outgrowth of micrometastases
to macrometastases [43]. Interestingly, bevacizumab based treatment was shown to
reduce the incidence of BM as first site of recurrence in patients with advanced
NSCLC [62, 120]. Application of the integrin inhibitor intetumumab was shown to
reduce number and size of BM in a breast cancer BM mouse model [45]. However,
efficacy of intetumumab in various frequent primaries of BM has not been
investigated yet. Clinical investigations have populated a BM prophylactic value for
various substances. Treatment with EGFR tyrosine kinase inhibitors was shown to
reduce the incidence of BM in patients with EGFR mutated NSCLC and treatment
with the VEGF receptor tyrosine kinase inhibitor sorafenib was found to reduce the
incidence of BM in patients with advanced renal cell carcinoma [27, 121]. Only one
randomized trial investigated the prophylactic value of target therapies. A BM
prophylactic value was postulated for lapatinib as compared to trastuzumab as
lapatinib is able to cross the blood brain barrier. However, no significant difference in
the occurrence of BM as first site of recurrence was observed [52]. Future studies
might focus on the approach to prevent BM.
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5 Aims of this thesis
a. Which clinical characteristics at the time of diagnosis of BM influence survival?
b. Do established prognostic indices, which have largely been developed in
patients enrolled in clinical trials, have value in a real-life population of patients
with BM?
c. Does the expression of HIF 1 alpha, Ki67 proliferation index and microvascular
density as well as angiogenic pattern in BM specimens correlate with
treatment response and survival?
d. Do radiological findings correlate with tissue based characteristics and survival
in patients with BM?
e. Do the invasion patterns of BM in the surrounding brain parenchyma correlate
with primary tumour type?
f. Characterization of the adaptive and innate inflammatory response in and
around BM. Does the inflammatory pattern differ between primary tumour
types?
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6 Results 6.1 Brain Metastases free survival differs between breast cancer subtypes.
Prologue BM are a frequent complication in breast cancer [6, 122]. In order to guide the
development of preventive trials, a better knowledge on the clinical course of patients
developing BM is needed. The breast cancer subtypes have a known impact on the
propensity for BM as well as on the prognosis upon the diagnosis of BM [19].
However, the impact of the breast cancer subtype on time to development of BM has
not been investigated. In general, BM are regarded a late complication during the
metastatic disease. However some patients present with early development of
symptomatic BM. In the paper “Brain Metastases free survival differs between breast
cancer subtypes” we investigated the time from diagnosis of the metastatic breast
cancer to the development of BM in order to identify patients developing particularly
early or late BM during the clinical course. Patients with triple negative breast cancer
had a significantly shorter time till development of BM compared to patients with
HER2 positive or luminal breast cancer [123].
Brain metastases free survival differs between breast cancersubtypes
A Berghoff1,2, Z Bago-Horvath1,3, C De Vries1,2, P Dubsky1,4, U Pluschnig1,2, M Rudas1,3, A Rottenfusser1,5,M Knauer6, H Eiter7, F Fitzal1,4, K Dieckmann1,5, RM Mader1,2, M Gnant1,4, CC Zielinski1,2, GG Steger1,2,M Preusser1,2 and R Bartsch*,1,2
1Comprehensive Cancer Center Vienna, Medical University of Vienna, Waehringer Guertel 18-20, A-1090 Vienna, Austria; 2Department of Medicine I,Clinical Division of Oncology, Medical University of Vienna, Waehringer Guertel 18-20, A-1090 Vienna, Austria; 3Department of Pathology, MedicalUniversity of Vienna, Vienna, Austria; 4Department of Surgery, Medical University of Vienna, Vienna, Austria; 5Department of Radiotherapy, MedicalUniversity of Vienna, Vienna, Austria; 6Department of Surgery, Academic Teaching Hospital Feldkirch, Feldkirch, Austria; 7Department of Radiotherapy,Academic Teaching Hospital Feldkirch, Feldkirch, Austria
BACKGROUND: Brain metastases (BM) are frequently diagnosed in patients with HER-2-positive metastatic breast cancer; in addition, anincreasing incidence was reported for triple-negative tumours. We aimed to compare brain metastases free survival (BMFS) of breastcancer subtypes in patients treated between 1996 until 2010.METHODS: Brain metastases free survival was measured as the interval from diagnosis of extracranial breast cancer metastases untildiagnosis of BM. HER-2 status was analysed by immunohistochemistry and reanalysed by fluorescent in situ hybridisation if a score of2þ was gained. Oestrogen-receptor (ER) and progesterone-receptor (PgR) status was analysed by immunohistochemistry. Brainmetastases free survival curves were estimated with the Kaplan–Meier method and compared with the log-rank test.RESULTS: Data of 213 patients (46 luminal/124 HER-2/43 triple-negative subtype) with BM from breast cancer were available for theanalysis. Brain metastases free survival differed significantly between breast cancer subtypes. Median BMFS in triple-negative tumourswas 14 months (95% CI: 11.34–16.66) compared with 18 months (95% CI: 14.46–21.54) in HER-2-positive tumours (P¼ 0.001)and 34 months (95% CI: 23.71–44.29) in luminal tumours (P¼ 0.001), respectively. In HER-2-positive patients, co-positivity for ERand HER-2 prolonged BMFS (26 vs 15 m; P¼ 0.033); in luminal tumours, co-expression of ER and PgR was not significantly associatedwith BMFS. Brain metastases free survival in patients with lung metastases was significantly shorter (17 vs 21 months; P¼ 0.014).CONCLUSION: Brain metastases free survival in triple-negative breast cancer, as well as in HER-2-positive/ER-negative, is significantlyshorter compared with HER-2/ER co-positive or luminal tumours, mirroring the aggressiveness of these breast cancer subtypes.British Journal of Cancer (2012) 106, 440–446. doi:10.1038/bjc.2011.597 www.bjcancer.comPublished online 10 January 2012& 2012 Cancer Research UK
Keywords: advanced breast cancer; brain metastases; carcinomatous meningitis; human epidermal growth factor receptor 2 (HER-2)-positive breast cancer; triple-negative disease
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In the last decade, overall survival of metastatic breast cancerpatients has improved due to advances in systemic treatment(Lin and Winer, 2007; Kiely et al, 2011). Despite this success, therising incidence of brain metastases (BM) as late complicationbecame a major clinical problem (Weil et al, 2005; Pestalozzi et al,2006). About 10–15% of all metastatic breast cancer patients willeventually develop symptomatic BM during their course of disease.Brain metastases decrease quality of life and increase morbidityand mortality. Currently, survival of patients with BM ranges from2 to 16 months (Weil et al, 2005).
Prognosis and clinical behaviour of breast cancer differsbetween subtypes (Perou et al, 2000; Sorlie et al, 2001; Kenneckeet al, 2010). Patients with triple-negative tumours, defined by the
absence of oestrogen-receptor (ER), progesterone-receptor (PgR)and Her-2-receptor expression, are at higher risk of beingdiagnosed with BM compared with the luminal or HER-2-positivesubtypes (Heitz et al, 2009). HER-2-positive patients, on the otherhand, have a higher incidence of BM than patients with HER-2-negative breast cancer (Sanna et al, 2007). Especially since theintroduction of trastuzumab, a growing incidence of symptomaticBM was reported. As trastuzumab cannot penetrate trough theblood–brain barrier due to its molecular weight, a tumour cellsanctuary is created. Furthermore, trastuzumab improves systemicdisease control, which leads to a ‘unmasking’ of BM in patients whowould otherwise have died from progression of systemic disease.
Apart from triple-negative or HER-2-positive disease, estab-lished risk factors for the development of BM are young age at firstdiagnosis, presence of lung metastases and short disease-freeinterval (Weil et al, 2005).
Treatment of BM remains challenging and consists of surgery,whole-brain irradiation, radiosurgery and systemic therapy (Weilet al, 2005). Surgery or radiosurgery is an option for patients with
Received 2 November 2011; revised 7 December 2011; accepted 16December 2011; published online 10 January 2012
*Correspondence: Dr R Bartsch;E-mail: [email protected]
British Journal of Cancer (2012) 106, 440 – 446& 2012 Cancer Research UK All rights reserved 0007 – 0920/12
www.bjcancer.com
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one to three metastases. Whole-brain irradiation, while offeringactivity also in patients with 43 metastases, causes long-termsides effects such as memory loss and cognitive impairment. Effectof systemic therapy is limited by the blood–brain barrier. Thus,limited therapy options for symptomatic BM substantiates theurgent need for better understanding of risk factors andpossibilities of prevention.
Importantly, treatment with lapatinib resulted in a decreasedincidence of BM in HER-2-positive disease (Geyer et al, 2006).Other preventive measures such as prophylactic cranial radio-therapy, while well established in small-cell-lung cancer, is notroutinely used in breast cancer, as no survival benefit was observedso far (Saip et al, 2009). Even screening for BM is not a part ofroutine follow-up, as no evidence for a benefit from early detectionexists (Niwinska et al, 2007). This, however, might be rather due tothe lack of appropriate selection criteria for a potential screeningcohort. Therefore, a more precise definition of patients and breastcancer subtypes at high risk for early development of BM is needed(Heitz et al, 2009).
The objective of this study therefore was to determine clinicaland histopathological risk factors associated with early develop-ment of BM. This might identify a high-risk population derivingthe largest benefit from screening and prevention.
PATIENTS AND METHODS
Two Austrian centres contributed information relating to demo-graphics, case history and survival. Data were processed at theMedical University of Vienna, Austria. This retrospective analysiswas conducted in accordance with the ethical regulations of theMedical University of Vienna and approval by the local ethicscommittee was obtained.
Patients
Patients treated for symptomatic BM from breast cancer between1996 and 2010 were identified from a breast cancer database. Noroutine screening for BM was conducted, and none of the patientsavailable for this analysis participated in trials of BM screening orprevention. Data were analysed as of August 2011.
Hormone-receptor and HER-2 status
Oestrogen-receptor and progesterone-receptor status was assessedby immunohistochemistry (ERa antibody, clone 1D5, Dako A/S,Glostrup, Denmark; and PR antibody, Dako A/S). Receptorexpression was estimated as the percentage of positively stainedtumour cells. Results were given as 1þ , 2þ and 3þ positive ornegative staining, with a cutoff value of o10% positive tumourcells (Hammond et al, 2010). HER-2 status was assessed byimmunohistochemistry (Herceptest; Dako A/S) or dual colourfluorescent in situ hybridisation (FISH; PathVision HER-2 DNAprobe kit, Vysis Inc., Downers Grove, IL, USA). Tumours wereclassified as HER-2-positive if they had a staining intensity of 3þon the Herceptest; if a score of 2þ was gained, tumours werereanalysed by FISH (Wolff et al, 2007).
Breast cancer subtypes
Breast cancer subtypes were defined according to the results of theimmunohistochemical analysis. Tumours heralding hormone-receptor expression in the absence of HER-2-receptor over-expression were summarised as belonging to the luminal subtype,without further differentiation. The HER-2 subtype was defined byoverexpression of the HER-2 receptor and/or amplification of theHER-2/neu gene. Tumours were defined as triple-negative in theabsence of ER, PgR as well as HER-2 expression (Anders et al,2011; Duan et al, 2011).
Treatment plan and patient evaluation
In metastatic patients, routine re-evaluation of patients’ tumourstatus was performed every 3 months with contrast-enhanced CTscans of the chest and the abdomen, with additional work up ifindicated. In patients with early breast cancer, follow-up was doneaccording to local protocol. Brain imaging was performed onlywhen symptoms of CNS metastases or carcinomatous meningitisoccurred. Brain metastases were diagnosed by CT and/or MRI andhistologically confirmed in case neurosurgery was performed.Carcinomatous meningitis was defined as enhancement of themeninges as detected by MRI and/or detection of tumour cells inthe cerebrospinal fluid. Metastatic breast cancer and BM weretreated according to the current evidence-based standard of careincluding surgery, radiotherapy, systemic therapy, targetedtherapy and endocrine treatment (Beslija et al, 2007). Follow-upof BM was conducted every 3 months with either contrast-enhanced cranial CT or MRI scans.
Study end points
We defined brain metastases free survival (BMFS) as the intervalfrom diagnosis of metastatic disease until the development of BM.Therefore, patients with BM as first site of metastatic disease wereexcluded from analysis of BMFS. Furthermore, we analysed theassociation of breast cancer subtypes with brain as first site ofdisease progression, number of BM, time to development of BM(o24 months vs 448 months), and development of carcinoma-tous meningitis.
Statistical analysis
Brain metastases free survival was estimated by the Kaplan–Meierproduct limit method. To test the differences between BMFScurves, the log-rank test was used. For correlation of twoparameters, the w2-test and the likelihood ratio were used. Two-tailed P-values o0.05 were considered to indicate statisticalsignificance. Variables exhibiting significance (Po0.05) or nearsignificance (Po0.09) at univariate analysis were included into aCox proportional hazards models.
The association of the following variables with BMFS wereinvestigated using univariate analysis: breast cancer subtype(luminal vs triple-negative vs Her-2-positive), presence of pulmo-nary metastases, presence of any visceral metastases, age atprimary diagnosis (465 years; o35 years), grading (grades 1 and2 vs 3), stage at primary diagnosis (localised vs metastatic) andtime to progression after first diagnosis of early breast cancer(o24 months vs 424 months). Correlation analysis wasperformed for subtype and BM as first site of recurrence, time toprogression to the brain (o24 months, 448 months), number ofBM (1–3 vs 43 BM) and presence of carcinomatous meningitis.
All statistics were calculated using statistical package for thesocial sciences (SPSS) 17.0 software (SPSS Inc., Chicago, IL, USA).
RESULTS
Patient characteristics
Overall, 250 patients with BM from breast cancer were identifiedfrom two Austrian centres between 1996 and 2010 (absoluteincidence of breast cancer in Austria 1996–2010: 68 661 patients).Thirty-seven patients had to be excluded due to incompleteinformation about breast cancer subtype (e.g., missing dataconcerning Her-2 status, hormone-receptor status). Therefore,213 patients were available for this retrospective analysis.
According to the immunohistochemical analysis of the primarytumour, patients were divided into three groups: luminal subtype,HER-2 subtype and triple-negative subtype. Forty-six patients
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(21.6%) belonged to the luminal subtype, 124 patients (58.2%) tothe HER-2 subtype and 43 patients (20.2%) to the triple-negativesubtype. Forty-four patients (20.7%) had BM as first site ofmetastatic disease and therefore were excluded from the analysis ofBMFS. All patients were treated according to the current standardof treatment for breast cancer and metastatic breast cancer,respectively (Beslija et al, 2007; Goldhirsch et al, 2007). In all,89.9% were treated with chemotherapy-based regime for meta-static disease before the diagnosis of BM. The remaining 10.1%of patients were treated with either endocrine monotherapy ortrastuzumab monotherapy. Patient characteristics are summarisedin Table 1.
Brain metastases free survival
Median BMFS was 19 months (95% CI: 15.18– 22.82) in thepopulation of 169 patients with metastatic breast cancer who didnot have BM as first site of progression. Univariate analysisrevealed a significant difference in median BMFS between breastcancer subtypes. In the luminal subtype, median BMFS was 34months (95% CI: 23.71 –44.29) compared with 18 months (95% CI:14.46–21.54) in the HER-2-positive subtype (P¼ 0.001, log-ranktest) and 14 months (95% CI: 11.34– 16.66) in the triple-negativesubtype (P¼ 0.001, log-rank test) (Figure 1).
In patients with lung metastases, median BMFS was 17 months(95% CI: 14.10 –19.90) compared with 21 months (95% CI: 15.45 –26.55) in patients with no evidence of lung metastases (P¼ 0.014,log-rank test) (Figure 2). In patients with time to extracranialprogression after first diagnosis of early breast cancer of o24months, median BMFS was significantly shorter compared topatients with time to extracranial progression after first diagnosisover 24 months (14 vs 24 months; Po0.001, log-rank test). None ofthe other variables included into the univariate model displayed asignificant influence on BMFS (Table 2).
Table 1 Patient characteristics (a) without BM and (b) with BM as firstsite of progression
(a)Entered
patients (n¼ 169)
Characteristics n %
Median age at first diagnosis (years) 50Range 25– 82
Age 465 years 17 10.1Age o35 years 17 10.1
Grade 3 tumour 116 73.9Invasive ductal carcinoma 135 87.1Stage IV 32 18.9
SubtypeLuminal subtype 36 21.3HER-2 subtype 102 60.4Triple-negative subtype 31 18.3
Adjuvant chemotherapy 115 83.9Adjuvant endocrine therapy 53 38.1Adjuvant trastuzumab 12 8.8Median time to progression (months) 22Range 0 –166Visceral metastases 121 72.0Brain as the first site of metastatic disease 0 0
Median metastatic sites 2Range 1– 5
Lung 79 47.0Liver 71 42.3Bones 81 48.2Lymph nodes 48 28.6Soft tissue 54 32.1Skin 17 10.1Others 11 6.6
Palliative chemotherapy before BM 152 89.9Palliative endocrine therapy before BM 63 37.5Palliative trastuzumab before BM 85 50.3Palliative lapatinib before BM 2 1.2
Response to systemic therapy at time of BM diagnosisCR 3 3.3PR 29 31.9SD 32 35.2PD 27 29.7
Median BM free survival (months) 19Range 1 –170Median OS from first diagnosis (months) 58.5Range 3 –218Median OS from diagnosis of metastatic disease 33Range 2 –125Median OS from diagnosis of BM (months) 5.5Range 0 –81
(b)Entered
patients (n¼ 44)
Characteristics n %
Median age at first diagnosis (years) 54Range 27– 79
Age 465 years 5 11.4Age o35 years 4 9.1
Grade 3 tumour 31 75.6Invasive ductal carcinoma 30 73.2Stage IV 4 9.1
SubtypeLuminal subtype 10 22.7HER-2 subtype 22 50.0Triple-negative subtype 12 27.3
Adjuvant chemotherapy 33 80.5Adjuvant endocrine therapy 13 32.5Adjuvant trastuzumab 4 10.0median time to progression (months) 18.5Range 0 –89Visceral metastases 17 38.6Brain as only site of metastatic disease 22 50
Median metastatic sites 1Range 1– 6
Lung 6 13.6Liver 15 34.1Bones 11 25.0Lymph nodes 6 13.6Soft tissue 4 9.1Skin 0 0Others 1 2.3
Median OS from first diagnosis (months) 29Range 0 –121Median OS from diagnosis of metastatic disease (months) 9Range 0 –50Median OS from diagnosis of BM (months) 9Range 0 –50
Abbreviations: CR¼ complete response; PR¼ partial response; SD¼ stable disease;PD¼ progressive disease; BM¼ brain metastases; OS¼ overall survival. Character-istics grading, staging, subtype are from time point of first diagnosis. Characteristicsmetastatic sites are from time point of diagnosis of brain metastases.
Table 1 (Continued)
(b)Entered
patients (n¼44)
Characteristics n %
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In the multivariate analysis of BMFS, presence of lungmetastases and breast cancer subtype as well as time toextracranial progression after first diagnosis of early breast cancerretained statistical significance. Hazard ratio (HR) for non-luminalbreast cancer subtypes was 1.51 (95% CI: 1.17– 1.95; P¼ 0.002, Coxproportional hazards model), 1.39 (95% CI: 1.01–1.93; P¼ 0.047,Cox proportional hazards model) for presence of lung metastasesand 1.49 (95% CI: 1.07–2.08; P¼ 0.019, Cox proportional hazardsmodel) for time to progression after first diagnosis of early breastcancer of o24 months, respectively.
v2-test and likelihood ratio
The likelihood ratio of developing BM as first site of metastaticdisease did not differ significantly between the breast cancersubtypes (luminal subtype 21.7%; HER-2 subtype 17.7%; triple-negative subtype 20.7%; P¼ 0.372, w2-test).
On the other hand, the likelihood of being diagnosed with BMin o24 months (BMFS o24 months) correlated significantly withthe breast cancer subtype. Within the luminal subtype, 30.6%(11 patients) of patients developed BM in o24 months; in theHER-2 subtype, 59.4% (60 patients) and in the triple-negativesubtype, 77.4% (24 patients) of patients had a BMFS of o24months (Po0.001, w2-test). Furthermore, the likelihood of BMFS448 months again correlated significantly with the breast cancersubtype. Only one patient (3.2%) within the triple-negativesubtype had a BFMS 448 months, while 12 patients (17.6%) ofthe HER-2 group and 12 patients (33.3%) of the luminal group hada BMFS of 448 months, respectively (P¼ 0.006, w2-test).
In all, 92 (48.7%) patients had over three BM at first diagnosis ofBM. Accordingly, 32.3% of patients had a single metastasis, 9.5%had two BM and 9.5% three BM. The number of BM at time of firstdiagnosis of BM did not differ between the subtypes. In all, 24patients (58.5%) within the luminal subtype had three or lessmetastases, corresponding numbers for the HER-2-positive andtriple-negative subtypes are 50.9% and 50.0%, respectively(P¼ 0.666, w2-test).
The likelihood ratio for the development of carcinomatousmeningitis again significantly correlated with breast cancersubtype. In all, 19.6% (nine patients) of the luminal subtypecompared with 3.2% (four patients) of the HER-2 subtype and9.3% (four patients) of the triple-negative subtype developedcarcinomatous meningitis (P¼ 0.002, w2-test).
BMFS in subsets of the HER-2-positive subtype
In HER-2-positive patients, we further analysed whether HER-2/ERco-positivity or trastuzumab-based therapy had any influence onBMFS. In patients who received trastuzumab-based therapy beforethe development of BM, median BMFS was 17 months (95% CI:13.41–20.53) compared with 21 months (95% CI: 8.53–33.47) inHER-2-positive patients who had not received trastuzumab-basedtreatment (P¼ 0.939, log-rank test). Therefore, trastuzumab didnot prolong BMFS.
In patients with ER/HER-2 co-positive tumours, median BMFSwas 26 months (95% CI: 16.40 –35.60) and therefore significantly
1.0Breast cancer subtype
Luminal subtypeHer2 subtypeTriple-negative subtype
P=0.001
0.8
0.6
0.4
0.2
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0.0
0 50 100
Brain metastases free survival (months)
150 200
Survival functions
Figure 1 Kaplan–Meier estimates for BMFS. Median BMFS in triple-negative subtype was 14 months (95% CI: 11.34–16.66) compared with 18months (95% CI: 14.46–21.54) in HER-2 subtype and 34 months (95% CI:23.71–44.29) in luminal subtype (P¼ 0.001, log-rank test).
1.0
Survival functions
Presence of lungmetastases
P=0.014
NoYes0.8
0.6
0.4
0.2
Cum
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0.0
0 50 100Brain metastases free survival (months)
150 200
Figure 2 Kaplan–Meier estimates for BMFS. Median BMFS in patientswith the presence of lung metastases was 17 months (95% CI: 14.10–19.90) compared with 21 months (95% CI: 15.45–26.55) in patients withno evidence of lung metastases (P¼ 0.014, log-rank test).
Table 2 Univariate analysis: factors associated with brain metastases freesurvival (BMFS)
FactorMedian BMFS
(months) 95% CI P-value
SubtypeLuminal subtype 34 23.71–44.29 0.001HER-2 subtype 18 14.47–21.54Triple-negative subtype 14 11.34–16.66
Presence of metastasesVisceral 18 12.97–23.03 n.s.Pulmonary 17 14.10–19.90 0.014
Age at first diagnosiso35 years 16 11.97–20.03 n.s.4 65 years 21 8.90–33.10 n.s.
Grade 3 17 13.70–20.30 n.s.Stage IV at primary diagnosis 19 9.02–28.98 n.s.Time to progression o24 months 14 12.09–15.91 o0.001
Abbreviation: CI¼ confidence interval.
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longer than in patients with ER-negative/HER-2-positive disease(15 months; 95% CI: 10.77–19 –23; P¼ 0.033, log-rank test)(Figure 3).
In a further step, we investigated whether palliative endocrinetherapy in ER/HER-2 co-positive patients had a significant impacton BMFS, as tamoxifen has the ability to pass the blood–brainbarrier. Indeed, BMFS in patients who received palliative endo-crine therapy was 30 months (95% CI: 16.17–43.83) comparedwith 14 months (95% CI: 10.31 –17.68) months in patients with ER/HER-2 co-positive disease who did not receive prior palliativeendocrine therapy (P¼ 0.004, log-rank test).
BMFS in subsets of the luminal subtype
Expression of progesterone receptor did not significantly influenceBMFS in patients with breast cancer of the luminal subtype. InPgR-positive patients, median BMFS was 35 months (95% CI:17.39–52.62) compared with 34 months (95% CI: 18.35–49.66) inPgR-negative patients (P¼ 0.692, log-rank test).
Overall survival after diagnosis of BM
Median overall survival after the diagnosis of BM was 5 months(95% CI: 2.64–7. 36) in the luminal group, 7 months (95% CI:4.31– 969) in HER-2-positive group and 5 months (95% CI: 1.83–8.17) in triple-negative breast cancer patients (P¼ 0.364, log-ranktest). HER-2-positive patients treated with trastuzumab-basedtherapy after completion of local therapy for BM (surgery,radiotherapy) had a significant longer overall survival afterdiagnosis of BM (4 vs 14 months; 95% CI: 2.40–5.61 vs 7.22–20.78;Po0.001, log-rank test).
DISCUSSION
Brain metastases are an increasing issue in modern breast cancertherapy, as up to 15% of patients with stage IV disease willeventually be diagnosed with symptomatic BM (Weil et al, 2005).Therefore, development of adequate preventive strategies isurgently required.
In the field of BM prevention in Her-2-positive disease,promising results of lapatinib were reported, a dual tyrosine-kinase inhibitor of EGFR and HER-2 (Cameron et al, 2008). Otherpreventive strategies such as prophylactic cranial irradiationcurrently have no role in breast cancer treatment, as supportingdata are missing (Saip et al, 2009). Also, screening for BM is notestablished, since early detection of BM was not found to influencesurvival henceforth (Niwinska et al, 2010). This, however, mightresult from the inclusion of patients at relatively low risk fordeveloping BM into the respective clinical trials; therefore, a betterdefinition of risk groups is warranted as first step to establisheffective strategies of screening and prevention.
Clinical and translational research redefined breast cancer as aheterogeneous disease, divided into different subtypes defined bydivergent gene expression profiles. In daily clinical practice,grading as well as immunohistochemical assessment of hormone-receptor status, Her-2, and Ki-67 are usually used as approxima-tion. Therefore, breast cancer is assigned to the luminal, the HER-2or the triple-negative phenotype at first diagnosis. This classifica-tion influences estimation of prognosis and treatment decisions(Perou et al, 2000; Sorlie et al, 2001, 2003). In the present study, weshow that different breast cancer subtypes associate with time todevelopment of BM. Patients with triple-negative disease had asignificantly shorter BMFS (14 months) compared with 34 monthsin patients with luminal tumours (P¼ 0.001). Previously, thetriple-negative subtype was identified to have a higher overall riskof developing BM; furthermore, BM are diagnosed relatively earlyduring the course of disease (Pestalozzi et al, 2006; Heitz et al,2009). Here, we could demonstrate tremendous differences ofBMFS in triple-negative disease in comparison to luminal tumours,as BMFS of luminal subtypes is almost doubled. This findingindicates that triple-negative breast cancer warrants furtherresearch of BM-preventive strategies (Pestalozzi, 2009).
A higher incidence of BM was observed in HER-2-positivedisease as well. Different authors suggested a connection totrastuzumab, a monoclonal antibody targeting the extracellulardomain of HER-2. As trastuzumab cannot penetrate the blood–brain barrier, the CNS becomes a safe haven for tumour cells(Clayton et al, 2004). Also, improved control of systemic diseasemay eventually lead to the ‘unmasking’ of BM (Lin and Winer,2007). In our analysis, BMFS within the HER-2 subtype was 18months and was significantly different from the other two subtypes(P¼ 0.001). Compared with luminal cancers, shorter BMFS wasobserved in Her-2-positive disease, while BMFS was longercompared with triple-negative tumours. No influence of trastuzu-mab-based therapy on BMFS was observed. This finding indicatesthat biological behaviour rather than systemic treatment definesthe risk for early or late development of BM in patients with HER-2-positive breast cancer (Burstein et al, 2005; Pestalozzi et al, 2006;Lin and Winer, 2007).
Several studies postulated the absence of ER expression as anunfavourable factor for the probability of developing BM (Slimaneet al, 2004; Weil et al, 2005). Therefore, we performed an analysisof BMFS in the HER-2-positive subtype in dependence of ERexpression. Patients with ER/HER-2 co-positive disease wereshown to have significantly longer BMFS compared with patientswith ER-negative/HER-2-positive disease (26 months vs 15months; P¼ 0.033). This once again shows that the Her-2-positivephenotype comprises heterogeneous subtypes.
Brain metastases are usually diagnosed rather late in thecourse of metastatic disease (Weil et al, 2005). Previous studiesindicate a correlation of visceral and pulmonary metastasesand the occurrence of BM (Weil et al, 2005; Kennecke et al,2010). Our findings further support this investigation, aspulmonary metastases remained a significant risk factor associ-ated with shorter BMFS in the Cox regression model (HR 1.49;P¼ 0.016). Therefore, we suggest that patients with triple-negativetumours and pulmonary metastases might be the most suitable
1.0
Survival functions
P=0.033
HER-2 subtypeHER-2 positive/ER-negativeHER-2/ER co-positive
0.8
0.6
0.4
0.2
Cum
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0.0
0 50 100
Brain metastases free survival (months)
150 200
Figure 3 Kaplan–Meier estimates for BMFS. Median BMFS in HER-2/ERco-positive patients was 26 months (95% CI: 16.40–35.60) compared to(15 months; 95% CI: 10.77–19–23) in patients with HER-2-positive/ER-negative disease (P¼ 0.033, log-rank test).
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group for prospective trials investigating strategies of screeningand prevention.
The number of BM is an important factor for prognosis as wellas treatment, as surgery or radiosurgery is usually only applied inpatients with oligometastatic (1–3 metastases) disease (Kamar andPosner, 2010; Niwinska et al, 2011a, b). Recently, an influence ofbreast cancer subtypes on the number of BM at first diagnosis waspostulated. Oestrogen-receptor-positive patients, according to onestudy, might be more likely to develop oligometastatic braininvolvement (Garg et al, 2011). In our homogenous, largecollective, however, we cannot support those findings; thelikelihood for oligometastatic involvement did not differ betweenthe breast cancer subtypes.
Carcinomatous meningitis, just like BM, occurs late during thecourse of the disease and treatment options are very limited (deAzevedo et al, 2011). While breast cancer subtype influencesoverall survival after the diagnosis of carcinomatous meningitis,little is known about risk factors (Lee et al, 2011; Niwinska et al,2011a, b). In our study, patients with luminal subtype were at
higher risk for the development of carcinomatous meningitiscompared to patients with HER-2 or triple-negative disease (19.6%vs 3.2% vs 9.3%; P¼ 0.002). Although the small sample size has tobe taken into account, this apparent contradiction to solid BMwarrants further investigation.
In conclusion, our study shows that patients with triple-negativeas well as patients with ER-negative/HER-2-positive disease are athighest risk for developing BM early during their course of disease.The risk is further raised by the presence of pulmonary metastases.This analysis might help in defining the optimal breast cancerpatient population for future prospective trials of BM screeningand prevention.
ACKNOWLEDGEMENTS
Apart from the authors, the following persons contributed to thisstudy: Sabine Fromm, Gabriela Altorjai, Gudrun Boeckmann,Alexander DeVries and Carina Dinhof.
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6.2 Brain-only metastatic breast cancer is a distinct clinical entity characterized by favourable median overall survival time and a high rate of long-term survivors.
Interlude Survival estimation is the basis for treatment decisions in patients with newly
diagnosed BM [124]. Further, the precise definition of prognostically homogenous
cohorts is needed for the establishment of clinically meaningful clinical trials [63,
125]. The DS-GPA for patients with BM from breast cancer includes breast cancer
subtype, age and Karnofsky performance score [68]. Of notice, the DS-GPA is based
on the data of patients eligible for inclusion in a clinical trial and might therefore
represent an inclusion bias. Therefore, we aimed to investigate clinical prognostic
factors in a real life cohort of patients with BM from breast cancer. Interestingly, we
identified patients with brain only metastatic breast cancer as a distinct prognostic
subgroup with frequent occurrence of long-term survival [126]. Therefore, information
on the status of the extracranial disease might add additional value in the prognostic
evaluation of patients with BM from breast cancer.
Brain-only metastatic breast cancer is a distinct clinical entitycharacterised by favourable median overall survival time anda high rate of long-term survivors
AS Berghoff1,2, Z Bago-Horvath2,3, A Ilhan-Mutlu2,4, M Magerle2,4, K Dieckmann2,5,6, C Marosi2,4, P Birner2,3,G Widhalm2,5,6, GG Steger2,4, CC Zielinski2,4, R Bartsch2,4 and M Preusser*,2,4
1Institute of Neurology, Medical University of Vienna, Vienna, Austria; 2Comprehensive Cancer Center, Vienna, Austria; 3Institute of Clinical Pathology,Medical University of Vienna, Vienna, Austria; 4Department of Medicine I, Clinical Division of Medical Oncology, Medical University of Vienna,Vienna, Austria; 5Department of Radiotherapy, Medical University of Vienna, Vienna, Austria; 6Department of Neurosurgery, Medical University ofVienna, Vienna, Austria
BACKGROUND: The clinical course of breast cancer patients with brain metastases (BM) as only metastatic site (brain-only metastaticbreast cancer (BO-MBC)) has been insufficiently explored.METHODS: All breast cancer patients with BM treated at our institution between 1990 and 2011 were identified. For each patient, fullinformation on follow-up and administered therapies was mandatory for inclusion. Oestrogen receptor, progesterone receptor andHer2 status were determined according to standard protocols. Statistical analyses including computation of survival probabilities wasperformed.RESULTS: In total, 222 female patients (26% luminal; 47% Her2; 27% triple negative) with BM of MBC were included in this study. In all,38/222 (17%) BM patients did not develop extracranial metastases (ECM) during their disease course and were classified as BO-MBC. Brain-only-MBC was not associated with breast cancer subtype or number of BM. The median overall survival of BO-MBCpatients was 11 months (range 0–69) and was significantly longer than in patients with BM and ECM (6 months, range 0–104;P¼ 0.007). In all, 7/38 (18%) BO-MBC patients had long-term survival of 43 years after diagnosis of BM and long-term survival wassignificantly more common in BO-MBC patients as compared with BM patients with ECM (Po0.001).CONCLUSIONS: Brain-only metastatic behaviour occurs in around 17% of breast cancer with BM and is not associated with breastcancer subtype. Exploitation of all multimodal treatment options is warranted in BO-MBC patients, as these patients have favourableprognosis and long-term survival is not uncommon.British Journal of Cancer (2012) 107, 1454–1458. doi:10.1038/bjc.2012.440 www.bjcancer.comPublished online 9 October 2012& 2012 Cancer Research UK
Keywords: metastatic breast cancer; brain metastases; brain-only metastatic behaviour; prognosis; overall survival; breast cancersubtypes
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Metastatic breast cancer (MBC) is the leading cause of cancer-relateddeath in women (De Vita et al, 2012). The overall survival (OS) ofpatients with MBC constantly improved over the past decades mainlydue to advances in systemic treatment (Kiely et al, 2011). Despitethese advances, the development of brain metastases (BM) remains asevere and devastating complication decreasing quality of life andincreasing morbidity and mortality (Weil et al, 2005). The incidenceseems to be rising as up to 40% of patients will develop BM duringtheir course of disease (Weil et al, 2005; Pestalozzi et al, 2006).Treatment options for patients with BM are limited. Local treatmentapproaches include surgery, radiosurgery and radiotherapy depend-ing on number of BM, status of systemic disease and performancestatus of the patient (Lin et al, 2004). Although some trials postulate apositive impact of systemic treatment, the true effect of systemictherapy approaches on BM remains unclear (Bartsch et al, 2007, 2012;
Lin et al, 2008). Survival of BM patients varies with breast cancersubtypes, however, the median OS remains limited ranging from 3.5to a maximum of 25.3 months (Sperduto et al, 2012).
Despite the general poor prognosis, we observed patients withBM from MBC with long-term survival of 436 months after thefirst diagnosis of BM at our institution. As some patients presentedwith isolated brain metastatic disease in the absence of extracranialdisease (brain-only (BO) MBC) during their course of disease, wehypothesised that patients with BO metastatic behaviour might bea distinct entity.
We undertook this study to define the clinical characteristicsand course of patients with BO-MBC and to compare it to patientswith BM and extracranial metastatic disease.
MATERIALS AND METHODS
Patients
We identified all breast cancer patients with BM treated at ourinstitution between 1990 and 2011. Diagnosis of BM was
*Correspondence: Dr M Preusser;E-mail: [email protected] 3 July 2012; revised 20 August 2012; accepted 31 August 2012;published online 9 October 2012
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performed by cranial computed tomography and/or cranialmagnetic resonance imaging (MRI). All patients were treatedaccording to the current evidence-based standard of care forsystemic disease as well as for BM. Treatment approaches includedradiosurgery, (whole brain) radiation therapy, surgicalapproaches, targeted as well as endocrine therapy and chemother-apeutic agents. For each patient, full information on clinicalcharacteristics, follow-up and administered therapies was manda-tory for inclusion.
Breast cancer subtypes
Oestrogen receptor (ER), progesterone receptor (PR) and Her2status were assessed by immunohistochemistry (ERa antibody,clone 1D5, Dako A/S, Glostrup, Denmark; and PR antibody, DakoA/S, Herceptest; Dako A/S) with a fully automated multi-modalslide-staining system (Ventana Benchmark ULTRA, Ventana,Tucson, AZ, USA). Oestrogen receptor, PR and Her2 status weredetermined according to standard protocols (Wolff et al, 2007;Hammond et al, 2010). Breast cancer subtypes were defined asluminal subtype in the presence of ER and/or PR expression andthe absence of Her2 expression, as Her2 subtype in the presence ofHer2 expression regardless of ER and PR expression, and as triple-negative subtype in the absence of ER, PR and Her2 expression.
Study endpoints
Brain-only-MBC patients were defined as breast cancer patientswith BM and the absence of extracranial metastases (ECM) duringthe entire course of the disease. We assessed the incidence of BO-MBC in relation to clinical characteristics including patient age,breast cancer subtypes (Her2-positive, triple-negative and luminalsubtypes), number of BM and evaluated OS times. Overall survivalwas defined as time from first diagnosis of BM by computedtomography and/or MRI scan till death of any cause.
Statistical analysis
For correlation of two parameters the w2 test was used. Two-tailedP-values p0.05 were considered to indicate statistical significance.For univariate survival analysis the Kaplan–Meier product limitmethod was used. To test differences between curves the log-ranktest was applied. For multivariable survival analysis a Coxregression model was used. All statistics were calculated usingstatistical package for the social sciences (SPSS) 17.0 software(SPSS Inc., Chicago, IL, USA).
RESULTS
Patients characteristics
In total, 222 female patients with a median age of 49 years at firstdiagnosis of breast cancer (range 26–79) and a median age of 53years at first diagnosis of BM (range 26–83) were included in thisstudy. All patients presented with symptomatic BM as none of thepatients underwent screening for BM. Median time from firstdiagnosis of breast cancer to diagnosis of BM was 46.9 months(range 0–200). In all, 98/222 (44%) had neurosurgical resectionand 22/222 (10%) radiosurgery as first local treatment approachfor BM. In total, 180/222 (81%) were treated with whole brainradiotherapy (WBRT). In all, 73/180 (41%) patients receivedWBRT as adjuvant therapy after neurosurgical resection, 30/180(17%) after radiosurgery and 77/180 (43%) as the only localtreatment approach for BM. Overall, 85/180 (38%) receivedsystemic therapy after diagnosis of BM. Table 1 lists furtherpatients characteristics.
Metastatic pattern
In total, 60/222 (27%) patients had BM as first site of recurrence.Of 60 patients with BM as first site of recurrence, 22 (37%)developed further systemic metastases during their course ofdisease. In all, 38/222 (17%) of BM patients did not develop ECMduring their disease course (median follow-up time 7 months;range 0–104) and were classified as BO-MBC cases. Table 1 listsfurther details on the metastatic pattern.
Brain only metastatic pattern
Brain-only metastatic behaviour was neither associated with breastcancer subtype (P¼ 0.198; w2 test) nor with number of BM(P¼ 0.110; w2 test). Further, prior trastuzumab-based therapy didnot correlate with BO metastatic behaviour (P¼ 0.090; w2 test).Distribution of diagnosis-specific graded prognostic assessment(GPA) class did not differ between the BO-MBC cohort andpatients with extracranial disease (P¼ 0.784; w2 test). Patients withBO-MBC were more likely to have neurosurgical resection as first-line therapy for BM (P¼ 0.002; w2 test) and less likely to receivechemotherapy after diagnosis of BM compared with patients withECM (P¼ 0.016; w2 test).
Overall survival
The median OS from diagnosis of BM in the entire cohort was 11.8months (range 0–104). Overall survival in luminal subtype was 9months, 7 months in Her2 subtype and 6 months in triple-negativesubtype (P¼ 0.47; log-rank test). At a median follow-up of 7months after first diagnosis of BM (range 0–104) 202/222 (91%)patients had died. The median OS of BO-MBC patients was 11months (95% CI 8.5–13.5) and was therefore significantly longerthan in patients with BM and ECM (6 months; 95% CI 3.8–8.2;P¼ 0.007, log-rank test) (Figure 1). In multivariable analysis withdiagnosis-specific GPA and number of BM, BO metastaticbehaviour remained a significant prognostic factor of OS (hazardratio 0.6; P¼ 0.029; Cox regression model). In the BO-MBC cohort,Karnofsky performance status 470 (P¼ 0.02; log-rank test), singleBM (Po0.001; log-rank test) and ER expression (P¼ 0.014; log-rank test) were associated with favourable OS in univariateanalysis and included into multivariate analysis. In multivariateanalysis Karnofsky performance status 470 (hazard ratio 0.07;P¼ 0.01; Cox regression model) and single BM (hazard ratio 0.13;P¼ 0.003; Cox regression model) remained significant (Table 2). Inall, 7/38 (18%) BO-MBC patients had long-term survival of 43years after diagnosis of BM. Compared with patients with thepresence of extracranial disease, long-term survival was signifi-cantly more common in BO-MBC patients (Po0.001; w2 test).
DISCUSSION
Our data show that BO-MBC is a distinct clinical breast cancerentity with favourable median OS time of 11 months comparedwith 6 months in BM patients with additional ECM. Interestingly,we observed survival of 436 months in 7/38 (18%) patients withBO-MBC, indicating that long-time survival is possible and notuncommon in this patient population. Our data stress thatintensive therapy with exploitation of all multimodal treatmentapproaches is warranted in breast cancer patients presenting withmetastatic disease confined to the central nervous system. Thisconclusion is well in line with the situation in non-small cell lungcancer, where stage IV patients with exclusive oligometastaticcerebral disease and limited primary tumour also constitute a goodprognosis subgroup that can be treated with curative intent(Pfannschmidt and Dienemann, 2010). High Karnofsky index, thepresence of only one BM and positive ER expression were
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favourable prognostic factors in our cohort of BO-MBC patientsand may help to adapt clinical management strategies.
The pathobiological explanation for BO metastatic involvementin breast cancer remains unclear. Previous studies have shown thatthe Her2-positive and the triple-negative breast cancer subtypesare characterised by relatively high incidences of BM (Kenneckeet al, 2010). However, in our study we found no correlation of
Table 1 Patients’ characteristic
BM and ECM(n¼ 184)
BO(n¼38)
Characteristic n % n % w2 Test/t-test
Age at first diagnosis of breast cancer (years)Median 48.5 52 0.92Range 26–79 34–79
Breast cancer subtypeLuminal 45 24.5 13 34.2 0.19Her2-positive 92 50.0 13 34.2Triple-negative 47 25.5 12 31.6
Stage IV at first diagnosisYes 26 14.2 1 2.6 0.5No 157 85.8 37 97.4
Chemotherapy before diagnosis of BMYes 169 91.8 33 86.8 0.33No 15 8.2 5 13.2
Her2-targeted therapy before BMYes 70 76.1 7 53.8 0.90No 22 23.9 6 46.2
Age at first diagnosis of BM (years)Median 52.5 54.5 0.48Range 26–81 36–83
Time to BM from first diagnosis of breast cancer (months)Median 41.0 30.0 0.02Range 0–200 0–116
Number of BMMean 3 2 0.36Range 1–20 1–8
Karnofsky performance status at first diagnosis of BM470 167 90.8 36 94.7 0.43o70 17 9.2 2 5.3
DS-GPAClass I 43 23.4 6 15.8Class II 81 44.0 18 47.4Class III 51 27.7 12 31.6 0.78Class IV 9 4.9 2 5.3
Metastatic pattern at first diagnosis of BMVisceral metastases 129 58.1 0 0 —
Lung metastases 86 38.7 0 0Liver metastases 79 35.6 0 0
Lymph metastases only 5 2.3 0 0Bone metastases only 7 3.2 0 0
First-line treatment for BMRadiosurgery 19 10.3 3 7.9 0.002Chemotherapy 1 0.5 1 2.6Surgery 71 38.6 27 71.1WBRT 88 47.8 7 18.4Best supportive care 5 2.7 0 0
Chemotherapy after diagnosis of BMYes 77 41.8 8 21.1 0.016No 107 58.2 30 78.9
Systemic progression after treatment for BMYes 84 45.7 0 0 —No 100 54.3 38 100
BM progressionYes 62 33.7 14 36.8 0.71No 122 66.3 24 63.2
Table 1 (Continued )
BM and ECM(n¼ 184)
BO(n¼38)
Characteristic n % n % w2 Test/t-test
OS from diagnosis of BM (months)Median 6 11 0.007Range 0–104 0–69
Survival beyond 3 yearsYes 5 2.7 7 18.4 o0.001No 179 97.3 31 81.6
Abbreviations: BM¼ brain metastases; BO¼ brain-only; DS-GPA¼ diagnosis-specificgraded prognostic assessment; ECM¼ extracranial metastases; OS¼ overall survival;WBRT¼whole brain radiotherapy.
1.0
0.8
0.6
Cum
sur
viva
l
Survival functions
P=0.007
Brain-only metastaticbehaviour
No (n=184)Yes (n=38)No-censoredYes-censored0.4
0.2
0.0
0 20 40Overall survival from diagnosis of BM (months)
60 80 100 120
Figure 1 Overall survival from diagnosis of BM in patients with BOmetastatic behaviour (11 months; 95% confidence interval (CI) 8.47–13.59)compared with patients with present ECM (6 months; 95% CI 3.81–8.19).
Table 2 Multivariate survival analysis in BO-MBC cohort
Hazard ratio CI 95% P-value
Karnofsky performance scoreat first diagnosis of BM
0.07 0.01–0.50 0.01
Number of BM 0.13 0.04–0.50 0.003
ER expression 0.49 0.22–1.1 0.78
Abbreviations: BM¼ brain metastases; BO-MBC¼ brain-only metastatic breastcancer; CI¼ confidence interval; ER¼ oestrogen receptor.
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breast cancer subtype with BO metastatic behaviour. Thedistribution of breast cancer subtypes within our BO-MBC cohortwas equalised, as approximately one third of the patients belongedto the Her2-positive, one third to the triple-negative and one thirdthe luminal subtype, respectively. It is interesting to note that priortrastuzumab-based therapy did not correlate with BO metastaticbehaviour, although trastuzumab is thought to favour thedevelopment of BM owing to its inability to cross the blood-brainbarrier (Bendell et al, 2003; Musolino et al, 2011). Patients withtriple-negative and luminal breast cancer subtypes developed BMsignificantly earlier during their disease course than patients withHer2-positive disease in our study (Berghoff et al, 2012). Furtherstudies are needed to clarify the molecular mechanisms of theselective brain tropism of metastatic spread in some breast cancerpatients. As postulated by the ‘seed and soil’ hypothesis, thedevelopment of this distinct metastatic behaviour maybe explained by the interaction between specific tumour cells(‘the seed’) and the microenvironment of the brain (‘the soil’)(Fidler, 2011).
So far, only a few studies focusing on BM as first site ofrecurrence were conducted (Boogerd et al, 1993, 1997; Niwinskaet al, 2011; Dawood et al, 2012). Dawood et al (2012) documented ahigh incidence of BM as first site of recurrence in a population oftriple-negative breast cancer patients with stage I to III, but incontrast to our study, no further analysis of the clinical courseafter diagnosis of BM was performed. Boogerd et al (1993) showedthat breast cancer patients with single BM in the absence of ECMhave improved OS after intensive local treatment compared withBM patients with ECM at first diagnosis of BM. However, in thisstudy no differentiation of breast cancer subtypes and character-isation of prognostic factors was performed. To our knowledge,our study is the first to investigate the incidence and clinicalcourse of contemporary breast cancer patients with BM as first siteof recurrence with a focus on patients with BO-MBC.
However, our study has some limitations that have to beconsidered in the interpretation of the data. First, only retro-spectively collected data were available for our analysis and weincluded patients diagnosed and treated with MBC over a long
period (1990–2011). Changes in clinical management such as theintroduction of new therapy standards (e.g., trastuzumab,lapatinib for Her2-positive MBC) or diagnostic procedures (e.g.,cranial MRT) during this period may have influence our results.However, the date of diagnosis of both groups, BO-MBC and BMwith ECM, was distributed evenly over the entire study periodmaking a bias arising from differences in clinical managementimprobable. In any case, analysis of data from prospective clinicaltrials might be useful to validate our findings.
In our series, 60/222 (27%) patients had BM as first site ofrecurrence and more than one third of these patients, i.e., 22/60(37%) developed ECM after diagnosis of BM. Overall, 38/222 (17%)patients experienced BO metastatic disease in the absence of ECMduring their course of disease. Our data show that patients with BOmetastatic behaviour represent a distinct clinical entity with abetter survival prognosis from diagnosis of BM compared with BMpatients with additional ECM. We could not identify any factorspredicting for BO metastatic behaviour, but identified highKarnofsky index, the presence of only one BM and positive ERstatus as favourable prognostic factors in BO-MBC patients. Aslong-term survival is not uncommon and was achieved in a fifth ofBO-MBC patients, exploitation of all multimodal treatment optionsis warranted in patients with BM as first site of recurrence. Futurestudies are needed to clarify the role of systemic therapies withnovel targeted agents in relation to established local therapyapproaches like neurosurgery, radiosurgery and radiotherapy.
ACKNOWLEDGEMENTS
We thank Irene Leisser for technical assistance with preparation oftissue specimens. This study was performed within the PhD thesisproject of Anna Sophie Berghoff in the PhD program ‘ClinicalNeuroscience (CLINS)’ at the Medical University Vienna.
Conflict of interest
The authors declare no conflict of interest.
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This work is published under the standard license to publish agreement. After 12 months the work will become freely available and thelicense terms will switch to a Creative Commons Attribution-NonCommercial-Share Alike 3.0 Unported License.
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! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !
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6.3 Prognostic significance of Ki67 proliferation index, HIF1 alpha index and microvascular density in patients with non-small cell lung cancer brain metastases.
Interlude Survival estimation in patients with NSCLC BM is based on clinical prognostic factors
including number of BM, Karnofsky performance score, age and status of
extracranial disease [68]. So far no tissue based characteristics are involved in the
prognostic evaluation of NSCLC BM patients. Re-evaluation of tissue based
characteristic in metastatic sites might add valuable additional information, as little is
known so far on the accordance of primary tumour and matched BM [14, 127].
Therefore, we concentrated on the identification of tissue based prognostic factors in
patients with NSCLC BM in the paper “Prognostic significance of Ki67 proliferation
index, HIF1 alpha index and microvascular density in patients with non-small cell
lung cancer brain metastases”. We identified low median Ki67 proliferation index as
well as high median microvascular density as favourable tissue based prognostic
factors indicating that inclusion of tissue based characteristic might add additional
value to already existing clinical prognostic assessments. We also observed, that
patients receiving whole brain radiation therapy survived shorter when the BM
tumour tissue revealed a high HIF 1 alpha expression [128].
Original article
1Strahlentherapie und Onkologie X · 2014 |
The development of brain metastases (BM) is a devastating complication in cancer patients, for which there are on-ly limited treatment options. Unfortu-nately, the incidence of BM has increased over the last decade. Non-small cell lung cancer (NSCLC) is the primary tumor most frequently responsible for BM and approximately 40 % of patients suffering from metastatic NSCLC eventually devel-op BM [1].
The prognosis upon diagnosis of BM is poor, with a median overall surviv-al (OS) of only a few months [2]. Several prognostic scores have been established in order to provide survival estimations for patients with newly diagnosed BM. These prognostic scores rely mainly on estab-lished clinical prognostic factors such as age, Karnofsky Performance Status, sta-tus of extracranial disease and number of BM [2–5]. The diagnosis-specific graded prognostic assessment score (DS-GPA) is an established prognostic score for surviv-al estimation in patients with newly diag-
nosed NSCLC BM [2]. Herein, the calcu-lated median OS from diagnosis of BM ranges from 3 months in the least favor-able group, to 14.8 months in the most fa-vorable group [2]. Tissue-based prognos-tic factors are not currently included in any of the established prognostic scores for BM patients.
Neoangiogenesis, hypoxia and pro-liferation are hallmarks of cancer. These factors have been shown to influence pa-tients’ prognosis and response to therapy in many tumor types, including primary and metastatic NSCLC [6–10]. However, the prognostic value of these parameters in NSCLC BM has not been systematical-ly studied.
In the present study we investigated the association of Ki67 tumor cell prolif-eration index, the expression of hypox-ia-inducible factor 1 alpha (HIF-1 alpha) and the expression of CD34 (as an endo-thelial marker) with outcome parameters in order to explore their prognostic value. The study cohort comprised a large and
well-defined series of NSCLC patients treated with first-line neurosurgical re-section upon diagnosis of BM.
Methods
Patients
All patients diagnosed with NSCLC BM having undergone first-line neurosurgical resection between January 1990 and Feb-ruary 2011 were identified from the Neu-ro-Biobank, Medical University of Vien-na. Histological confirmation of BM orig-inating from NSCLC was mandatory for inclusion. Clinical data, including clin-ical prognostic factors, were identified by chart review. DS-GPA was calculated based on clinical factors [2, 3]. Survival data was obtained from the National Can-cer Registry of Austria database and the Austrian Brain Tumor Registry [11]. The ethics committee of the Medical Univer-sity of Vienna approved the study (vote 078/2004).
A. S. Berghoff1,2,3 · A. Ilhan-Mutlu2,3 · A. Wöhrer1,2 · M. Hackl4 · G. Widhalm2,5 · J. A. Hainfellner1,2 · K. Dieckmann2,6 · T. Melchardt7 · B. Dome8 · H. Heinzl2,9 · P. Birner2,10 · M. Preusser2,3
1Institute of Neurology, Medical University of Vienna, Vienna, Austria
2Comprehensive Cancer Center CNS Tumors Unit, Medical University of Vienna, Vienna, Austria
3Department of Medicine I, Medical University of Vienna, Vienna, Austria
4Austrian National Cancer Registry, Statistics Austria, Vienna, Austria
5Department of Neurosurgery, Medical University of Vienna, Vienna, Austria
6Department of Radiotherapy, Medical University of Vienna, Vienna, Austria
7Third Medical Department, Paracelsus Medical University Hospital Salzburg, Salzburg, Austria
8Department of Surgery, Medical University of Vienna, Vienna, Austria
9 Center for Medical Statistics, Informatics, and Intelligent Systems Medical University of Vienna,
Vienna, Austria10 Institute of Clinical Pathology, Medical University of Vienna, Vienna, Austria
Prognostic significance of Ki67 proliferation index, HIF1 alpha index and microvascular density in patients with non-small cell lung cancer brain metastases
Strahlenther Onkol 2014DOI 10.1007/s00066-014-0639-8Received: 29 August 2013Accepted: 25 November 2013
© Springer-Verlag Berlin Heidelberg 2014
2 | Strahlentherapie und Onkologie X · 2014
Original article
Tissue-based analysis
Formalin-fixed and paraffin-embedded tissue blocks were assembled according to standard laboratory practice. Tissue blocks were cut into 3-µm slices with a microtome. Immunohistochemistry was performed using an automated horizon-tal slide processing system (Autostainer Plus Link; Ki67; Dako Denmark, Glos-trup, Denmark) and a fully automated multimodal slide staining system (Bench-Mark ULTRA; HIF-1 alpha, CD34; Ven-tana Medical Systems, Tucson, AZ, USA) according to standard protocol [12–14]. In brief, slides underwent heat-induced epitope retrieval in pH6.0 citrate buffer (HIF-1 alpha: 92 min; Ki67: 20 min) or in pH8.0 buffer (CD34: 36 min). After-wards, sections were incubated with anti-body: HIF-1 alpha: polyclonal rabbit pu-rified anti-human HIF-1 alpha/610959 BD Transduction Laboratories™ (BD Bio-sciences, East Rutherford, NJ, USA) 1:10; Ki67: monoclonal mouse Ki67 clone MIB-1/M7240 (Dako), 1:200; CD34: No-vocastra™ lyophilized mouse monoclonal antibody endothelial cell marker (CD34) (Novocastra™, Leica Biosystems, Wetzlar, Germany) 1:50.
For the Ki67 proliferation index, 500 cells were counted within the area of strongest staining to give the percentage of positive cells (0–100 %) [12]. HIF-1 al-pha score was calculated according to the modified H-score [15–17]. HIF-1 alpha intensity groups were defined as follows: 0 = no appreciable staining in the tumor cell nucleus; 1 = barely detectable stain-ing intensity in the nucleus; 2 = moderate staining intensity distinctly in the tumor cell nucleus; 3 = strong staining intensity of the tumor cell nucleus. For each inten-sity group the fraction of cells (0–100 %) was recorded. The HIF-1 alpha index was calculated by multiplying the intensity by the fraction of cells producing this inten-sity, producing a total range of 0–300. The mean microvascular density (MVD) was defined by the number of CD34-positive vessels within the area of the highest den-sity at a 200x magnification (“hot spot”) [18]. Furthermore, the vascular pattern was analyzed in the CD34 staining to dif-ferentiate between the “angiogenic type” defined by the predominance of sprouting
vessels (characterized by multilayer endo-thelium) and the “silent type” defined by predominance of vessels with thin mono-layer endothelium. Specimens with an equal distribution of angiogenic and si-lent types were defined as the “balanced type” [17].
Statistical analysis
The Spearman!s rank correlation coeffi-cient was used to assess monotone associ-ations between two continuous variables. For assessing group differences, χ-square, paired and unpaired t-, Mann–Whitney U and Kruskal–Wallis tests were used as appropriate. A significance level of 0.05 was applied. OS of patients was estimat-ed with the Kaplan–Meier product lim-it method and group differences were as-sessed with the log-rank test. The median was used as the cutoff value for continu-ous variables entered in univariate anal-ysis.
Variables with significant results in univariate analysis were entered in-to a multivariate Cox proportional haz-ards model. Overall and partial measures of dependence (R squared, R2 values) were computed according to Kent and O’Quigley [19, 20]. Due to the exploratory and hypothesis-generating design of the present study, no adjustment for multiple testing was applied [21].
For calculation of the tissue GPA (tG-PA) prognostic score a multivariate Cox regression model was used. For graphi-cal representation, the patient cohort was divided into three equal sized classes ac-cording to the terciles of the tGPA.
All statistical analyses were performed with the Statistical Package for the So-cial Sciences version 20.0 software (IBM, SPSS, Armonk, NY, USA) and SAS 9.3 (SAS Institute Inc., Cary, NC, USA).
Results
Patient characteristics
A total of 230 patients (151 male, 79 fe-male) with a median age of 56 years (range 33–78 years) at first diagnosis of NSCLC BM were included. All patients underwent neurosurgical resection as first line therapy for newly diagnosed
BM. Histology was as follows: 165/230 (71.7 %) patients had adenocarcinoma, 29/230 (12.6 %) squamous cell carcino-ma, 15/230 (6.5 %) adenosquamous carci-noma, 17/230 (7.4 %) large cell carcinoma and 4/230 (1.7 %) patients had unknown histology. A history of cigarette smoking was reported by 169/230 (73.5 %) patients. Further patient characteristics are listed in . Table 1.
Tissue-based findings in brain metastasis specimens
Median Ki67 proliferation index was 39.8 % (range 5–97 %), median HIF-1 alpha index was 60 (range 0–270) and median MVD was 71/0.7 mm2 (range 7–298/0.7 mm2). Of all specimens, 102/230 (44.3 %) showed a predominance of microvascular sprouting (angiogenic type); 62/230 (27.0 %) specimens showed a silent angiogenesis with predominance of mature vessels and without signs of an-giogenesis (silent type); 61/230 (26.5 %) specimens showed an equal distribution of microvascular sprouting and silent angiogenesis (balanced type) and 5/230 (2.2 %) specimens were not definable due to too few classifiable vessels.
In BM specimens, MVD showed a sig-nificant association with vascular pattern: MVD values increased when going from specimens with silent, to balanced, to an-giogenic vascular patterns (Kruskal–Wal-lis test, p< 0.001; . Fig. 1a).
Ki67 proliferation index was signifi-cantly higher in BM specimens with squa-mous histology as compared to cases with nonsquamous histology (Mann–Whitney U test, p = 0.002; . Fig. 1b).
Among BM specimens, no correlation was observed between Ki67 proliferation index and MVD (Spearman’s correlation coefficient − 0.039, p = 0.556) or vascular pattern (Kruskal–Wallis test, p = 0.587). Furthermore, no correlation between HIF-1 alpha index and MVD (Spearman’s correlation coefficient − 0.049, p = 0.459) or vascular pattern (Kruskal–Wallis test, p = 0.572) was present. No correlation between histology and MVD (Kruskal–Wallis test, p = 0.311), HIF-1 alpha index (Kruskal–Wallis test, p = 0.321) or vascu-lar pattern (χ-square test, p = 0.799) was evident. Weak correlation was observed
3Strahlentherapie und Onkologie X · 2014 |
Abstract · Zusammenfassung
between Ki67 proliferation index and HIF-1 alpha index (Spearman’s correla-tion coefficient 0.298, p < 0.001).
Comparative analyses of brain metastases and corresponding primary tumors
Tumor tissue from the corresponding primary tumor was available in 53/230 (23.0 %) cases. Median Ki67 prolifera-tion index of the primary tumor was 39 %
(range 4–79 %) and did not significantly differ from the BM Ki67 proliferation in-dex (paired t-test, p = 0.897). Median pri-mary tumor MVD was 65/0.7 mm2 (range 26–179/0.7 mm2), which was significant-ly lower than in BM (71/0.7 mm2; paired t-test, p = 0.032). Median primary tumor HIF-1 alpha index was 30 (0–210), which was significantly lower than in BM (60; paired t-test, p = 0.013).
Survival analyses
Impact of parameters on time to diagnosis of brain metastasesTime to diagnosis of BM was only evalu-ated in patients with subsequent diagno-sis of BM and no synchronous diagnosis of primary tumor and BM (n = 103). No impact of Ki67 proliferation index, HIF-1 alpha index, MVD or vascular pattern of the primary tumor on time to develop-ment of BM (TTBM) was observed. Pa-
Strahlenther Onkol 2014 DOI 10.1007/s00066-014-0639-8© Springer-Verlag Berlin Heidelberg 2014
A. S. Berghoff · A. Ilhan-Mutlu · A. Wöhrer · M. Hackl · G. Widhalm · J. A. Hainfellner · K. Dieckmann · T. Melchardt · B. Dome · H. Heinzl · P. Birner · M. Preusser
Prognostic significance of Ki67 proliferation index, HIF1 alpha index and microvascular density in patients with non-small cell lung cancer brain metastases
AbstractBackground. Survival upon diagnosis of brain metastases (BM) in patients with non-small cell lung cancer (NSCLC) is highly vari-able and established prognostic scores do not include tissue-based parameters.Methods. Patients who underwent neu-rosurgical resection as first-line therapy for newly diagnosed NSCLC BM were included. Microvascular density (MVD), Ki67 tumor cell proliferation index and hypoxia-inducible fac-tor 1 alpha (HIF-1 alpha) index were deter-mined by immunohistochemistry.Results. NSCLC BM specimens from 230 pa-tients (151 male, 79 female; median age 56 years; 199 nonsquamous histology) and
53/230 (23.0 %) matched primary tumor sam-ples were available. Adjuvant whole-brain ra-diation therapy (WBRT) was given to 153/230 (66.5 %) patients after neurosurgical resec-tion. MVD and HIF-1 alpha indices were sig-nificantly higher in BM than in matched pri-mary tumors. In patients treated with adju-vant WBRT, low BM HIF-1 alpha expression was associated with favorable overall sur-vival (OS), while among patients not treated with adjuvant WBRT, BM HIF-1 alpha expres-sion did not correlate with OS. Low diagnosis-specific graded prognostic assessment score (DS-GPA), low Ki67 index, high MVD, low HIF-1 alpha index and administration of adjuvant
WBRT were independently associated with favorable OS. Incorporation of tissue-based parameters into the commonly used DS-GPA allowed refined discrimination of prognos-tic subgroups.Conclusion. Ki67 index, MVD and HIF-1 al-pha index have promising prognostic val-ue in BM and should be validated in further studies.
KeywordsSurvival · Whole-brain radiation therapy · Proliferation · Angiogenesis · Hypoxia
Prognostische Signifikanz von Proliferationsindex Ki67, HIF-1α-Index und mikrovaskulärer Gefäßdichte bei Patienten mit zerebralen Metastasen eines nicht-kleinzelligen Lungenkarzinoms
ZusammenfassungHintergrund. Die Überlebensprognose von Patienten mit zerebralen Metastasen eines nicht-kleinzelligen Lungenkarzinoms (NSCLC) ist sehr variabel. Bisher werden gewebsba-sierte Parameter nicht in die prognostische Beurteilung inkludiert.Methoden. Neurochirurgische Resektate ze-rebraler NSCLC-Metastasen wurden in die-ser Studie untersucht. Die Gefäßdichte („mi-crovascular density“, MVD), der Ki67-Proli-ferationsindex sowie der HIF-1α-Index wur-den mittels immunhistochemischer Metho-den analysiert.Ergebnisse. Insgesamt wurden Proben von 230 Patienten (151 Männer, 79 Frauen; mitt-leres Alter 56 Jahre; 199 Adenokarzinome) und korrespondierenden Primärtumoren
(53/230; 23,0 %) eingeschlossen. Mit einer Ganzhirnbestrahlung nach neurochirurgi-scher Resektion wurden 153/230 Patienten (66,5 %) behandelt. Eine höhere Gefäßdich-te sowie ein niedrigerer HIF-1α-Index wur-den in den korrespondierenden Primärtumo-ren im Vergleich zu den zerebralen Metasta-sen beobachtet. Ein niedriger HIF-1α-Index zeigte eine signifikante Korrelation mit dem Gesamtüberleben in Patienten mit postope-rativer Ganghirnbestrahlung. In der Gruppe der Patienten ohne postoperative Ganzhirn-bestrahlung hingegen konnte kein prognos-tischer Einfluss des HIF-1α-Index beobachtet werden. Ein niedriger diagnosespezifischer Prognosescore (DS-GPA), ein niedriger Ki67-Proliferationsindex, eine hohe Gefäßdichte,
ein niedriger HIF-1α-Index sowie die Durch-führung einer postoperativen Ganzhirnbe-strahlung zeigten eine unabhängige und si-gnifikante Korrelation mit dem Gesamtüber-leben. Der Einschluss von gewebebasierten Parametern in der üblich verwendeten DS-GPA ermöglicht die Unterscheidung prognos-tischer Subgruppen.Schlussfolgerung. Die Analyse des Ki67-Proliferationsindex, der Gefäßdichte sowie des HIF-1α-Index sollte in die prognostische Beurteilung von Patienten mit zerebralen NSCLC-Metastasen inkludiert werden.
SchlüsselwörterÜberleben · Ganzhirnbestrahlung · Proliferation · Angiogenese · Hypoxie
4 | Strahlentherapie und Onkologie X · 2014
Original article
tients with large cell carcinoma histolo-gy (median TTBM: 4 months) developed BM earlier than patients with adenocarci-noma (median TTBM: 12 months), squa-mous cell (median TTBM: 11 months) or adenosquamous cell carcinoma histology (median TTBM: 9 months; log-rank test, p = 0.052; . Fig. 2). Furthermore, patients with large cell carcinoma (11/17, 64.7 %) or adenocarcinoma (99/165, 60.0 %) had more synchronous diagnosis of NSCLC and BM than patients with adenosqua-mous (7/15, 46.7 %) or squamous cell carcinoma (8/29, 27.6 %; χ-square test, p = 0.009).
Impact of clinical characteristics on overall survival from diagnosis of brain metastasisDS-GPA showed a statistically significant correlation with OS measured from first diagnosis of BM. Patients with DS-GPS class 1 had a median OS of 17 months, compared to 7 months in class 2, 5 months in class 3 and only 1 month in pa-tients with class 4 (log-rank test, p < 0.001; . Fig. 3a). However, no significant differ-ence in OS was observed between DS-GPA class 2 and DS-GPA class 3 (7 vs. 5 months; log-rank test, p = 0.205).
Histology significantly influenced survival prognosis. Patients with adeno-carcinoma had a median OS of 9 months from diagnosis of BM, compared to 8 months in patients with large cell histolo-gy, 6 months in patients with adenosqua-mous histology and 4 months in patients with squamous histology (log-rank test, p = 0.008; . Fig. 3b).
Patients scheduled for adjuvant WBRT after neurosurgical resection of BM had a significantly longer median OS than pa-tients without adjuvant WBRT after neu-rosurgical resection of BM (9 vs. 5 months; log rank test, p < 0.001). Patients with a single BM received WBRT significantly less frequently after neurosurgical resec-tion (100/164, 61.0 %) than did patients with 2–3 BM (38/47, 80.9 %) or > 3 BM (15/18, 83.3 %; χ-square test, p = 0.012). Furthermore, patients receiving chemo-therapy after diagnosis of BM survived significantly longer than patients not re-ceiving chemotherapy (15 vs. 6 months; log-rank test, p.0.005). Patients receiving combination therapy comprising WBRT
Table 1 Patient characteristicsCharacteristic Entire population (n = 230)
No. patients PercentageMedian age at first diagnosis of lung cancer, years (range) 56 (33–78)Histology of primary tumor– Adenocarcinoma 165 71.7– Squamous cell carcinoma 29 12.6– Adenosquamous carcinoma 15 6.5– Large cell carcinoma 17 7.4– Unknown 4 1.7Stage IV primary tumor– Yes 145 63.0– No 85 37.0Surgery for primary tumor before diagnosis of BM– Yes 76 33.2– No 153 66.8Number of extracranial metastatic sites– 0 180 78.3– 1 32 13.9– ≥ 2 18 7.8Visceral metastases before first diagnosis of BM– Yes 28 12.2– No 202 87.8Number of chemotherapy lines before first diagnosis of BM– 0 181 78.7– 1 40 17.4– ≥ 2 9 3.9Time from first diagnosis of primary tumor to first diagnosis of BM, months (range)
11 (1–162)
Median age at first diagnosis of BM, years (range) 57 (34–78)GPA class at first diagnosis of BM– I 64 27.8– II 114 49.6– III 47 20.4– IV 5 2.2Status of primary tumor at first diagnosis of BM– No evidence of disease 55 23.9– Partial response 6 2.6– Stable disease 32 13.9– Progressive disease 10 4.3– Synchronous first diagnosis of primary tumor and BM 127 55.2WBRT after surgery– Yes 153 66.5– No 76 33.0– Unknown 1 0.4Chemotherapy after diagnosis of BM– Yes 79 34.3– No 146 63.5– Unknown 5 2.2Event– Yes 203 88.3– No 27 11.7Median overall survival from first diagnosis of lung cancer, months (range)
14.5 (0–168)
Median overall survival from first diagnosis of BM, months (range)
8.0 (0–141)
BM brain metastasis, GPA graded prognostic assessment score, WBRT whole-brain radiation therapy
5Strahlentherapie und Onkologie X · 2014 |
and chemotherapy after surgery had im-proved survival (15 months) compared to patients receiving WBRT (8 months) or chemotherapy alone (14 months; log-rank test, p < 0.001; . Fig. 3c).
A synchronous diagnosis of BM and primary NSCLC had been made for 127/230 (55.2 %) patients. In this co-hort, patients treated with surgical treat-ment of both primary tumor and BM had
a more favorable OS compared to pa-tients in whom only the BM was resected (15 vs. 7 months; log-rank test, p = 0.004; . Fig. 3d).
Impact of tissue-based characteristics on overall survival from diagnosis of brain metastasisPatients with a low Ki67 proliferation in-dex in the BM tissue had an improved
survival compared to patients with high Ki67 proliferation index (10 vs. 6 months; log-rank test, p = 0.011; . Fig. 4a). Patients with a low HIF-1 alpha index in the BM tissue had more favorable OS than pa-tients with a high HIF-1 alpha index (11 vs. 7 months; log-rank test, p = 0.013; . Fig. 4b). Patients with high MVD in the BM tissue survived significantly lon-ger than patients with low MVD (10 vs. 6 months; log-rank test, p = 0.049; . Fig. 4c). The vascular pattern did not show a significant impact on prognosis (log-rank test, p = 0.850).
In the cohort of patients treated with WBRT after neurosurgery, patients with a low HIF-1 alpha index had a more fa-vorable median OS than patients with a high HIF-1 alpha index (15 vs. 7 months; p = 0.004; . Fig. 5a). However, HIF-1 al-pha expression had no impact on OS in the cohort of patients without WBRT (log-rank test, p = 0.904; . Fig. 5b). A trend was observed in multivariate inter-action analysis of WBRT and HIF-1 alpha index (Cox regression model, p = 0.074).
Multivariable analysis of overall survivalAccording to the results of univariate analysis, we entered the following pa-rameters into multivariate survival anal-yses using the Cox regression model: DS-GPA, primary tumor histology, chemo-
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Fig.1 8 a MVD was significantly associated with angiogenic pattern. b We found significantly higher Ki67 indices in brain me-tastases (BM) with squamous cell histology as compared to BM with nonsquamous cell histology. Asterisks denote statistical-ly significant differences (p < 0.05)
Histology of primary tumor
Adenocarcinoma (n=66)Squamous cell carcinoma (n=21)Adenosquamous cellcarcinoma (N=8)Large cell carcinoma(n=6)
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Fig. 2 9 Time to devel-opment of brain me-tastases with regard to tumor histology. BM brain metastases
6 | Strahlentherapie und Onkologie X · 2014
Original article
therapy (yes/no), adjuvant WBRT (yes/no), HIF-1 alpha index, Ki67 prolifera-tion index and MVD. DS-GPA, WBRT, HIF-1 alpha index, Ki67 proliferation in-dex and MVD remained independent prognostic parameters for survival from diagnosis of BM in multivariable analy-sis (. Table 2). Furthermore, the tissue-based characteristics were shown to add statistically significant information to the model (Cox regression model,three degrees of freedom, p < 0.001). Over-all, the R2 measure showed that the sev-en prognostic factors explained 34.04 % of the variability in OS time. Moreover, the partial R2 measure showed that the tissue-based prognostic characteristics in addition of the clinical prognostic char-acteristics explained 10.62 % variability
in OS time. After accounting for the ef-fects of the clinical prognostic factors and the other respective tissue-based charac-teristics, the partial R2 values for MVD, HIF-1 alpha index and ki67 proliferation index were 2.72, 2.18 and 4.38 %, respec-tively (. Table 2).
Calculation of a prognostic score including tissue-based characteristicsTo illustrate the potential of improved prognostication by incorporation of tis-sue-based prognostic parameters into the DS-GPA, we calculated a tGPA. Using the terciles as cutoffs, the entire cohort was divided into three tGPA classes (class 1: 76 patients; class 2: 77 patients; class 3: 77 patients). A statistically significant asso-
ciation was observed between tGPA and median OS (class 1: 15 months, class 2: 9 months, class 3: 4 months; log-rank test, p < 0.001; . Fig. 5c). As no significant dis-crimination was observed between DS-GPA class 2 and DS-GPA class 3, we ap-plied the tGPA to this group of patients (n = 161). Herein, tGPA showed a stati-cally significant discrimination. Patients with tGPA class 1 had median OS of 11 months; for patients with class 2 this was 8 months and patients with tGPA class 3 had a median OS of 5 months (log-rank test, p < 0.001; . Fig. 5d).
Discussion
In this project we investigated for the first time the prognostic value of Ki67 pro-
1.0 DS-GPA Histology
Treatment after BM surgery Patients with synchronousdiagnosis of NSCLC and BM
(n=125)None (n=62)
BM surgery only (n=103)Surgery of primary tumorand BM(n=22)
p=0.004
WBRT only (n=88)Chemotherapy only (n=13)
WBRT + Chemotherapy(n= 65)
p<0.001
Adenocarcinoma(n= 165)Squamous cellcarcinoma (n= 29)Adenosquamous cellcarcinoma (n= 15)Large cell carcinoma(n=17)
p=0.008
Class 1 (n=64)Class 2 (n=114)Class 3 (n=47)Class 4 (n=5)
p<0.0010.8
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Fig. 3 9 a Overall surviv-al (OS) from diagnosis of brain metastases (BM) ac-cording to diagnosis-spe-cific graded prognostic as-sessment (DS-GPA) class. b OS from diagnosis of BM according to primary tu-mor histology. c OS from diagnosis of BM accord-ing to adjuvant treatment after surgery for BM. d OS from diagnosis of BM in pa-tients with synchronous di-agnosis of BM and primary non-small cell lung cancer (NSCLC) according to surgi-cal strategy. WBRT whole-brain radiation therapy
7Strahlentherapie und Onkologie X · 2014 |
1.0 Ki67 proliferationindex
HIF 1 alpha index Microvascular density
p=0.049
<71/0.7 mm2 (n=117)>71/0.7 mm2 (n=113)
<60 (n=116)>61 (n=114)
p=0.011 p=0.013
<39.8% (n=113)>39.8% (n=117)
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Fig. 4 8 a Overall survival (OS) from diagnosis of brain metastases (BM) according to Ki67 proliferation index. b OS from diag-nosis of BM according to HIF-1 alpha index. c OS from diagnosis of BM according to microvascular density (MVD)
1.0 Patients receiving WBRT aftersurgery
tGPAclass 1 (n=76)class 2 (n=78)class 3 (n=76)
p<0.001
tGPA in DS-GPA class 2& 3 population (n=161)
class 1 (n=34)class 2 (n=58)class 3 (n=69)
p<0.001
HIF <60 (n=74)HIF >60 (n=79)
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Fig. 5 9 a Overall surviv-al (OS) from diagnosis of brain metastases (BM) in patients receiving adjuvant whole-brain radiation ther-apy (WBRT) after surgery of BM related to HIF-1 alpha index. b OS from diagno-sis of BM in patients not re-ceiving adjuvant WBRT af-ter surgery of BM related to HIF-1 alpha index. c OS from diagnosis of BM relat-ed to tissue graded prog-nostic assessment (tGPA) class, d OS from diagnosis of BM in patients with GPA class 2 related to tGPA
8 | Strahlentherapie und Onkologie X · 2014
Original article
liferation index, HIF-I alpha index and MVD in a large and well-defined cohort of NSCLC BM. Our findings clearly show that these parameters are biologically and clinically relevant and may help to guide the management of patients with NSCLC BM.
In our large cohort of patients with NSCLC BM, we observed an indepen-dent, significant prognostic impact of Ki67 proliferation index, HIF-1 alpha in-dex and MVD on OS from diagnosis of BM. Our results are well in line with pre-vious findings in primary NSCLC, which postulated that high Ki67 proliferation and high HIF-1 alpha indices be unfavor-able prognosis parameters [22, 23]. How-ever, our study is, to our best knowledge, the first to investigate these tissue-based prognostic factors in BM tissue. The as-sociation of high MVD and favorable OS prognosis in our cohort might be per-ceived as somewhat surprising, as a high MVD was shown to be associated with an impaired survival prognosis in pri-mary NSCLC [24, 25]. However, a pre-vious study of MVD in NSCLC lymph node metastases postulated a switch of the prognostic value of MVD in the metastat-ic setting, as a high MVD in the lymph node metastases correlated with an im-proved OS prognosis [26]. Taken togeth-er, these results suggest a differential in-fluence of MVD on prognosis in prima-ry NSCLC tumors and NSCLC metastatic lesions. The surrounding microenviron-ment might influence the pathobiolog-ical behavior and the angiogenic poten-tial of a given tumor, as postulated in the
“seed and soil” theory [27]. While some primary NSCLCs were shown to grow in an alveolar pattern with only low neoan-giogensis, preclinical data demonstrated a highly angiogenic behavior of NSCLC BM cells after extravasation into the peri-vascular niche [28, 29]. Previously, che-motherapy drug delivery through the in-creased capillary surface was postulated to account for the improved survival of patients with highly angiogenic tumors [26]. However, we observed an indepen-dent impact of high MVD in the multivar-iate analysis, irrespective of chemothera-py administration. Nevertheless, the rea-sons for the unexpectedly observed bene-ficial effect of increased BM angiogenesis on OS are not clear.
Our findings underscore the heteroge-neity of tumor behavior among NSCLC subtypes and the relevance of these differ-ences for the biology and clinical course of BM. Firstly, we found a higher prolifera-tion rate in squamous, compared to non-squamous BM tumors—a finding that mirrors the situation in primary NSCLC [30]. In line with these results, we found that patients with squamous cell BM had a poor outcome, with median OS reaching only 4 months and thereby significantly shorter than that observed for other tu-mor types (6–9 months).
Interestingly, we found a profound effect of tumor histology on the time to BM development from first diagnosis of NSCLC. Patients with large cell carcino-mas developed BM within a median 4 months from diagnosis of the primary tu-mor, while in other tumor types BM be-
came evident only after median follow-up times of more than 11 months. To the best of our knowledge, this result has not been described previously and warrants further investigation. It is of note that a relative-ly high incidence of BM has been docu-mented in adenocarcinoma and large cell carcinoma previously [31]. Additionally, a higher incidence of synchronous diag-nosis of primary tumor and BM was ev-ident for large cell and adenocarcinoma in our series, thus further highlighting the higher propensity of BM in these histo-logical entities.
Concerning cases with synchronous diagnosis of BM and primary NSCLC tu-mor, we observed a strong effect of surgi-cal strategy on patient outcome. Patients treated with resection of both the CNS and the primary tumors fared significant-ly better than patients treated with neu-rosurgery only. Our study is limited by its retrospective nature; in particular, the prescription bias with respect to the ad-ministered therapies may be a potential is-sue of concern resulting from poorly stan-dardized therapy approaches in patients with BM. Furthermore, statistical power may be an additional issue and prospec-tive, randomized trials are urgently war-ranted to reappraise our findings. Howev-er, compared to previous studies, we were able to include and investigate an appre-ciable sample size. Some small phase II prospective trials already exist and un-derscore our findings: these have shown that a subgroup of patients with synchro-nous diagnosis of NSCLC and oligomet-astatic disease benefits from multimodal-ity treatment including BM and lung re-section [32–34].
We observed significant longer surviv-al in patients receiving a multimodal ther-apy approach including surgery, chemo-therapy and WBRT as compared to pa-tients receiving only adjuvant WBRT after surgery. Although a selection bias cannot be ruled out, our findings once more un-derscore the shaky and ambiguous val-ue of adjuvant WBRT after neurosurgi-cal resection of NSCLC BM [35, 36]. A prospective phase III trial failed to dem-onstrate an impact of adjuvant WBRT on OS in patients with one to three BM treat-ed with neurosurgical resection or radio-surgery [37]. However, time to intracra-
Table 2 Results of multivariate survival analysesParameter Exp(B) 95 % CI P-value Partial R2
DS-GPA 1.693 1.374–2.087 < 0.001 12.33 %Histology (categorical) 1.40 %– Adenocarcinoma 0.657 0.7379–1.139 0.134– Squamous cell carcinoma 0.836 0.433–1.615 0.594– Adenosquamous cell carcinoma 0.665 0.307–1.442 0.302– Large cell carcinoma 1.378 0.799–2.377Chemotherapy (yes/no) 0.753 0.545–1.041 0.086 4.91 %Adjuvant WBRT (yes/no) 0.591 0.428–0.816 0.001 3.26 %HIF-1 alpha index (continuous) 1.003 1.000–1.005 0.050 2.18 %Ki67 proliferation index (continuous) 1.013 1.005–1.021 0.002 4.38 %MVD (continuous) 0.996 0.993–1.000 0.031 2.72 %DS-GPA diagnosis-specific graded prognostic assessment, WBRT whole-brain radiation therapy, MVD micro-vascular density
9Strahlentherapie und Onkologie X · 2014 |
nial disease progression was significant-ly prolonged in patients receiving WBRT. Considering the relative radioresistance of NSCLC and the long-term side effects of WBRT (e.g. neurocognitive decline), a predictive marker for patients profiting from adjuvant WBRT would be of clin-ical relevance [38–40]. Our data suggest that the HIF-1 alpha index, which is fre-quently used a as surrogate marker for hy-poxia, might serve as a predictive mark-er for WBRT. This is in good agreement with the results of previous studies indi-cating the value of HIF-1 alpha expression as a predictor for the response to radio-therapy in various primary tumors [41]. Our results clearly suggest the need for prospective studies to further investigate whether stratification of BM patients for adjuvant WBRT based on HIF-1 alpha ex-pression is a feasible strategy.
Conclusion
In order to make appropriate personal-ized and prognostic-based treatment de-cisions, prognostic scoring systems have to be as precise as possible and include all relevant prognostic aspects. To date, established prognostic scores only in-clude clinical prognostic factors and do not include radiological or pathological findings [2–4, 42]. In the present study, we could demonstrate the impact of pro-liferation, MVD and hypoxia on surviv-al in our cohort of patients with NSCLC BM. We illustrate by example that the ad-dition of tissue-based parameters to tra-ditional prognostic scores based on clin-ical parameters alone may improve dis-crimination between prognostic sub-groups. Therefore, the inclusion of tissue-based prognostic factors should be con-sidered, but needs to be validated in in-dependent patient cohorts and prospec-tive studies.
Corresponding address
P. Birner MDInstitute of Clinical Pathology Medical University of Vienna Waehringer Guertel 18–20, 1090 [email protected]
Acknowledgements. We thank Carina Dinhof, Gerda Riecken, Irene Leisser, Ursula Rajky and Bettina Jesch for excellence technical assistance. The costs for this project were covered by the research budget of the Medical University of Vienna. This study was per-formed within the PhD thesis project of Anna Sophie Berghoff in the PhD program “Clinical Neuroscience (CLINS)” at the Medical University Vienna.
Compliance with ethical guidelines
Conflict of interest. A. S. Berghoff, A. Ilhan-Mutlu, A. Wöhrer, M. Hackl, G. Widhalm, J. A. Hainfellner, K. Dieckmann, T. Melchardt, B. Dome, H. Heinzl, P. Birner and M. Preusser state that there are no conflicts of interest.
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! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !
! %+!
6.4 Preoperative diffusion-weighted imaging of single brain metastases correlates with patient survival times.
Interlude As previously mentioned survival estimation in patients with newly diagnosed BM is
based on clinical characteristics [68]. Radiological parameters have not yet been
included in the prognostic assessment, but might add valuable information as they
correlate with histological characteristics, providing an indirect insight in a tumour’s
microarchitecture. Diffusion weighted imaging visualizes the mobility of water
molecules in the extracellular space. A hyperintense diffusion weighted imaging
represents a low diffusion capacity i.e. a restricted mobility of water molecules in the
extracellular space [129]. On the cellular basis, hyperintense diffusion weighted
imaging was shown to correlate with high cellularity, poor differentiation and dense
stromal matrix [129-131]. In the study “Preoperative diffusion-weighted imaging of
single brain metastases correlates with patient survival times” we aimed to
investigate the prognostic impact and tissue based correlation of diffusion weighted
imaging in a cohort of patients with singular BM and neurosurgical resection as first
line treatment approach. We observed that hyperintense preoperative diffusion
weighted imaging correlated with high density of reticulin fibers in the tissue based
analysis and an impaired survival prognosis [132].
Preoperative Diffusion-Weighted Imaging of Single BrainMetastases Correlates with Patient Survival TimesAnna Sophie Berghoff1,9, Thomas Spanberger2,9, Aysegul Ilhan-Mutlu3,9, Manuel Magerle3,9,
Markus Hutterer4, Adelheid Woehrer1,9, Monika Hackl5, Georg Widhalm6,9, Karin Dieckmann7,9,
Christine Marosi3,9, Peter Birner8,9, Daniela Prayer2,9, Matthias Preusser3,9*
1 Institute of Neurology, Medical University of Vienna, Vienna, Austria, 2 Department of Radiology, Division of Neuroradiology, Medical University of Vienna, Vienna,
Austria, 3 Department of Medicine I, Medical University of Vienna, Vienna, Austria, 4 Department of Neurology, Wilhelm Sander NeuroOncology Therapy Unit, University
Hospital Regensburg, Regensburg, Germany, 5 Austrian National Cancer Registry, Statistics Austria, Vienna, Austria, 6 Department of Neurosurgery, Medical University of
Vienna, Vienna, Austria, 7 Department of Radiotherapy, Medical University of Vienna, Vienna, Austria, 8 Clinical Institute of Clinical Pathology, Medical University of Vienna,
Vienna, Austria, 9 Comprehensive Cancer Center CNS Tumors Unit, Medical University of Vienna, Vienna, Austria
Abstract
Background: MRI-based diffusion-weighted imaging (DWI) visualizes the local differences in water diffusion in vivo. Theprognostic value of DWI signal intensities on the source images and apparent diffusion coefficient (ADC) maps respectivelyhas not yet been studied in brain metastases (BM).
Methods: We included into this retrospective analysis all patients operated for single BM at our institution between 2002and 2010, in whom presurgical DWI and BM tissue samples were available. We recorded relevant clinical data, assessed DWIsignal intensity and apparent diffusion coefficient (ADC) values and performed histopathological analysis of BM tissues.Statistical analyses including uni- and multivariate survival analyses were performed.
Results: 65 patients (34 female, 31 male) with a median overall survival time (OS) of 15 months (range 0–99 months) wereavailable for this study. 19 (29.2%) patients presented with hyper-, 3 (4.6%) with iso-, and 43 (66.2%) with hypointense DWI.ADCmean values could be determined in 32 (49.2%) patients, ranged from 456.4 to 1691.8*1026 mm2/s (median 969.5) andshowed a highly significant correlation with DWI signal intensity. DWI hyperintensity correlated significantly with highamount of interstitial reticulin deposition. In univariate analysis, patients with hyperintense DWI (5 months) and lowADCmean values (7 months) had significantly worse OS than patients with iso/hypointense DWI (16 months) and highADCmean values (30 months), respectively. In multivariate survival analysis, high ADCmean values retained independentstatistical significance.
Conclusions: Preoperative DWI findings strongly and independently correlate with OS in patients operated for single BMand are related to interstitial fibrosis. Inclusion of DWI parameters into established risk stratification scores for BM patientsshould be considered.
Citation: Berghoff AS, Spanberger T, Ilhan-Mutlu A, Magerle M, Hutterer M, et al. (2013) Preoperative Diffusion-Weighted Imaging of Single Brain MetastasesCorrelates with Patient Survival Times. PLoS ONE 8(2): e55464. doi:10.1371/journal.pone.0055464
Editor: Wang Zhan, University of Maryland, College Park, United States of America
Received November 29, 2012; Accepted December 23, 2012; Published February 5, 2013
Copyright: ! 2013 Berghoff et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permitsunrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This study was supported by grant number 13457 of the Austrian National Bank (principle investigator: Matthias Preusser) and grant number MA7-49139/13 of the scholarship program for scientific research of the city of Vienna (recipient: Anna Sophie Berghoff).
Competing Interests: The authors have declared that no competing interests exist.
* E-mail: [email protected]
Introduction
Metastases to the brain are a frequent complication of cancerand are associated with high morbidity and mortality. Primarytumor types vary in their propensity to form brain metastases (BM)with lung cancer, breast cancer and melanoma showing thehighest incidences of central nervous system (CNS) involvement.[1,2] Treatment so far relies mainly on surgery and radiotherapy,although some targeted drugs have shown clinically meaningfulactivity in distinct molecular tumor subtypes and are beginning toenter clinical practice. [3,4,5].
The prognosis of BM patients is poor with median overallsurvival times of only few months. Several risk stratification scores
have been developed such as the recursive portioning analysis(RPA), the graded prognostic assessment (GPA) and the diagnosisspecific graded prognostic assessment (DS-GPA). [6,7,8] Thesescores are based on parameters with established prognostic impactincluding the Karnofsky performance status (KPS), patient age,status of the primary tumor, presence of extracranial metastasesand the number of BM. [6,7,8] Median overall survival (OS) fromdiagnosis of BM varies extensively from 3 months in the leastfavourable group, up to 25.3 months in the most favourablegroups which includes also long term survivors. [8,9] Neurora-diological variables, with the exception of the number of BM, arenot considered for prognostic risk stratification so far.
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The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Magnetic Resonance Imaging (MRI) using pre- and post-contrast T1-weighted imaging, T2-weighted imaging and fluidattenuated inversion recovery (FLAIR) is the modality of choicefor radiological evaluation of brain tumors. [10] Increasingly,additional advanced radiological techniques like magnetic reso-nance spectroscopy (MRS), perfusion MRI, or diffusion-weightedimaging (DWI) are used to characterize brain lesions in order toprovide further clinically relevant information. [11,12] DWI is anMRI method based on the visualisation of the mobility of watermolecules in the extracellular space. A low diffusion capacity dueto a restricted mobility of the water molecules in the extracellularspace results in a hyperintense signal in DWI and low apparentdiffusion coefficient (ADC) values. In contrast, a high diffusioncapacity due to an increased mobility of water molecules results ina hypo- or isointense DWI signals and high ADC values. [12]DWI parameters have been shown to correlate with varioushistopathological characteristics such as tumor type, tumor grade,Ki67 tumor cell proliferation index, cellularity, or amount ofinterstitial fibrosis and survival prognosis in several intra- andextracranial tumor types. [13,14,15,16,17,18,19,20,21]. However,the prognostic value of DWI and its correlation with histomor-phological findings in patients with BM has not been systemat-ically studied so far.
In the present study, we investigated the prognostic impact ofDWI signal intensity and performed a correlative analysis withtissue-based parameters in a homogenous cohort of patientswith single BM and surgery as first line treatment for BM.
Patients and Methods
Ethics StatementThe study was approved by the local ethics committee of the
Medical University of Vienna, Austria. No written consent wasgiven by the patients for their information to be stored in thedatabase and used for research, because this study was performedin a retrospective manner in line with local regulations. Theinstitutional ethics committee waived the need for writteninformed consent from the participants for this project (Ethicscommittee protocol number 641/2011).
PatientsWe identified all patients with radiologically proven single
BM who underwent surgery as a first-line-therapy for a singleBM between April 2002 and December 2010 and whosepresurgical MRI work-up included DWI. Availability of at leastone tissue block for research purposes with viable BM tissue andfull information on the clinical course including date ofdiagnosis, administered therapies, Karnofsky performance score,GPA and date of death or date of last follow-up investigationwere mandatory for inclusion. All clinical parameters wereretrieved by chart review and from the database of NationalCancer Registry of Austria and the Austrian Brain TumorRegistry. [22].
Imaging AnalysisAll imaging analyses were performed by one investigator (TS)
blinded to all clinical and histological data. In conventionalMRI (contrast-enhanced and native T1-weighted images,FLAIR and T2-weighted images, as available) the maximumdiameter and localization of the single BM was determined. InDWI, the BM was semiquantitatively judged to be eitherhypointense, isointense, or hyperintense in comparison tonormal non-pathological brain tissue. In BM which showedheterogeneous signal behaviour, diffusion intensity was graduat-
ed upon the predominant (.70% of the metastasis) signalbehaviour. In the cases with available ADC maps, ADC valueswere derived as described previously in up to 5 non-overlappingareas of interest (each at least 50 mm2) in solid, non-necrotic,non-macrohemorrhagic areas of the BM. In each case, themean ADC value (ADCmean) was calculated from the ADCvalues of all areas of interest. [13].
Tissue Based AnalysisTissue based analysis was performed blinded to clinical and
radiological data. Histological confirmation of BM was evaluatedon routinely performed hematoxylin and eosin (H&E) stainedtissue sections by a specialist in neuropathology. Cellularity wasevaluated semiquantatively on an H&E section as low, moderateand high. Gomori silver impregnation stain for reticulin wasperformed according to laboratory standard. The amount ofextracellular reticulin fibers was semiquantitatively grouped asfollows: prominent interstitial fibrosis (more than 25% of thetumor tissue displaying a dense interstitial meshwork of reticulinfibres); little interstitial fibrosis (less than 25% of the tumor tissuedisplaying a dense interstitial meshwork of reticulin fibres). Ki67(antibody MIB1, Dako, Glostrup, Denmark) immunostaining andanalysis was performed as previously published. [23] Ki67proliferation index was obtained by counting 500 cells and givingthe percentage of positive cells (0–100%). [23] Differentiation ofthe tumor tissue was divided into well, moderately and poorlydifferentiated based on the tumor organization, the cell polymor-phism and the mitotic activity.
Statistical AnalysisFor correlation of parameters the Spearmans correlation
coefficient, Chi square test or the Mann-Whitney U test wereused as appropriate. Overall survival (OS) was defined as timefrom first diagnosis of BM until death or last day of follow up. Forall tests, a two-sided p-value of ,0.05 was considered asstatistically significant. For univariate survival analysis Kaplan-Meier curves and the log-rank test were used. Variables thatshowed statistically significant prognostic value at univariatesurvival analysis were entered in multivariate survival analysisusing the Cox regression model.
The statistical software package SPSS version 19 (SPSS Inc,Chicago, IL, USA) was used for all calculations.
Results
Patients’ Characteristics65 patients (31 female, 34 male) with a median age of 59
years (range 33–80) at first diagnosis of BM were available forthis study. All patients had a single BM and surgery as first linetreatment for BM. 45/65 (69.2%) of patients had adjuvantwhole brain radiotherapy (WBRT) and 28/65 (43.1%) adjuvantchemotherapy after surgery of BM. Table 1 lists furtherpatients’ characteristics.
Imaging Analysis19/65 (29.2%) of patients presented with hyperintense, 3/65
(4.6%) with isointense and 43/65 (66.2%) with hypointenseDWI signals. Clinical characteristics including primary tumortypes, size of BM, patient age, status of primary tumor,presence of extracranial metastases and GPA did not differbetween DWI signal intensity groups (p.0.05; Chi square test;table 2).
ADC maps were available for 32 patients. The medianADCmean value was 969.47*1026 mm2/s. ADC values strongly
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correlated with signal intensity in isotropic DWI (p,0.001, Mann-Whitney U test; table 2). Clinical characteristics includingprimary tumor types, size of BM, patient age, status of primary
tumor, presence of extracranial metastases, GPA and KPS did notcorrelate with ADCmean values (p.0.05; Mann Whitney U test).
Table 1. Patients’ characteristics.
Parameter Patient population (n = 65)
n %
Age at first diagnosis of BM, years, (range) 59 (33–80)
Primary tumor type
Lung cancer 25 38.5
Breast cancer 8 12.3
Melanoma 5 7.7
Kidney cancer 5 7.7
Colorectal cancer 3 4.6
Others 19 29.2
Synchronous diagnosis of BM and primary tumor
yes 29 44.6
no 36 55.4
Status of primary tumor at first diagnosis of BM
No evidence of disease 19 52.8
Stable disease 11 30.6
Progressive disease 6 16.7
Presence of extracranical metastases
yes 43 66.2
no 22 33.8
Karnofsky performance score
,70 4 6.2
.70 61 93.8
GPA class
I 23 35.4
II 15 23.1
III 25 38.5
IV 2 3.1
Number of BM
Single BM 65 100
BM localisation
Infratenorial 19 29.2
Supratentorial 46 70.8
Size of BM
,3 cm 22 33.8
.3 cm 43 66.2
DWI signal intensity
Hypointense 43 66.2
Isointense 3 4.6
Hyperintense 19 29.2
ADCmean (range) 969.47*1026 mm2/s (456.38–1691.80)
1st line treatment for BM
Surgery 65 100
WBRT after surgery 45 69.2
Chemotherapy after surgery 28 43.1
OS from first diagnosis of BM, months (range) 15 (0–99)
doi:10.1371/journal.pone.0055464.t001
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Tissue Based Findings14/65 (21.5%) specimens were classified with low, 30/65
(46.2%) with moderate and 21/65 (32.3%) with high cellularitybased on H&E histomorphology.
No statistically significant correlation of DWI signal intensity orADCmean and cellularity was observed (p.0.05; Chi square testand Mann-Whitney U test, respectively). 3/65 (4.6%) specimenswere classified as well differentiated, 12/65 (18.5%) as moderatelydifferentiated and 46/65 (70.8%) as poorly differentiated. Nostatistically significant correlation of DWI signal intensity orADCmean and differentiation was observed (p.0.05; Chi squaretest and Mann-Whitney U test, respectively). Mean ki67 prolifer-ation index was 44.4% (range 5.4% –89.6%) and did not correlatewith DWI signal intensity (p.0.05; Mann-Whitney U test) orADCmean values (Spearmans correlation coefficient r = - 0.3,p = 0.09). 24/65 (36.9%) specimens presented with prominentinterstitial fibrosis while 41/65 (63.1%) showed little interstitialfibrosis. Semiquantitative DWI signal intensity showed a signifi-cant correlation with density of the reticulin network: tumors withrestricted diffusion showed higher amounts of interstitial fibrosisand tumors with unrestricted diffusion showed less interstitialfibrosis (p = 0.02; Chi square test; table 2, figure 1).
Survival AnalysesMedian OS from first diagnosis of BM to death was 15 months
(range 0–99 months) in the entire population.In univariate analysis, patients with hypo/isointense DWI signal
intensity showed a significantly longer survival with a median OSof 16 months (95% CI: 10.79–21.25) than patients withhyperintense DWI signal intensity with a median OS of 5 months(95% CI: 0–12.47; p = 0.029; log rank test; figure 2). Patientswith high ADCmean values showed a significantly longer survivalwith a median OS of 30 months (95% CI: 13.97–46.03) thanpatients with low ADCmean values with a median OS of 7 months(95% CI: 1.51–12.49; p = 0.02; log rank test; figure 2). Further-more, primary tumor type, Karnofsky performance score ,70,lack of adjuvant WBRT after neurosurgery and high GPA weresignificantly associated with unfavourable OS in univariateanalysis (p,0.05). Adjuvant chemotherapy after surgery for BMhad no statistically significant impact on OS (p.0.05).
All factors with statistically significant impact on OS in theunivariate analysis were included in multivariate analysis (AD-Cmean, primary tumor type, KPS and adjuvant WBRT (yes/no)).Primary tumor type as well as KPS and adjuvant WBRT did notremain statistically significant in multivariate analysis. Only highADCmean values remained as statistically significant independent
Table 2. Diffusion weighted imaging analysis.
Parameter DWI signal intensityChisquare
Hypo/isointense Hyperintense
n % n %
Age at first diagnosis of BM
,60 years 26 74.3 9 25.7 0.50
.60 years 20 66.7 10 33.3
Primary tumor type
Lung cancer 19 76 6 24 0.22
Breast cancer 6 75 2 35
Melanoma 3 60 2 40
Kidney cancer 5 100 0 0
Colorectal cancer 3 100 0 0
Others 10 53.8 9 46.2
Status of primary tumor at first diagnosis of BM
Synchronous diagnosis 20 69 9 31 0.14
No evidence of disease 14 73.7 5 26.3
Stable disease 7 63.6 4 36.4
Progressive disease 5 83.3 1 16.7
Presence of extracranial metastases
yes 13 59.1 9 40.9 0.16
no 33 76.7 10 23.3
Karnofsky performance score
,70 1 25 3 75 0.04
.70 45 73.8 16 26.2
GPA class
I 19 82.6 4 17.4 0.45
II 10 66.7 5 33.3
III 16 64 9 36
IV 1 50 1 50
BM localisation
Infratentorial 14 73.7 5 26.3 0.74
Supratentorial 32 69.6 14 30.4
Size of BM
,3 cm 16 72.7 6 27.3 0.80
.3 cm 30 69.8 13 30.2
ADCmean
,969.47*1026 mm2/s 8 44.4 10 55.6 0.001
.969.47*1026 mm2/s 15 100 0 0
Celluarity
Low 9 64.3 5 35.7 0.86
Moderate 22 73.3 8 26.7
High 15 71.4 6 28.6
Differentiation
Low 34 73.9 12 26.1 0.50
Moderate 8 66.7 4 33.3
High 3 100 0 0
Ki67 proliferation index
0–25% 12 75 4 25 0.81
25.1–50% 15 71.4 6 28.6
Table 2. Cont.
Parameter DWI signal intensityChisquare
Hypo/isointense Hyperintense
n % n %
50.1–75% 17 70.8 7 29.2
75.1–100% 2 50 2 50
Interstitial fibrosis
Little 33 80.5 8 19.9 0.02
Prominent 13 54.2 11 45.8
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Figure 1. T1-weighted and diffusion weighted imaging of a patient with hyperintense DWI signal intensity (A, B) and of a patientwith hypointense DWI signal intensity (D, E) and the Gomori silver impregnation stain for reticulin in these patients showing densereticulin network (C) and scattered reticulin network (F).doi:10.1371/journal.pone.0055464.g001
Figure 2. Kaplan Meier plots showing the statistically significant association of DWI signal intensity (A), ADCmean values (B).doi:10.1371/journal.pone.0055464.g002
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prognostic factors (Harzard ratio 0.32, 95% CI 0.12–0.91;p = 0.03; Cox regression model; table 3).
Discussion
In this study, we found a highly significant association of pre-surgical DWI parameters with OS times of patients operated forsingle BM. Both, DWI signal intensity as assessed semiquantita-tively by visual impression and ADCmean values stratified patientsinto prognostic groups. The median OS of patients with tumorsshowing hyperintense DWI was 5 months compared to 16 monthsin patients with iso- or hypointense DWI signals (p = 0.029; logrank test). ADCmean values showed an even stronger separationof risk groups with patients with high ADCmean values showingmore than 4-times longer median OS (30 months) than patientswith low ADCmean values (7 months; p = 0.008; log rank test).The prognostic impact of ADC values was independent fromknown prognostic factors including GPA class, the primary tumortype and the KPS and also from postoperative therapy includingadjuvant WBRT and chemotherapy in multivariate analysis(Hazard ratio 0.32, 95% CI 0.12–0.91; p = 0.03; Cox regressionmodel).
While, to the best of our knowledge, the correlation of DWIparameters with patient outcomes has not been investigated inBM, some studies have postulated a prognostic value of DWIsignal intensity in primary tumors. In colorectal cancer, low meanADC values were shown to be associated with aggressive tumorbehaviour, impaired response to therapy and decreased prognosis.[19] Similarly, a correlation of low ADC values and impaired OSand impaired progression free survival was postulated for severalother extracranial cancers with high propensity to form BM like
lung cancer or breast cancer. [21,24] For the instance ofintracranial lesions, hyperintense DWI signal were shown to beassociated with worse outcome in primary CNS lymphoma andpituitary macroadenoma. [16,25] In line with these findings weobserved a statistically significant and independent adverseprognostic value of restricted diffusion in our homogenous cohortof patients with single BM. Therefore, DWI signal intensity couldserve as a prognostic imaging biomarker for clinical decisionmaking.
The DWI signal intensity was shown to correlate with histologyand cellularity of various intra- and extracranial tumors, providingan indirect insight in a tumor’s microarchitecture.[13,15,19,21,26] In high grade gliomas a hyperintense DWIsignal with low ADCmean values resembles areas of highcellularity with high cytoplasm to nucleus ratio. [14,15] Similar,a correlation of hyperintense DWI signal intensity and poor tumordifferentiation was shown for extracranial tumors like lung cancer,breast cancer or rectal cancer. [19,21,24] For the instance of BM,a low ADCmean value was shown to correlate with high tumorcellularity and poor tumor differentiation. [26,27] In our study, wecould demonstrate a significant correlation of a prominentinterstitial fibrosis with signs of restricted diffusion in DWI, whichresembles the impaired mobility of water molecules in theintercellular space. The interstitial reticulin fiber network is partof the fibrotic collagen-rich tumor stroma and our data furtheremphasize the importance of the microenvironment in thepathobiology of BM. [28] In line with our results, several othertumor types with a restricted diffusion due to dense stromal matrixwere shown to have an impaired survival prognosis. [29,30,31].
Our study has some limitations that need to be acknowledged.We performed a retrospective study in a single center and were
Table 3. Survival analysis from first diagnosis of brain metastasis to death.
Parameter Median OS, months95% Confidenceinterval Log-rank test Cox regression model
ADCmean
,969.47 7 1.51–12.49 0.008 0.03
.969.47 30 13.97–46.03
Primary tumor type
Lung cancer 21 11.81–30.19 0.015 0.64
Breast cancer 12 0–31.40
Melanoma 4 0.78–7.22
Kidney cancer not reached not reached
Colorectal cancer 11 0–22.20
Others 12 5.76–18.24
Karnofsky performance
,70 1 0–3.94 0.001 0.06
.70 15 11.73–24.27
GPA class
I 21 16.57–25.43 0.001 0.48
II 21 1.77–40.23
III 12 0.28–23.73
IV 0 -
WBRT after surgery
Yes 18 12.66–23.34 0.034 0.41
No 5 0–11.57
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therefore able to include only a limited number of cases, thusrestricting the statistical power of our correlative analyses. On theother hand, our approach enabled us to analyse a well-definedpatient cohort characterized by single brain metastasis homo-genously treated by neurosurgical BM resection as the initialtherapy. Another limitation related to the retrospective nature ofour study is the fact that ADC maps could not be retrieved in allcases. In the absence of ADC maps, diffusion restriction as cause ofDWI hyperintensity cannot be unequivocally differentiated fromother phenomena such as T2-shine through. [32] Further, theaccuracy of ADC values is potentially limted due to the usage ofdifferent MRI machines. [33] However, we found a strongcorrelation of ADC values and semiquantitaitve DWI signalintensity in the cohort of 32 patients of whom both parameterswere available. Furthermore, in this cohort the prognostic impactof ADC values was even more pronounced than the semiquan-titatively evaluated DWI signal intensity. Still, our findings need tobe reproduced in independent data sets, preferably in prospectivestudies.
In conclusion, we could demonstrate the independent prognos-tic value of DWI findings in our large homogenous cohort ofpatients with a single BM and its correlation with tissue basedcharacteristic, indicating the value of DWI signal intensity as animaging biomarker. Future studies should prospectively evaluate
the prognostic value and the inclusion in prognostic scores of DWIparameters.
Acknowledgments
We thank Irene Leisser and Carina Dinhof for excellence technicalassistance. This study was performed within the PhD thesis project of AnnaSophie Berghoff in the PhD program ‘‘Clinical Neuroscience (CLINS)’’ atthe Medical University Vienna. This study was performed within theframework of the Society of Austrian Neurooncology (SANO, www.sano.co.at). Dr. Berghoff gratefully acknowledges EANO and SNO for awardingher with the EANO/SNO Travel Grant that allowed the first presentationof these data in an oral presentation at SNO 2012 (November 17th,Washington, USA).
Author Contributions
Conceived and designed the experiments: ASB TS AIM MM M. HuttererAW M. Hackl GW KD CM PB DP MP. Performed the experiments: ASBTS AIM MM M. Hutterer AW M. Hackl GW KD CM PB DP MP.Analyzed the data: ASB TS AIM MM M. Hutterer AW M. Hackl GWKD CM PB DP MP. Contributed reagents/materials/analysis tools: ASBTS AIM MM M. Hutterer AW M. Hackl GW KD CM PB DP MP. Wrotethe paper: ASB TS AIM MM M. Hutterer AW M. Hackl GW KD CM PBDP MP.
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9. Berghoff AS, Bago-Horvath Z, Ilhan-Mutlu A, Magerle M, Dieckmann K, et al.(2012) Brain-only metastatic breast cancer is a distinct clinical entitycharacterised by favourable median overall survival time and a high rate oflong-term survivors. Br J Cancer 107: 1454–1458.
10. Gaspar LE, Gutin PH, Rogers L, Schneider JF, Larson D, et al. (2000) Pre-irradiation evaluation and management of brain metastases. American Collegeof Radiology. ACR Appropriateness Criteria. Radiology 215 Suppl: 1105–1110.
11. Calli C, Kitis O, Yunten N, Yurtseven T, Islekel S, et al. (2006) Perfusion anddiffusion MR imaging in enhancing malignant cerebral tumors. Eur J Radiol 58:394–403.
12. Lee EK, Lee EJ, Kim MS, Park HJ, Park NH, et al. (2012) Intracranialmetastases: spectrum of MR imaging findings. Acta Radiol. In press.
13. Arvinda HR, Kesavadas C, Sarma PS, Thomas B, Radhakrishnan VV, et al.(2009) Glioma grading: sensitivity, specificity, positive and negative predictivevalues of diffusion and perfusion imaging. J Neurooncol 94: 87–96.
14. Fan GG, Deng QL, Wu ZH, Guo QY (2006) Usefulness of diffusion/perfusion-weighted MRI in patients with non-enhancing supratentorial brain gliomas: avaluable tool to predict tumour grading? Br J Radiol 79: 652–658.
15. Sugahara T, Korogi Y, Kochi M, Ikushima I, Shigematu Y, et al. (1999)Usefulness of diffusion-weighted MRI with echo-planar technique in theevaluation of cellularity in gliomas. J Magn Reson Imaging 9: 53–60.
16. Boxerman JL, Rogg JM, Donahue JE, Machan JT, Goldman MA, et al. (2010)Preoperative MRI evaluation of pituitary macroadenoma: imaging features
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17. Wang S, Kim S, Chawla S, Wolf RL, Knipp DE, et al. (2011) Differentiationbetween glioblastomas, solitary brain metastases, and primary cerebrallymphomas using diffusion tensor and dynamic susceptibility contrast-enhancedMR imaging. AJNR Am J Neuroradiol 32: 507–514.
18. Pillai S, Singhal A, Byrne AT, Dunham C, Cochrane DD, et al. (2011)Diffusion-weighted imaging and pathological correlation in pediatric medullo-blastomas-‘‘They are not always restricted!’’. Childs Nerv Syst 27: 1407–1411.
19. Curvo-Semedo L, Lambregts DM, Maas M, Beets GL, Caseiro-Alves F, et al.(2012) Diffusion-weighted MRI in rectal cancer: apparent diffusion coefficient asa potential noninvasive marker of tumor aggressiveness. J Magn Reson Imaging35: 1365–1371.
20. Aoyagi T, Shuto K, Okazumi S, Hayano K, Satoh A, et al. (2012) Apparentdiffusion coefficient correlation with oesophageal tumour stroma and angiogen-esis. Eur Radiol 22: 1172–1177.
21. Nakajo M, Kajiya Y, Kaneko T, Kaneko Y, Takasaki T, et al. (2010) FDGPET/CT and diffusion-weighted imaging for breast cancer: prognostic value ofmaximum standardized uptake values and apparent diffusion coefficient valuesof the primary lesion. Eur J Nucl Med Mol Imaging 37: 2011–2020.
22. Wohrer A, Waldhor T, Heinzl H, Hackl M, Feichtinger J, et al. (2009) TheAustrian Brain Tumour Registry: a cooperative way to establish a population-based brain tumour registry. J Neurooncol 95: 401–411.
23. Preusser M, Hoeftberger R, Woehrer A, Gelpi E, Kouwenhoven M, et al. (2012)Prognostic value of Ki67 index in anaplastic oligodendroglial tumours–atranslational study of the European Organization for Research and Treatmentof Cancer Brain Tumor Group. Histopathology 60: 885–894.
24. Ohno Y, Koyama H, Yoshikawa T, Matsumoto K, Aoyama N, et al. (2012)Diffusion-weighted MRI versus 18F-FDG PET/CT: performance as predictorsof tumor treatment response and patient survival in patients with non-small celllung cancer receiving chemoradiotherapy. AJR Am J Roentgenol 198: 75–82.
25. Barajas RF Jr, Rubenstein JL, Chang JS, Hwang J, Cha S (2010) Diffusion-weighted MR imaging derived apparent diffusion coefficient is predictive ofclinical outcome in primary central nervous system lymphoma. AJNRAm J Neuroradiol 31: 60–66.
26. Duygulu G, Ovali GY, Calli C, Kitis O, Yunten N, et al. (2010) Intracerebralmetastasis showing restricted diffusion: correlation with histopathologic findings.Eur J Radiol 74: 117–120.
27. Hayashida Y, Hirai T, Morishita S, Kitajima M, Murakami R, et al. (2006)Diffusion-weighted imaging of metastatic brain tumors: comparison withhistologic type and tumor cellularity. AJNR Am J Neuroradiol 27: 1419–1425.
28. Langley RR, Fidler IJ (2011) The seed and soil hypothesis revisited–the role oftumor-stroma interactions in metastasis to different organs. Int J Cancer 128:2527–2535.
29. Moorman AM, Vink R, Heijmans HJ, van der Palen J, Kouwenhoven EA(2012) The prognostic value of tumour-stroma ratio in triple-negative breastcancer. Eur J Surg Oncol 38: 307–313.
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cancer patients, especially in triple-negative carcinoma patients. Breast CancerRes Treat 125: 687–696.
31. Mesker WE, Junggeburt JM, Szuhai K, de Heer P, Morreau H, et al. (2007) Thecarcinoma-stromal ratio of colon carcinoma is an independent factor for survivalcompared to lymph node status and tumor stage. Cell Oncol 29: 387–398.
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33. Sasaki M, Yamada K, Watanabe Y, Matsui M, Ida M, et al. (2008) Variability inabsolute apparent diffusion coefficient values across different platforms may besubstantial: a multivendor, multi-institutional comparison study. Radiology 249:624–630.
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! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !
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6.5 Invasion patterns in brain metastases of solid cancers. !Interlude BM are described as well delineated lesions towards the surrounding brain
parenchyma [133]. However, preclinical studies suggest that invasion patterns might
differ as growth alongside pre-existing vessels was observed in a melanoma BM
mouse model [43]. Further, a diffusely infiltrating growth, as observed in
glioblastoma, was observed in some cases of small cell lung cancer [134]. Although
different invasion patterns, namely expansive growth, multicellular migration and
individual cell migration were postulated for extracranial tumours, no study
systematically investigated the invasion patterns of BM and the involved molecular
factors [135]. In order to investigate the interaction of BM with the surrounding brain
parenchyma, we conducted a cohort of BM autopsy specimen containing viable brain
metastasis tumour tissue but as well the surrounding brain parenchyma. In the paper
“Invasion patterns in brain metastases of solid cancers” we investigated the
infiltrative pattern of BM [136]. We observed a well-demarcated growth, growing
rather through outwardly extending than through infiltration only in half of the
investigated specimens. Expression of adhesion molecule integrin alpha v beta 6,
which is known to modulate invasion and inhibit apoptosis, was associated with well-
demarcated growth. Growth either via vascular co-option or a glioma like diffuse
single cell infiltration was observed in the remaining investigated specimens. The
high fraction of BM showing an infiltrative growth pattern has clinical implication as
the inclusion of a safety margin in local therapy approaches such as neurosurgery
and radiosurgery, has to be discussed in cases with infiltrating growth in order to
prevent local recurrences. Concerning the primary tumour, growth via vascular co-
option was more frequently observed in melanoma BM, while small cell lung cancer
BM showed a high propensity for diffuse single cell infiltration.
Invasion patterns in brain metastasesof solid cancers
Anna S. Berghoff, Orsolya Rajky, Frank Winkler, Rupert Bartsch, Julia Furtner,Johannes A. Hainfellner, Simon L. Goodman, Michael Weller, Jens Schittenhelm,and Matthias Preusser
Institute of Neurology, Medical University of Vienna, Vienna, Austria (A.S.B., J.A.H.); Department of Medicine I,
Medical University of Vienna, Vienna, Austria (O.R., R.B., M.P.); Comprehensive Cancer Center, CNS Unit (CCC-
CNS), Vienna, Austria (A.S.B., O.R., R.B., J.A.H.); Neurology Clinic and National Center for Tumor Disease,
University of Heidelberg, Heidelberg, Germany (F.W.); Department of Radiology, Medical University of Vienna,
Vienna, Austria (J.F.); Therapeutic Area Oncology, Cellular Pharmacology, Merck-Serono, Darmstadt, Germany
(S.L.G.); Department of Neurology, University Hospital Zurich, Zurich, Switzerland (M.W.); Department of
Neuropathology, Institute of Pathology and Neuropathology, University of Tubingen, Tubingen, Germany (J.S.)
Background. Brain metastases are generally consideredto be well demarcated from the surrounding brain paren-chyma, although infiltrative growth patterns have beenobserved. We systemically investigated infiltrationpatterns and expression of adhesion molecules in a largeand well-defined series of autopsy cases of brain meta-stases.Methods. Ninety-seven autopsy specimens from 57 brainmetastasis patients (primary tumor: 27 lung cancer, 6breast cancer, 8 melanoma, 2 colorectal cancer, 1 kidneycancer, and 13 other) were evaluated for patterns of inva-sion into surrounding brain parenchyma. Expression ofintegrins av; cytoplasmic b3, avb3, avb5, avb6, andavb8;andofEandNcadherinwereevaluatedusing immu-nohistochemistry.Results. Three main invasion patterns were seen: well-demarcated growth (29/57, 51%), vascular co-option(10/57, 18%), and diffuse infiltration (18/57, 32%).There was no statistically significant association of inva-sion pattern with primary tumor type, although vascularco-option was most common in melanoma brain metasta-ses (4/10). Invasion patterns of different brain metastasesof the same patient were highly concordant (P , .001,chi-square test). Distance of infiltration from the maintumor mass ranged from 12.5 mm to 450 mm (median56.2 mm) and was not significantly different between
the vascular co-option and the diffuse infiltrationgroups.Levelsofavb6were significantlyhigher in thewell-demarcated group than in the vascular co-option and thediffuse infiltration groups (P¼ .033, Kruskal-Wallis test).Expression of avb5 in tumor cells was higher in brain me-tastasis lesions previously treated with stereotactic radio-surgery (P¼ .034, chi-square test).Conclusions. Distinct invasion patterns of brain metasta-ses into the brain parenchyma are not specific for primarytumortypes, seemtobe influencedbyexpressionofav integ-rin complexes, and may help to guide clinical decision-making.
Keywords: adhesion molecules, brain metastases,cadherin, integrin, invasion.
Brain metastases are a frequent complication inoncology and affect up to 40% of patients withmetastatic cancer.1 While the incidence of brain
metastases has shown a constant increase over the lastdecades, treatment options remain limited and relymainly on local approaches like surgery, radiosurgery,or whole brain radiotherapy (WBRT).2–4 Better under-standing of the pathobiology of brain metastases maylead to novel treatments.
Brain metastases are usually regarded as growing ina well-delineated fashion within the brain parenchyma.5
This notion is based mainly on their neuroradiologicalpresentationwith relatively sharpdemarcationofcontrast-enhancing areas and a generally better delineation thanthat of malignant gliomas. However, the histological pat-terns of invasion in brain metastases have so far notbeenaddressed incomprehensive studies, althoughinfiltra-tive behavior has occasionally been noted.6,7 Clinically,
Corresponding Author: Matthias Preusser, MD, Department of
Medicine I and Comprehensive Cancer Center, Central Nervous System
Tumours Unit (CCC-CNS), Medical University of Vienna, Waehringer
Guertel 18-20, 1090 Vienna, Austria (matthias.preusser@meduniwien.
ac.at).
Received May 11, 2013; accepted June 17, 2013.
Neuro-Oncologydoi:10.1093/neuonc/not112 NEURO-ONCOLO GY
#The Author(s) 2013. Published by Oxford University Press on behalf of the Society for Neuro-Oncology.All rights reserved. For permissions, please e-mail: [email protected].
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infiltrative behavior with unclear resection margins is reg-ularly noted by neurosurgeons, and high local recurrencerates after surgery and radiosurgery have been reportedfor such cases.8,9
In general, cancer cells grow and invade solid tissues indifferent ways such as expansive growth, multicellularmigration, and individual cell migration.10 Migrationand invasion require complex regulation of specificmolecules, including adhesion molecules (eg, integrins,cadherins), cytoskeletalcomponents (eg,actomyosin),pro-teolytic enzymes (eg, matrix metalloproteases [MMPs]),and others.10–13 However, the types of invasive behaviorof tumor cells have been described mostly in models ofnon-CNS tissues (eg, skin), and it is unknown whethersimilar mechanisms are active in the brain, with its distinctmicroenvironment. The CNS microenvironment differsfrom that of other solid organs. The brain parenchmya iscomposed of highly specialized cells (neurons, astrocytes,oligodendrocytes, microglia), and its extracellular matrix(ECM) has a distinct composition. It lacks constituentsusually found in solid organs, such as fibronectin and colla-gen, but it is rich in proteoglycans, tenascin, laminin,heparin/chondroitin/dermatan sulfates, and hyaluronicacid.14
In this studywesystemically characterized the invasionpatterns of brain metastases and their correlation with theexpression of several adhesion molecules in a series ofautopsy specimens. Surgery specimens are not suitablefor such studies, since in most cases they include no oronly little well-preserved brain tissue around the resectionmargin and are thus not sufficient for investigation of theinvasion front and the interaction of cancer cells with thebrain parenchyma.
Materials and Methods
Patients
All patients with histologically proven brain metastaseswho underwent brain autopsy between 1987 and 2011were identified from the Neuro-Biobank of the Medical
University of Vienna. From each patient, at least one rep-resentative formalin-fixed and paraffin-embedded tissueblock containing tumor tissue and surrounding brain pa-renchyma was selected. Clinical and demographic datawere retrieved by chart review. This study was approvedby the ethics committee of the Medical University ofVienna (ethics committee protocol number 078/2004).
Evaluation of Invasion Patterns
Evaluation of invasion patterns was performed on oneroutinely stained hematoxylin and eosin (H&E) sectionper tumor block. For enhanced visibility and better evalu-ation of single tumor cells, immunohistochemistry forcytokeratin (carcinomas) or HMGB45 (melanomas)and for evaluation of vascular structure immunohisto-chemistry for CD34 was performed on an automated hor-izontal slide-processing system (AutostainerPlusLink,Dako) using standard protocols in selected cases(Table 1).15–17 Maximal invasion distance of tumorcells from the main tumor mass was microscopically mea-sured on H&E slides with a grid of 25 mm length at 400×magnification.
Immunohistochemistry and Evaluation of Integrins andCadherins
Immunohistochemistry for the av subunit, cytoplasmic b3,andavb3,avb5,avb6, andavb8complexeswasperformedwith a fully automated multimodal slide-staining system(BenchMark, Ventana Medical Systems) as described previ-ously.18 In brief, an indirect biotin-avidin system with stan-dard cell conditioner 1 and EDTA pretreatment protocolwere used. Signal amplification was achieved with a copperenhancer (iView DAB Detection Kit, Ventana MedicalSystems).19 Immunohistochemistry for E cadherin and Ncadherin was performed using an automated horizontalslide-processing system (AutostainerPlusLink, Dako). Inbrief, antigen retrieval was performed with ph9 buffer(Flex TRS high, Dako). Slides were incubated with primaryantibody for 1 h for N cadherin (anti–N cadherin antibody,ab18203, solution 1:500, abcam) and overnight for E
Table 1. Antibodies
Antibody to Clone Dilution Positive Control Source
av subunit EM01309 1:1000* HT29 colon cancer cell line, DU-145 prostate cancer cell line Goodman et al18
b3 subunit EM00212 1:500* Normal kidney, malignant melanoma Goodman et al18
avb3 EM22703 1:500 Normal kidney, malignant melanoma Goodman et al18
avb5 EM09902 1:800* Normal colon tissue, HT29 colon cancer cell line Goodman et al18
avb6 EM05201 1:1000* Normal kidney, HT29 colon cancer cell line Goodman et al18
avb8 EM13309 1:1000* Normal peripheral nerve, Ovcar-3 ovarian cancer cell line Goodman et al18
E cadherin Ab15148 1:30 Skin Abcam
N cadherin Ab18203 1:500 Liver carcinoma Abcam
CD34 NCL-END 1:500 Glioblastoma Novocastra,
Pan-cytokeratin Lu5 1:100 Lung carcinoma BMA Biomedicals
HMBG45 HMB45 1:50 Melanoma Dako
*Protein concentration 1 mg/mL.
Berghoff et al.: Invasion patterns in brain metastases of solid cancers
2 NEURO-ONCOLOGY
cadherin (anti–E cadherin antibody, ab15148, solution1:30, abcam). Adequate positive and negative controlswere included in each run. Table 1 lists antibodies, clones,dilution, positive controls, and sources of reagents.
Analyses of immunohistochemical staining of theintegrin av subunit, cytoplasmic b3, avb3, avb5, avb6,and avb8 complexes, and E cadherin and N cadherinwere performed by calculating the H-score.20,21 In brief,the intensity of membranous staining was multipliedby the percentage of cells showing a specific, complete,membranous immunoreactivity. Further, integrin andcadherin expression of the vascular structures of the sur-rounding brain parenchyma, tumor vessels, peritumoralvessel, and stroma was evaluated semiquantitatively andrecorded as either positive or negative.
Macroscopic Autopsy and Radiology
For illustrative purposes, we retrospectively retrieved dig-itized photographs of the macroscopic autopsy specimensand premortem cranial MR images of the investigatedpatient cohort from the archives of our Neuro-Biobankand the Department of Neuroradiology where available.
Statistics
We performed exploratory analyses of the correlationbetween invasion pattern and integrin and cadherin ex-pression. For correlation of 2 binary variables, thechi-square test was used. For correlation of mediansbetween invasion groups, the Kruskal–Wallis test wasperformed. For correlation of invasion patterns withtime from first diagnosis of brain metastases to death(overall survival time), we used the Kaplan–Meiermethod and the log-rank test. Patients in whom brainmetastases were detected at death were excluded fromsurvival analysis. As the purpose of the study was explor-atory, no adjustment for multiple testing was applied.22
All statistics were calculated using Statistical Packagefor the Social Sciences 20.0 software.
Results
Patients’ Characteristics
Fifty-seven patients (26 female, 31 male) with a medianage of 58 years (range 27–91) at death were included inthe analysis. Overall, 97 autopsy specimens were evaluat-ed. Available for investigation were 1 brain metastasistissue block in all 57 patients, 2 distinct brain metastasistissue blocks in 30/57 (52.6%) patients, and 3 distinctbrain metastasis tissue blocks in 10/57 (17.5%) patients.In 18/57 (31.6%) patients, diagnosis of brain metastaseswas made only at autopsy. Twenty-three of 57 (40.4%)patients received treatment for brain metastases.First-line treatment for brain metastases was surgeryin 7/57 (12.3%) patients, stereotactic radiosurgery(SRS) in 8/57 (14.0%), WBRT in 4/57 (7.0%), and che-motherapy in 4/57 (7.0%). Overall, 7/57 (12.3%)
patients received WBRT during the course of disease, 7/57 (12.3%) received SRS of the brain metastasis investi-gated in this study, and 17/57 (29.8%) patients receivedchemotherapy during the course of disease. Upon diagno-sis of brain metastases, 34/57 (59.6%) patients weretreated with best supportive care. According to autopsyprotocols, brain metastases were the cause of death in19/57 (33.3%) patients. Table 2 summarizes further thepatients’ characteristics, and detailed compilation isgiven in Supplemental Table S1.
Invasion Patterns of Brain Metastases
Histomorphology.—We delineated 3 distinct invasionpatterns: 29/57 (50.9%) brain metastases showed a dis-tinct, well-demarcated border to the surrounding brainparenchyma (well-demarcated group); 10/57 (17.5%;Fig. 1A) brain metastases showed distinct perivascularprotrusions of multicellular tumor cell formations fromthe main tumor mass into the brain parenchyma (vascularco-option group; Fig. 1B); and 18/57 (31.6%) brain me-tastases showed a diffuse infiltration of single tumor cellsinto the surroundingbrainparenchyma(diffuse infiltrationgroup;Fig.1C).Generally, the invasionpatternwasconsis-tent throughout major parts (.90% of the border) of thetumor/brain border in individual metastases.
In 30/57 (52.6%) cases, multiple distinct brain metas-tases of the same patient were available for investigation,and the invasion type was generally highly congruentamong the lesions (P , .001, chi-square test; Table 3).
Median maximal measurable invasion distance oftumor cells from the border of the main tumor mass was68.7 mm (range 12.5–125 mm) in the vascular co-optiongroup and 56.2 mm (range 12.5–450 mm) in the diffuseinfiltration group. The maximal measurable invasion dis-tance was not different between the vascular co-optiongroup and the diffuse infiltration group (P ¼ .486, t-test).
Correlation with primary tumor type.—Brainmetastasesof melanoma tended to grow via vascular co-option moreoften than other primary tumors (4/8). The most frequentprimary tumor in the well-demarcated as well as in thediffuse infiltrationgroupwas lungcancer.Brainmetastasesof small cell lung cancer (SCLC) showed frequentlya diffuse infiltrative growth (2/3), whereas non-SCLC(NSCLC) grew rather well demarcated (13/24, 54.2%).Squamous NSCLC was more common in the well-demarcated group (4/6), whereas adenocarcinomaNSCLC was equally represented in the well-demarcated(5/12, 41.7%) and the diffuse infiltration group (5/12,41.7%). See Table 2 for correlation of invasion patternswith primary tumor type.
Correlation with treatment.—Complete information onapplied therapies after diagnosis of brain metastaseswasavailable for 55/57 (96.5%) patients. No statisticallysignificant association was observed between first-line orother brain metastasis treatment and invasion patterns(Table 2). In the diffuse infiltration group, a higher pro-portion of patients had received WBRT at any time
Berghoff et al.: Invasion patterns in brain metastases of solid cancers
NEURO-ONCOLOGY 3
point (4/18; 22%) compared with the well-demarcatedgroup (2/28, 7.1%) or the vascular co-option group(1/10). Further, a higher proportion of patients hadreceived chemotherapy during their course of disease inthe diffuse infiltration group (8/17, 47.1%) than in thewell-demarcated (8/28, 28.6%) or the vascularco-optiongroup (1/10).
Correlation with clinical characteristics.—Survival timesfrom first diagnosis of brain metastases were available in 37patients. Median survival from diagnosis of brain metasta-ses was 2.0 months in the well-demarcated group (n ¼ 19),1.8 months in the vascular co-option group (n ¼ 5), and1.8 months in the diffuse infiltration group (n ¼ 13).Therewas no statistically significant correlation of invasionpattern with survival time from diagnosis of brain metasta-ses in this small cohort (P¼ .945, log-rank test). Patients inthe well-demarcated group had more often a singularbrain metastasis at first diagnosis of brain metastases(52%) than the vascular co-option (33.3%) or diffuse in-filtration group (35.7%; P ¼ .483, chi-square test).Extracranial metastases were present in 19/57 (33.3%)patients. No difference in the presence of extracranial me-tastases was observed between the 3 invasion patterns(P¼ .781, chi-square test). In the cohort of all 56 patients,therewasnosignificantassociationof invasionpatternwithsurvival time (P ¼ .825, log-rank test).
Correlation with macroscopic pathology findings andneuroradiology.—Illustrative correlations of macroscop-ic pathology and neuroradiological findings with histo-logical invasion patterns are shown in Fig. 1. The lownumber of available macroscopic photographs (n ¼ 4)and premortal neuroradiological images (n ¼ 5) preclud-ed systematic correlation with histological findings.
Integrin Expression
General description.—Alpha-v integrins showed strongmembranous expression on tumor, vascular, andstromal cells in variable fractions of cases. In general,the majority of specimens showed homogeneousav integ-rin expression patterns throughout the tumor tissue,except for avb8 expression, which was absent in the ma-jority of specimens (Supplemental Table S1). However,regionalaccentuationof integrinexpressionwasobservedin some specimens. Accentuated expression in perivascu-lar tumor cells was observed in 11/57 (19.3%), 9/57(15.8%), and 4/57 (7.0%) cases for the av subunit,avb6, and avb5, respectively. Perinecrotic overexpres-sion of avb6, av subunit, and avb5 was found in 4/57(7.0%), 2/57 (3.5%), and 2/57 (3.5%) cases, respectively(Fig. 2).
Analyzing expression on vascular structures, we ob-served avb5 integrin expression on all (57/57, 100%)
Table 2. Patient characteristics and integrin expression
Characteristic Well-demarcated(n 5 29)
VascularCo-option(n 5 10)
DiffuseInfiltration(n 5 18)
Chi-square Test,Kruskal–Wallis Test
n % n % n %
Primary tumor type
Lung Cancer 14 51.9 3 11.1 10 37.0
NSCLC 13 54.2 3 12.5 8 33.3
AdenoCa 5 41.7 2 16.7 5 41.7
SquamousCa 4 66.7 0 0 2 33.3
Large cell Ca 2 100.0 0 0 0 0
Not otherwise specified 2 50.0 1 25.0 1 25.0
SCLC 1 33.3 0 0.0 2 66.7 0.285
Breast Cancer 3 50.0 0 0.0 3 50.0
Melanoma 2 25.0 4 50.0 2 25.0
Kidney Cancer 1 100.0 0 0.0 0 0.0
Colorectal Cancer 2 100.0 0 0.0 0 0.0
Other 7 53.8 3 23.1 3 23.1
Localization of investigated brain metastasis
Supratentorial 22 47.8 8 17.4 16 34.8 0.545
Infratentorial 7 63.6 2 18.2 2 18.2
Treatment of investigated brain metastasis
Gamma Knife 0.334
Yes 5 71.4 0 0.0 2 28.6
No 23 46.9 10 20.4 16 32.7
WBRT 0.309
Yes 2 28.6 1 14.3 4 57.1
No 26 53.1 9 18.4 14 28.6
Berghoff et al.: Invasion patterns in brain metastases of solid cancers
4 NEURO-ONCOLOGY
vessels, including tumoral and peritumoral vessels as wellas the vascular structures of the surrounding brain paren-chyma. Alpha-vb3 expression was not observed on thevascular structures of the surrounding brain parenchyma,
except randomly on some larger vessels of the meninges.Prominent expression ofavb3 wasobserved on angiogen-ic, sprouting vessels with multilayered endotheliumwithin the tumor and in the peritumoral area. In 30/57
Fig. 1. Distinct invasion patterns in human brain metastases. Top row: example of well-demarcated invasion (patient 5, NSCLC, Supplemental
Table S1): (Aa) H&E slide (magnification ×1.25); (Ab) invasion front of well-demarcated brain metastasis (magnification × 400); (Ac)
macroscopic sample of well-demarcated brain metastasis; (Ad) MRI contrast-enhanced T1-weighted sequence sample of well-demarcated
brain metastasis. Middle row: example of vascular co-option (patient 13, melanoma, Supplemental Table S1): (Ba) H&E slide
(magnification × 1.25); (Bb) CD34 immunohistochemistry of vascular co-option (magnification × 400); (Bc) macroscopic sample of brain
metastasis growing via vascular co-option; (Bd) MRI contrast-enhanced T1-weighted sequence sample of brain metastasis growing via
vascular co-option. Bottom row: example of diffuse invasion (patient 2, SCLC, Supplemental Table S1): (Ca) H&E of brain metastasis
(magnification × 1.25); (Cb) CD18 cytokeratin staining showing diffusely infiltrating tumor cells; (Cc) macroscopic sample of diffuse
infiltrating brain metastasis; (Cd) MRI contrast-enhanced T1-weighted sequence sample of diffuse infiltrating brain metastasis. Color figures
available from authors upon request.
Table 3. Concordance between first, second, and third brain metastases
First Brain Metastasis(n 5 57)
Well-demarcated(n 5 29)
VascularCo-option(n 5 10)
DiffuseInfiltration(n 5 18)
Chi-squareTest
n % n % n %
Second brain metastasis (n ¼ 30)
Well-demarcated 14 100 0 0 0 0
Vascular co-option 1 17 5 80 0 0 P , .001
Diffuse infiltration 0 0 1 10 9 90
Third brain metastasis (n ¼ 10)
Well-demarcated 3 60 1 20 1 20
Vascular co-option 0 0 3 100 0 0 P ¼ .023
Diffuse infiltration 0 0 0 0 2 100
Berghoff et al.: Invasion patterns in brain metastases of solid cancers
NEURO-ONCOLOGY 5
(52.6%) specimens, immunoreactivity foravb3 of the an-giogenic tumor vessels was observed, and in 29/57(50.9%) specimens, angiogenic vessels in the peritumoralarea showed specific immunoreactivity for avb3. Specificimmunoreactivity for the b3 subunit was observed in an-giogenic tumor vessels of 46/57 (80.7%) specimens andin angiogenic vessels in the peritumoral area of 45/57(78.9%) specimens (Fig. 3). The expression detected fortheavb3 complex was generally lower than for theb3 cy-toplasmic domain. Theb3 chain is on 2 integrin complex-es, avb3 and glycoprotein IIbIIIa (the platelet fibrinogenreceptor). Tissue localization suggested that the stainingof b3 was not due to platelet deposits or aggregates. Theavb3 antibody used (EM22703) preferentially binds par-ticular ligated conformation of avb3, while thecytoplasmic-b3 antibody (EM00212) does not discrimi-nate.18 This may explain the difference in stainingresults between these antibodies.
Fibrous tumoral stroma was observed in 32/57(56.1%) specimens and showed expression of the avsubunit (32/32, 100%), avb3 (2/32, 6.3%), avb5(28/32, 87.5%), and avb6 (6/32, 18.8%).
Relative overexpression of av integrins at the invasionfront was not consistently found, but only in some speci-mens (av subunit: 8/57, 14.0%; avb5: 8/57, 14.0%;avb6: 8/57, 14.0%).
Correlation with invasion patterns.—Median H-score ofavb6 was significantly higher in the well-demarcatedgroup (median 90, range 0–300) than in the vascular
co-option group (median 0, range 0–120) and thediffuse infiltration group (median 30, range 0–120;P ¼ .033, Kruskal–Wallis test). No correlation of inva-sion pattern and median H-score of av subunit, avb3,avb5, avb8, or b3 subunit was observed.
Correlation with therapy.—Brain metastases previouslytreatedwithSRS presentedmore frequentlywithavb5ex-pression in the tumor cells (6/7) than did specimenswithout prior SRS (21/49, 42.9%; P ¼ .034, chi-squaretest). Furthermore, the median avb5 H-score was signifi-cantly higher in brain metastases with prior SRS (60 vs 0;P¼ .05, Mann–Whitney U-test). No correlation betweenSRS treatments and av subunit, avb3, avb6, avb8, or b3subunit expression was observed. Prior WBRT or chemo-therapy did not show a significant correlation with ex-pression of any of the integrin subunits investigated inthis study.
Cadherin Expression
Of the tumor specimens studied, 42/57 (73.7%) showedexpression of E cadherin, 10/57 (17.5%) showed expres-sion of N cadherin, and 6/57 (10.5%) showed expressionof both cadherins. No significant correlation of medianH-score of E cadherin or N cadherin and invasionpattern or primary tumor types was observed. Nine of57 (15.8%) specimens showed increased E cadherinexpression at the invasion front. Three of 57 (5.3%)
Fig. 2. Integrin expression patterns: (A) av subunit expression
(patient 5, NSCLC, Supplemental Table S1); (B) avb5 expression
with accentuation around a vessel (patient 5, NSCLC, Supplemental
Table S1); (C) avb5 expression in a brain metastasis growing via
vascular co-option (patient 13, melanoma, Supplemental Table S1);
(D) avb6 expression with accentuation around necrosis, the stars at
upper left and lower right mark the necrosis (patient 5, NSCLC,
Supplemental Table S1). Color figures available from authors upon
request.
Fig.3. Integrinexpression invascular structures: (A)avb3expressionon
tumor vessel, arrow marks a vessel in the peritumoral area withoutavb3
expression (patient 5, NSCLC, Supplemental Table S1); (B) avb3
expression in glomeruloid-like vessels of the peritumoral area, the star
at lower right marks the tumor tissue, the cross marks the surrounding
cerebellum (patient 8, SCLC, Supplemental Table S1); (C) avb3
expression in a vessel with vascular co-option (patient 13, melanoma,
Supplemental Table S1); (D) CD34 immunohistochemistry of the case
shown in (B), illustrating the peritumoral sprouting vessels (patient 8,
SCLC, Supplemental Table S1). Color figures available from authors
upon request.
Berghoff et al.: Invasion patterns in brain metastases of solid cancers
6 NEURO-ONCOLOGY
specimens showed overlapping increased expression atthe invasion front of E cadherin and av, 2/57 (3.5%)showed overlapping expression with avb5, and 1/57(1.8%) specimen showed overlapping expression withavb6 at the invasion front. No cadherin expression wasobserved in the tumor stroma or vascular structures.
Discussion
Brain metastases are an increasing challenge inoncologicalpractice, as survival in many types of solid cancers is in-creased by novel treatment strategies. The dominant treat-ment strategies for brain metastases are local and includesurgery and radiosurgery. The benefit from local treat-ments is likely to be heavily affected by the degreeto which macroscopically focal disease is truly focal on amicroscopic level. Accordingly, the brain metastasis/brain interface may assume major prognostic significance.
Here, we delineate 3 distinct invasion patterns of brainmetastases: well-demarcated growth, vascular co-option,and diffuse infiltration. We found a high fraction of casesshowing invasive growth via vascular co-option (18%) orsingle-cell infiltration (32%). These surprising findingschallenge the general notion that brain metastases pre-dominantly grow in an expansive and well-delineatedfashion, but they are in good agreement with previousresults from experimental studies, smaller and less com-prehensive investigations on human tissue samples, andclinical observations.
In half of our cases, we observed expansive growth ofan outwardly extending tumor mass within the brain pa-renchyma. Expression levels of avb6 were significantlyhigher in this group of well-demarcated tumors. Integrinavb6 is not expressed in healthy adult epithelia but isupregulated in cancer and has been shown to modulate in-vasion and inhibit apoptosis.23 However, the exact role ofavb6 in cancer pathobiology and in particular in brainmetastases remains to be determined.
The vascular basement membrane may act as aguiding track for perivascular growth of cell collectives.Our results indicate that this invasion behavior is notonly present in mesenchymal and epithelial tissuesbut also occurs in the distinct microenvironment of theCNS. In line with previous studies, we observed vascularco-option most commonly in melanoma brain metasta-ses; however, we found it also in other tumor types,such as NSCLC adenocarcinoma.24–26
Single-cell infiltration into the brain parenchyma ofbrain-metastatic tumor cells has previously been reportedto be characteristic for SCLC.7 Our data show that this in-vasion pattern is also not uncommon in brain metastasesof other tumor types, including NSCLC adenocarcino-ma/squamous cell carcinoma, breast cancer, and melano-ma. The high fraction of brain metastasis cases showinginfiltrative growth has implications for local therapyoptions and highlights the need for including a safetymargin beyond the neuroradiologically visible tumorborders.6 In our study, depth of invasion into the CNS pa-renchyma from the main tumor mass reached up to450 mm. Of note, SRS uses no margins for treatment,
but at 0.4 mm from the prescription isodose line, nearlya full dose is delivered, and therefore the magnitude of in-vasion has no clear consequence on SRS practice. The se-lection of patients in need of an extended local treatmentapproach is challenging, as the current neuroradiologicaltechniques cannot precisely visualize the invasion dis-tance of a given tumor. However, we previously demon-strated that the extent of peritumoral brain edema mightfunction as a surrogate marker for infiltrative tumorgrowth, as little brain edema was significantly morecommon in infiltrative brain metastases and correlatedwith impairedpatient survival times.8 Furtherprospectivestudies need to address the prognostic implications ofbrain metastasis invasion patterns in more detail.
We did not observe a statistically significant correla-tion of treatment modality with invasion pattern in ourcohort. However, a higher proportion of patients in thediffuse infiltration group had received prior radiation orchemotherapy. As our sample size is not adequate forfirm statistical conclusions, we cannot exclude thatradio- or chemotherapy may select for or produce tumorcells with a higher infiltrative potential, similarly tosome observations in primary tumors and gliomas.27
Interestingly, brain metastasis lesions previously treatedwith SRS showed higher expression of avb5, a findingthat is well in line with previous reports showing thatthis molecule is essential for tumor growth in preirradi-ated stroma.28 Further, we observed a high consistencyof invasion behavior between the growth patterns of dif-ferent brain metastases in individual patients. This againmay indicate that intrinsic molecular features of metasta-ses originating from a given primary tumor correlate withcertain invasion patterns.
Our resultshave to be interpretedwith caution becausethe small sample sizes often do not allow firm statisticalconclusions. Herein, we concentrated on the descriptivepresentation of our results. However, it has to be takeninto account that autopsy samples of brain metastasesare very rare, and our series displays a rather largecohort compared with previously published studies onautopsy specimens.6,7
We noted prominent expression of av integrins inmany brain metastasis cases. This underscores the impor-tant function of this class of molecules in metastaticcancer. Currently, several integrin inhibitors are underclinical development, and promising activity wasshown in some of the most frequent primary tumors ofbrain metastases such as NSCLC and melanoma.29–31
Interestingly, the anti–av-integrin antibody intetumu-mab reduced brain metastasis outgrowth in mice afterintracarotid infusion of brain-seeking human epidermalgrowth factor receptor 2–positive breast cancer cells.32
Thus, clinical trials specifically investigating the potentialof integrin inhibitors for prophylaxis and treatment ofbrain metastases seem warranted.
Supplementary Material
Supplementary material is available online at Neuro-Oncology (http://neuro-oncology.oxfordjournals.org/).
Berghoff et al.: Invasion patterns in brain metastases of solid cancers
NEURO-ONCOLOGY 7
Acknowledgments
We thank Irene Leisser and Gerda Ricken for excellenttechnical assistance with preparation of tissue specimens.Further we thank Prof Dr Harald Heinzl (Center forMedical Statistics, Informatics, and Intelligent Systems,Medical University of Vienna) for the supervision andadvice with statistical analyses. This study was performedwithin the PhD thesis project of Anna Sophie Berghoff inthe PhD program “Clinical Neuroscience (CLINS)” at theMedical University Vienna.
Funding
The costs for this project were covered by the researchbudget of the Medical University of Vienna and theUniversity of Tubingen.
Conflict of interest statement. S.L.G. is an employee atMerck-Serono and has a patent application referring tothe anti-integrin antibodies used here. M.W. has receivedresearch support and honoraria for lectures and service onits advisory board from Merck-Serono. All other authorsdeclare no conflict of interest.
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Berghoff et al.: Invasion patterns in brain metastases of solid cancers
NEURO-ONCOLOGY 9
! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !
! &)!
6.6 Characterization of the inflammatory response to solid cancer metastases in the human brain.
Interlude The interaction of the immune system and cancer came into focus of oncology
research as immune checkpoint inhibitors, intensifying anti-tumour T-cell response,
showed promising clinical responses [115]. Although, the importance of the
interaction with the immune system was shown for several pathologies like multiple
sclerosis, infection or neurodegeneration as well as for primary brain tumours, only
limited insight on the interaction with the immune systems exists for BM [137, 138].
Therefore, we aimed to investigate the interaction of the innate immune system,
namely the brain resident microglia, and BM in the established autopsy cohort. In the
paper “Characterization of the inflammatory response to solid cancer metastases in
the human brain” we observed a dense infiltration with microglia/macrophages at the
boarder between BM and surrounding brain parenchyma, while within the tumour
tissue only sparse infiltration could be observed [139]. Melanoma BM presented with
significantly less peritumoural microglia accumulation compared to NSCLC BM. As
microglia function involves phagocytic activity, cytotoxic activity via nitric oxide radical
release and activation of adaptive immune response, we further investigated the
status of microglia activation. Here we observed high expression of markers
associated with phagocytic function, while markers of nitric oxide radical release
showed only marginal expression. Expression of major histocompatibility antigen
class I, which is needed for antigen presentation in order to activate the adaptive
immune response, was frequently presented. However, only sparse infiltration with
cells of the adaptive immune response, namely B- and T cells, was observed. Our
findings indicate that the microenvironment around BM seems to be ready to alter an
immune defence but the BM tumour cells might induce immunosuppressive factors
preventing activation of an adaptive immune response.
RESEARCH PAPER
Characterization of the inflammatory response to solid cancermetastases in the human brain
Anna Sophie Berghoff • Hans Lassmann •
Matthias Preusser • Romana Hoftberger
Received: 6 May 2012 / Accepted: 18 June 2012 / Published online: 1 July 2012! Springer Science+Business Media B.V. 2012
Abstract New immunomodulatory agents showed prom-ising activity in brain metastases (BM). However, little is
known about the inflammatory response in BM. New
insights are needed to further guide the development oftreatment strategies. We investigated 17 human autoptic
tissue specimens of BM from breast cancer (n = 3), non-
small cell lung cancer (NSCLC; n = 5), small cell lungcancer (n = 3) and melanoma (n = 6). Immunohistochem-
ical staining for a comprehensive panel of 21 inflammation-
associated markers was performed. Results were quantifiedby manual counting of the various cell populations in three
areas of 0.5 mm2 (intratumoral, peritumoral, control region).
Profound microglia activation with marked peritumoralaccumulation and some intratumoral infiltration of HLA-
DR-positive microglia/macrophages was found. A high
proportion of these cells showed strong immunoreactivityfor phagocytosis associated markers and MHC class 1, while
a smaller subgroup of cells expressed molecules involved in
radical production. Only few B- and T-lymphocytes wereobserved in and around BM. The number of CD8-positive
T-cells was not correlated to MHC class 1 expression ontumor cells and only a fraction of T-cells showed Granzym B
expression. Melanoma BM had significantly less accumu-
lation of peritumoral microglia than NSCLC BM. Theinflammatory pattern was independent from treatment of
patients with glucocorticoids or radiation. The inflammatory
reaction to BM is mainly characterized by activation ofmicroglia/macrophages and shows pronounced upregulation
of markers involved in phagocytosis, but seem to be insuf-
ficient in activating adaptive immunity. Treatment strategiesaimed at activating specific immunity may potentiate
immune attack on tumor cells.
Keywords Brain metastases ! Microglia !Immune system ! Macrophages ! Lymphocytes !Adaptive immune system ! Innate immune system
AbbreviationsBM Brain metastasesBRAF v-RAF murine sarcoma viral oncogene
homolog B1
CTL4 Anti cytotoxic T lymphocyte associatedantigen 4
NSCLC Non-small cell lung cancer
EGFR Epithelial growth factor receptorHER2 In human epidermal growth factor receptor
2
CNS Central nervous systemSCLC Small cell lung cancer
MHC II Major histocompatibility antigen class II
MHC I Major histocompatibility antigen class IWBRT Whole-brain radiation therapy
NO Nitric oxide
APM Antigen-processing machingeryTGF-beta Transforming growth factor beta
A. S. Berghoff ! R. HoftbergerInstitute of Neurology, Medical University of Vienna,Waehringer Guertel 18-20, Vienna, Austria
A. S. Berghoff ! M. PreusserComprehensive Cancer Center, CNS Unit, Medical Universityof Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria
H. LassmannCenter for Brain Research, Medical University of Vienna,Spitalgasse 4, Vienna, Austria
M. Preusser (&)Department of Medicine I, Medical University of Vienna,Waehringer Guertel 18-20, 1090 Vienna, Austriae-mail: [email protected]
123
Clin Exp Metastasis (2013) 30:69–81
DOI 10.1007/s10585-012-9510-4
GFAP Glial fibrillary acidic proteinIBA-1 Ionized calcium binding adaptor molecule 1
AIF-1 Allograft inflammatory factor 1
SIGLEC-11 Sialic acid-binding Ig-like lectin 11HMGB1 High-mobility group box 1
iNOS Inducible nitric oxide synthase
NCF-1 Neutrophil cytosolic factor 1
Introduction
Brain metastases (BM) are a severe and devastating com-
plication of solid tumors, occurring in up to 25–40 %of patients with metastatic cancer [1–3]. The prognosis of
patients with BM is poor with median survival of
approximately 2–7 months [4]. However, some patientswith favorable prognostic factors, like primary histology of
breast cancer with expression of human epidermal growth
factor receptor 2 (HER2) and estrogen receptor, age under60 years and a Karnofsky performance status over 90 at
first diagnosis of BM, have median overall survival times
of up to 25.3 months [5]. Currently, therapy relies mainlyon surgery, radiosurgery and radiotherapy. Most systemic
therapies like cytotoxic and novel targeted agents have
shown only little or no efficacy against BM [6]. Reasonsfor this may include inadequate drug penetration through
the blood–brain barrier and resistance mechanisms [3, 7].
However, recently novel drugs have shown promisingactivity in specific subsets of BM, such as inhibitors of
v-RAF murine sarcoma viral oncogene homolog B1
(BRAF) in BRAF V600E mutated melanoma, the immu-nomodulatory anti cytotoxic T lymphocyte associated
antigen 4 (CTL4) antibody ipilimumab in melanoma, epi-
thelial growth factor receptor inhibitors in non-small celllung cancer (NSCLC) and lapatinib in HER2 positive
breast cancer [8, 9]. A better understanding of the patho-
biology of BM is likely to support the development ofadditional active agents for patients with BM.
The immune system plays an important role in the
pathophysiology of many central nervous system (CNS)disorders including multiple sclerosis, infection, neurode-
generation, and also neoplastic disease [10–13]. However,
while many research groups have studied the inflammatoryresponse to primary brain tumors, only very few data on the
role of the immune system in BM are available [14–19]. In
this study we aimed at characterizing the inflammatoryresponse to BM in the human brain and performed an
immunohistochemical study utilizing autoptic tissue spec-
imens of 17 BM patients. Brain tissue is usually not col-lected at autopsy of BM patients, but we were able to
compile this series from a large and well annotated bio-
bank at our institution.
Subjects and methods
Patients and materials
All patients with histologically proven BM of breast can-cer, SCLC, NSCLC or melanoma who underwent brain
autopsy between 1993 and 2011 were identified from the
bio-bank of the Medical University of Vienna. Clinical anddemographic data were retrieved by chart review. Of each
patient we selected one representative tissue specimen
which included viable BM and surrounding brain tissue. Ofeach patient one BM tissue block was available, because
for routine diagnostic purposes tissue material of one rep-
resentative BM lesion was sampled. All tissue samplesincluded in this study have been formalin fixed and par-
affin-embedded during routine diagnostic work-up. This
study was approved by the ethics committee of the MedicalUniversity Vienna.
Immunohistochemistry
Tissue blocks were cut into 3–5 lm slices with a micro-
tome. A comprehensive immunohistochemical stainingpanel was used to characterize microglia and lymphocyte
response to BM. Table 1 summarizes markers and immu-
nostaining protocols.
Quantitative evaluation
Regions of interest were defined as follows: BM lesion:
within the vital tumor tissue, peritumoral region: braintissue adjacent to the BM; control region: brain tissue at
least 0.5 mm from the BM border. The region of highest
density of microglia in the peritumoral region was identi-fied in the staining for HLA-DR in each case. Within this
region the density of immunoreactive cells was counted in
eight high power fields at a magnification of 9400(0.5 mm2). The same area was counted in each staining of
a case. Within the control region and within the BM the
density of immunoreactive cells was counted as well ineight high power fields at a magnification of 9400
(0.5 mm2). Expression of a marker in the tumor cells was
evaluated by semi quantitative methods and grouped assparse (0–10 % of the tumor cells), moderate (11–50 % of
the tumor cells) and strong (over 50 % of the tumor cells)
staining.
Statistical evaluation
Statistical evaluation was performed using SPSS 17.0 sta-
tistical software system (SPSS, Chicago, IL). To compare
differences between two groups Mann–Whitney U test wasperformed. P values \0.05 were regarded as significant.
70 Clin Exp Metastasis (2013) 30:69–81
123
Tab
le1
Lis
tan
dch
arac
teri
zati
on
of
use
dm
ark
ers
and
imm
un
oh
isto
chem
ical
stai
nin
gp
roto
cols
Mar
ker
Fu
nct
ion
An
tib
od
yD
ilu
tio
nA
nti
gen
retr
iev
al
1.
GF
AP
Inte
rmed
iate
fila
men
tp
rote
in,
incr
ease
of
exp
ress
ion
inre
spo
nse
toa
var
iety
of
neu
rolo
gic
ald
iso
rder
s(r
eact
ive
gli
osi
s)[4
4]
Rab
bit
po
lycl
on
alan
ti-g
lial
fib
rill
ary
acid
icp
rote
in/Z
03
34
Dak
oC
yto
mat
ion
1:3
,00
0P
rote
inas
eK
read
yto
use
Dak
oC
yto
mat
ion
2.
HL
AA
BC
/MH
CI
An
tig
enp
rese
nta
tio
nfo
rT
-cel
ls;
exp
ress
ion
ises
sen
tial
for
the
pro
pag
atio
no
fC
D8?
T-c
ell
med
iate
din
flam
mat
ion
[45]
Sta
met
al.
[46]
1:2
,00
0T
ris–
ED
TA
bu
ffer
(pH
8.5
)
3.
HL
A-D
R/M
HC
IIM
ajo
rh
isto
com
pat
ibil
ity
anti
gen
clas
sII
exp
ress
edo
nm
icro
gli
ace
lls,
nec
essa
ryfo
ran
tig
enre
cog
nit
ion
by
CD
4?
T-c
ells
[47]
Mo
use
mo
no
clo
nal
anti
-hu
man
HL
A-D
R,
DQ
,D
Pan
tig
en/M
07
75
Dak
oC
yto
mat
ion
1:4
00
Fle
xT
RS
low
(pH
6)
4.
CD
68
Sca
ven
ger
rece
pto
rin
vo
lved
inp
hag
ocy
tosi
s[4
8]
Mo
no
clo
nal
mo
use
anti
-hu
man
CD
68
/cl
on
eK
P1
/M0
81
4D
ako
Cy
tom
atio
n1
:5,0
00
Fle
xT
RS
low
(pH
6)
5.
CD
16
3S
cav
eng
erre
cep
tor
inv
olv
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Clin Exp Metastasis (2013) 30:69–81 71
123
Tab
le1
con
tin
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Mar
ker
Fu
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An
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72 Clin Exp Metastasis (2013) 30:69–81
123
Spearman correlation was used to identify interdependence
of variables.
Results
Patients’ characteristics
Autoptic brain tissue specimens with embedded BM of 17
cancer patients were available for this analysis (histologicaldiagnoses of the primary tumors: 6 melanoma, 3 SCLC, 5
NSCLC, 3 breast cancer). The median age at death was
56 years (range 35–83 years) and the study cohort includednine male and eight female patients. 7 patients had single
and 10 patients multiple brain (median 2, range 1–5)
metastases. Five patients were treated with whole-brainradiation therapy (WBRT), chemotherapy or a combination
of WBRT and chemotherapy for BM. Time from the last
treatment (WBRT and/or chemotherapy) till death was atleast 1 month (range 1–7 months). Four patients received
glucocorticoid therapy within 1 week before death. All
other patients had received no specific treatment for BM as
their performance status was too poor at the time of diag-nosis of BM or first diagnosis of BM was at autopsy.
Table 2 lists further demographic and clinical data.
Tissue analysis
In all cases we histologically found solid tumor massesembedded in CNS tissue. In 16/17 cases the tumor for-
mations were well-delineated from the surrounding CNStissue with a clear-cut border between tumor and CNS
tissue. Only sparse infiltrating single tumor cells or small
tumor cell nests in the brain parenchyma were observed inthese cases. One case of SCLC showed rather diffuse and
infiltrating growth pattern with a less demarcated border,
corresponding to the previously described ‘‘pseudoglio-matous’’ growth pattern [20].
Lymphocyte and plasma cell infiltration
We observed only very few B and T-cells in and around
BM (Fig. 1). Within the BM lesion only few scattered cellswere observed with a slightly higher density in perivascular
areas. The majority of small round inflammatory cells were
identified as T-cells by immunohistochemical methods.More CD8 and CD3 positive cells were observed compared
with CD20, CD79a and CD4. Density of CD8 positive
T-cell infiltration did not differ between primary tumortypes (P = 0.844; Kruskal–Wallis test) (Fig. 1). Among
the T-cells only a small proportion showed expression of
Granzym B. A mean of 4.7 (range 0–27) Granzym Bpositive cells per 0.5 mm2 were observed within BM
compared to 31.3 (range 1–140) CD8 positive cells per
0.5 mm2 (Spearman’s correlation coefficient 0.4; P =0.083). We did not observe unequivocal morphological
signs of Granzym B release specifically directed at tumor
cells.T-cell recognize their specific antigen only, when pre-
sented in association with major histocompatibility (MHC)
molecules. Significantly more microglial cells/macro-phages in the peritumoral region stained positive for MHC
class I (required for antigen recognition by CD8? T-cells)
compared to the control region (P = 0.004; paired t test)(Table 2). Furthermore, 14/17 (87.6 %) BM lesions did
demonstrate positive staining for MHC I of the tumor cells
[sparse staining: 3/17 (18.8 %) cases; moderate staining:2/17 (12.5 %) cases; strong staining: 9/17 (56.3 %) cases].
In contrast, only 3/17 (20.0 %) BM lesions showed positive
staining for HLA-DR/MHC class II (antigen presentationto CD4? T-cells) within the tumor cells [moderate: 2/17
(13.3 %) cases; strong: 1/17 (6.7 %) cases]. The number of
CD8-positive T-cells did not correlate with MHC Iexpression on tumor cells (P = 0.873; Kruskal–Wallis
Table 2 Patients’ characteristics
Characteristics Patients (n = 17)
n %
Male 9 52.9
Female 8 47.1
Median age, years (range) 56 (35–83)
Primary histology
Melanoma 6 35.3
SCLC 3 17.6
NSCLC 5 29.4
Breast cancer 3 17.6
Treatment for BM
WBRT 3 17.6
Chemotherapy 1 5.9
WBRT and chemotherapy 1 5.9
Glucocorticoid therapy
Yes 4 23.5
No 13 76.5
Extracranial metastases
Yes 13 23.5
No 4 76.5
Location of BM
Supratentorial 12 70.6
Infratentorial 5 29.4
First diagnosis of BM at autopsy
Yes 5 28.4
No 12 71.6
Median survival from diagnosisof BM, months (range)
1 (0–14)
Clin Exp Metastasis (2013) 30:69–81 73
123
Fig. 1 Lymphocyte infiltration of BM. a CD3 immunostaining (mag-nification 910), b CD 8 immunostaining (magnification 920), c CD79aimmunostaining (magnification 920), d CD20 immunostaining
(magnification 920), e density of different lymphocytes per 0.5 mm2
within BM, f T-cells per 0.5 mm2 within BM in different primary tumorhistologies
74 Clin Exp Metastasis (2013) 30:69–81
123
test) nor with MHC I expression on microglia cells/mac-
rophages in the peritumoral region (Spearman’s correlationcoefficient -0.1; P = 0.660).
Expression of markers related to microglia/macrophageactivation
Using immunohistochemistry for HLA-DR and IBA-1 weobserved a pronounced accumulation of densely packed
microglial cells/macrophages in the peritumoral region andaround areas of necrosis in all cases (Fig. 2; Table 3).
Viable tumor tissue areas and the surrounding normal
appearing CNS tissue contained only scattered microglialcells (Fig. 2).
To characterize marker of microglia/macrophage acti-
vation, immunohistochemical stainings for Siglec,HMGB1, AIF-1, and GLUT 5 were performed. Compared
to the other microglia/macrophage antigens, significantly
more cells in the peritumoral region expressed HMGB1(P \ 0.05; paired t test). HMGB1 staining was further
observed in neurons and in tumor cells. 15/17 (88.2 %) BM
lesions showed a strong, homogenous positive staining forHMGB1. HMGB1 was observed in the extracellular space
or around necrotic cells in 4/17 (23.5 %) BM lesions.
In further characterization of the microglia/macrophageinfiltrates, the majority of the cells in the peritumoral
‘‘microglial wall’’ were identified as macrophages with
broad, foamy cytoplasm and strong immunoreactivity forCD68 and CD163 (Fig. 2). A significantly higher propor-
tion of CD163-positive macrophages were identified within
the peritumoral microglia wall than in the control region(P \ 0.001; paired t test) (Table 2). The density of mac-
rophages in the peritumoral region was not correlated to the
presence of necrosis (P = 0.840; Mann–Whitney U test).To analyse oxidative burst activation in microglia/
macrophages, immunohistochemistry for iNOS, p22phox,
NCF-1, NOX-1 and NOXO-1 was performed. Amongthese, p22phox showed moderate expression, while all
other factors were only marginally expressed. No correla-
tion of iNOS expression and the presence of necrosis wasobserved (P = 0.521; Mann–Whitney U test). Overall, in
comparison to the cells with positive staining for the
macrophages markers CD163 and CD68, relatively fewcells showed positive staining for the enzymes involved in
oxygen and nitric oxide radical production (Table 2).
iNOS expression showed only marginal correlation withNADPH oxidase marker expression. The strongest corre-
lation was observed for iNOS and NOX 1 (Spearman’s
correlation coefficient 0.7; P = 0.006) followed by iNOSand p22phox (Spearman’s correlation coefficient 0.6;
P = 0.021) and iNOS and NCF1 (Spearman’s correlation
coefficient -0.6; P = 0.007), respectively. No correlation
was observed for iNOS and NOXO-1 (Spearman’s corre-
lation coefficient 0.1; P = 0.749).The density of the peritumoral microglia wall differed
between primary tumor types. Patients with melanoma had
a significantly less dense peritumoral microglia wall with amedian of 81.00 (range 44–135) HLA-DR positive cells
per 0.5 mm2 compared to 147 (range 131–297) HLA-DR
positive cells per 0.5 mm2 in patients with NSCLC(P = 0.010, Mann–Whitney U test) (Fig. 3). No significant
difference in the density of the microglia wall was foundbetween the other tumor types.
Interestingly, microglia density and expression of
microglia activation markers was not significantly influ-enced by treatment modality, anatomic brain region or
presence of necrosis in our small series (Fig. 3).
Astrocytes and reactive gliosis
Reactive gliosis, consisting of GFAP-positive astrocyteswith distended cytoplasm and radially arranged processes,
were observed in the peritumoral region. Compared to the
control region more reactive astrocytes were identified inthe peritumoral region (Table 2).
Discussion
The immune systems attracted rising interest in neuroon-cology as several new approaches in systemic therapy, like
dendritic cell vaccination therapy or the anti-CTL4 anti-
body ipilimumab, are under investigation and have shownactivity in clinical trials for primary and secondary brain
tumors [9, 21–23]. However, so far only little is known
about the immunologic response within BM. In the presentstudy, we systematically characterized the inflammatory
infiltrates in and around BM in human autopsy tissue
samples. Our data show that the inflammatory reaction toBM is mainly characterized by activation of microglia/
macrophages and shows pronounced upregulation of
markers involved in phagocytosis, while the infiltration byT- and B-lymphocytes is very low.
We observed that microglia/macrophages produce dense
infiltration in the peritumoral area of BM, whereas intratu-moral areas contained comparatively low numbers of
inflammatory cells. Interestingly, the inflammatory pattern
was independent from tumor localization and treatment withglucocorticoids or radiation in our small patient series.
However, we found evidence for differential inflammatory
response between tumor types. In our series, melanoma BMhad significantly less peritumoral microglia accumulation
than NSCLC BM. This finding may be related to the common
embryological origin of glial cells and melanocytes.
Clin Exp Metastasis (2013) 30:69–81 75
123
Fig. 2 Microglia/macrophage activation. a HLA-DR immunostainingin peritumoral region (magnification 92.5), b HLA-DR immunostain-ing in peritumoral region (magnification 920), c iNOS immunostainingin peritumoral region (magnification 920), d CD163 immunostaining
in peritumoral region (magnification 920), e CD163 immunostainingwithin BM (magnification 910), f CD68 immunostaining within BM(magnification 920)
76 Clin Exp Metastasis (2013) 30:69–81
123
Microglia cells are the main effector cells of the CNS
immune system and their function involves innate as well
as adaptive immune responses [11, 12]. Microglia cellsmay rapidly enlarge and differentiate to macrophages,
although macrophages in the CNS may also derive from
blood monocytes [12]. Microglia cells produce a highnumber of signaling molecules including cytokines, pro-
teases and prostanoids upon activation. In addition, acti-vated microglia can induce cytotoxic cell death throughout
production of nitric oxide (NO) and superoxide, which are
products of the enzymes inducible nitric oxide synthaseand NADPH oxidase [24]. Data on experimental metasta-
ses in murine brain suggest that activated microglia have
tumor cytotoxic effects, although some publications havealso indicated pro-neoplastic microglia effects in glioma
[25, 26]. So far research on microglia cells and macrophage
infiltration in BM from human tissue are sparse and asystematic investigation of microglia activation pattern in
different types of solid cancer metastases are lacking [14,
15]. For the better understanding of inflammatory mecha-nisms and their effects on metastatic tumor cells we ana-
lyzed microglia/macrophage activation with a broad panel
of established markers in human BM tissue by immuno-histochemical methods.
Microglia cells and macrophages are known to release
oxygen and nitric oxide radicals, which have been shown toplay a major role in neurodegenerative diseases, CNS
injury and especially in multiple sclerosis [27, 28]. A
previous in vitro study postulated that microglial cells exerttumoricidal activity against brain-metastatic cells through
NO release [26]. In contrast, another study found evidence
for deficiency in the NO release of microglia cells around
surgery specimen of human BM [14]. In our present studywe investigated a broad panel of markers involved in the
induction of oxidative stress, including iNOS, NOX1,
NOXO1, p22phox and NCF-1 [27]. Among these, onlyp22phox showed moderate expression, while all other
factors were only marginally expressed. Since oxygenradical production requires fully assembled NADPH oxi-
dase complexes, the low expression of some of the com-
ponents (NCF-1, NOXO1) suggests that very little activeenzyme is available [29]. However, we observed a corre-
lation of iNOS with markers of the NADPH oxidase. NO
reacts with oxygen radicals forming the highly cytotoxicperoxynitrite, which may thus result in at least some
NO-related tumoricidity. Interestingly, one study showed
that conditioned medium of brain-metastatic colon-carci-noma cells may inhibit NO production of endothelial cells,
thus indicating that tumor cells may have protective
mechanisms against NO-induced lysis [14, 30]. Takentogether, however, our data indicate that cytotoxic
microglia activation is minor in BM.
In contrast to the markers of radical production, markersassociated with phagocytotic activity, namely CD163 and
CD68, were consistently and prominently expressed in our
study. Our findings are in keeping with data from a pre-vious study, which also showed dense accumulation of
microglia cells and especially of CD163 and CD68 positive
macrophages at the border between BM and normal CNStissue in brain-metastatic lung adenocarcinoma [14, 31].
Table 3 Microglia activation (median number of immunoreactive cells/0.5 mm2 (range) in the peritumoral region, within BM lesion and in thecontrol region
Parameter Peritumoral region BM lesion Control region Spearman correlationperitumoral and controlregion
Spearman correlationperitumoral regionand BM lesion
HLA DR 131.00 (29–297) 37.00 (11–112) 47.00 (0–154) 0.6* -0.03
IBA-1 76.50 (3–172) 32.00 (1–240) 43.00 (7–106) 0.3 0.7*
CD163 74.50 (17–213) 32.00 (1–185) 9.00 (0–122) 0.5 0.7*
CD68 64.50 (4–205) 37.00 (8–109) 30.00 (9–90) 0.5 0.5
iNOS 25.00 (2–142) 9.00 (0–57) 12.00 (0–50) 0.3 0.3
p22phox 105.00 (22–268) 46.00 (0–216) 39.00 (17–98) 0.04 0.5
NCF-1 11.00 (0–55) 1.50 (0–30) 9.00 (0–59) 0.6 0.1
NOX-1 34.00 (5–145) 0 9.00 (0–108) 0.3 –
NOXO-1 14.00 (2–102) 0 11.00 (0–50) 0.9* –
Siglec 23.50 (7–94) 2.00 (0–34) 14.00 (0–43) 0.5* -0.1
HMGB1 82.50 (25–209) 0 84.00 (27–150) 0.6* –
AIF-1 40.00 (0–117) 13.00 (0–80) 13.00 (0–31) 0.7* 0.7*
GLUT 5 38.50 (4–115) 4 (0–22) 19.00 (2–38) 0.7* -0.1
HC-10 62.50 (6–141) 42.00 (17–107) 29.00 (1–113) 0.3 -0.5
GFAP 43.00 (15–117) 0 27.00 (6–48) 0.6 –
* P \ 0.05
Clin Exp Metastasis (2013) 30:69–81 77
123
Fig. 3 a Density of HLA-DR positive cells per 0.5 mm2 in theperitumoral region of different primary tumor histologies, b density ofHLA-DR positive cells per 0.5 mm2 in the peritumoral region insupratentorial and infratentorial location of BM, c density of HLA-DR positive cells per 0.5 mm2 in the peritumoral region in patientstreated with and without WBRT, d density of HLA-DR positive cells
per 0.5 mm2 in the peritumoral region in patients treated with andwithout chemotherapy, e density of HLA-DR positive cells per0.5 mm2 in the peritumoral region in patients treated with and withoutglucocorticoid therapy, f density of HLA-DR positive cells per0.5 mm2 in the peritumoral region in BM with and without necrosis
78 Clin Exp Metastasis (2013) 30:69–81
123
Previously, more CD68 positive macrophages were
observed in adenocarcinoma BM than in primitive neuro-ectodermal tumors or meningiomas [32]. However, only
little is known so far about the factors driving macrophage
infiltration in BM. We observed a high expression of thepotent macrophage-activating factor HMGB1 in microglia/
macrophages but also in the majority of vital tumor cells.
In addition HMGB1 was found in apoptotic tumor cells,necrotic tissue areas and in the extracellular spaces. Thus,
the release of HMGB1 from disintegrating tumor cells mayplay an important role in initiating or sustaining microglia/
macrophage recruitment to BM [33].
The adaptive immune system came into the focus ofcancer research as the density of tumor-infiltrating T-cells
were postulated to be associated with better survival in
various tumors [34–36]. Furthermore, new approaches insystemic therapy of cancer focus on the recruitment of
T-cells like the anti-CTL4 antibody ipilimumab in mela-
noma [37]. The healthy human brain contains almost nolymphocytes, but there is evidence for immune surveillance
of the normal human CNS by CD3(?)/CD8(?) lympho-
cytes, particularly in areas of relatively permissive blood–brain barrier composition [38, 39]. Some brain tumors such
as gangliogliomas are known to attract prominent lym-
phocytic infiltration. For the instance of glioblastomas, theamount of T-cell infiltration was shown to be associated
with survival of patients, who received vaccination with
dendritic cell immunotherapy [40]. Interestingly, we foundonly very few B- and T-lymphocytes in and around BM in
our patient series. Further, only a small proportion of
T-cells did demonstrate sings of cytotoxic activation. CD8-positive cytotoxic T-cells recognize their antigen via the
MHC class I molecule on the cell surface and subsequently
induce their cytotoxic action. Although we found variableamounts of MHC class I expression on tumor cells, this did
not correlate with the intratumoral number of CD8-positive
T-cells. Our findings may indicate that the sparse lympho-cytic infiltrates correspond mainly to secondarily recruited
T- and B-cells that are not antigen specific. BM cells may
produce immunosuppressive factors that inhibit antineo-plastic activity of the specific immune system, similar to the
situation in primary brain tumors [16, 18, 19, 41]. For
example, Mehlin et al. [42] presented data suggesting thatcoordinated downregulation or impaired upregulation of
certain components of the HLA class I antigen-processing
machingery may allow astrocytoma cells to evade the hosts’immune response, even if HLA class I antigen surface
expression is not altered. The expression of MHC molecules
on microglia and tumor cells could in principle make adirect tumor killing by an antigen-specific immune response
possible. Thus, treatment strategies aimed at boosting the
response of the specific immune system against BM mayincrease therapeutic efficacy. Recent examples of such
approaches in brain tumors include vaccination strategies
and transforming growth factor beta antisense therapy forglioblastoma and the anti-CTL4 antibody ipilimumab in
(brain-) metastatic melanoma [21, 22, 43]. Particularly,
immunological intervention using the immunomodulatoryanti-CTLA4 antibody ipilimumab has recently shown
clinically meaningful activity in melanoma patients with
BM [9]. Our findings in fact very nicely complement thesedata, as we show that an unspecific inflammatory response
is in principle activated in the brain by cancer metastasesbut adaptive immunity is only inadequately elicited. Taken
together, the data clearly suggest that activation of specific
immunity by immunological interventions in fact provideeffective therapeutic potential.
In conclusion the immunological environment in BM
seems to be ready to alter an immune defense but thespecific stimulus for activation might be missing or might
not overcome the anti-inflammatory factors produced by
the tumor cells. Further studies are needed to clarifywhether approaches aimed at activating specific immunity
are sufficient to induce significant antineoplastic immune
response in brain tumors including BM.
Acknowledgments We thank Irene Leisser and Marianne Leisserfor technical assistance with preparation of tissue specimens. Thisstudy was performed within the PhD thesis project of Anna SophieBerghoff in the PhD program ‘‘Clinical Neuroscience (CLINS)’’ atthe Medical University Vienna.
Conflict of interest The authors declare that they have no conflictof interest.
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Clin Exp Metastasis (2013) 30:69–81 81
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7 Discussion 7.1 General discussion
In this thesis, clinical and pathological characteristic were examined in a unique and
large cohort of patients with BM. We could identify clinical characteristics in the
disease course of patients with breast cancer BM, evaluate tissue based
characteristics as well as radiological characteristics influencing survival prognosis,
investigate the interaction of the innate immune system and BM and describe
different invasion patterns of BM. Our findings add valuable information on the
involved mechanisms of the brain metastatic cascade and might be used to further
guide the development of BM specific trials.
Patients with HER2 positive breast cancer and triple negative breast cancer were
shown to develop BM significantly earlier during their clinical course compared to
patients with ER positive breast cancer [123]. While the impact of the breast cancer
subtypes on overall survival, also upon the diagnosis of BM, is well reviewed, we
investigated to our best knowledge for the first time the brain metastasis free survival
according to the breast cancer subtype [19, 140]. We emphasized that preventive
strategies should be investigated in patients with HER2 positive and triple negative
breast cancer. Prophylactic cranial irradiation was discussed especially for patients
with triple negative or HER2 positive breast cancer [141, 142]. The CEREBEL
studies investigated the potential of lapatinib versus trastuzumab in order to prevent
BM as first side of progression. However, no significant difference between the two
HER2 directed systemic treatment approaches was observed, although the study did
not reach the pre-specified accrual goal [52]. Future studies should focus on the
value of new substances in the prevention of BM.
Brain only metastatic breast cancer was identified as distinct metastatic pattern and
clinically relevant subtype, as patients might experience long-term survival over 36
months [126]. So far the status of the extracranial disease is not included in the
diagnosis specific graded prognostic assessment of patients with BM from breast
cancer as it is based on the breast cancer subtype, age and Karnofsky performance
score [68]. However, the diagnosis specific graded prognostic assessment is based
on the clinical data of patients included in clinical trials of the Radiotherapy and
Oncology Group (RTOG). Therefore, the prognostic score might not truly resemble
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! ($!
the relevant prognostic factors in a real life cohort. Our observation emphasizes the
need to validate the established clinical prognostic scores in real life cohorts.
We identified high Ki67 proliferation index and high microvascular density as tissue
based prognostic factors in NSCLC BM [128]. While Ki67 proliferation index is a
known prognostic factor in primary NSCLC, the favourable prognostic impact of high
microvascular density in non small cell lung cancer BM is in contrast to the
prognostic impact in primary NSCLC [127, 143]. However, a previous study on
NSCLC lymph node metastases revealed that the prognostic implication of MVD
might change upon metastatic disease, as patients with high MVD in the lymph node
metastases presented with an improved survival prognosis compared to patients with
low MVD [144]. Therefore, neoangiogenesis as well as its prognostic impact might
change due to the changed microenvironment (“seed and soil”) [145]. We further
postulated a predictive value for the HIF 1 alpha index in patients receiving whole
brain radiation therapy after resection of NSCLC BM [128]. The value of whole brain
radiation therapy in NSCLC is currently discussed [63]. In a phase III study, no
impact on overall survival for addition of whole brain radiotherapy after neurosurgical
resection or radiosurgery of one to three BM was observed [78]. Regarding the side
effects of whole brain radiotherapy including neurocognitive impairment and the
impact on the quality of life, careful selection of patients profiting of the therapy is
needed [147]. The value of HIF 1 alpha index as a predictive marker for whole brain
radiotherapy should be investigated in prospective clinical trials.
Preoperative diffusion weighted imaging, which resembles mobility of water
molecules in the intercellular space, showed a significant correlation with survival
prognosis in patients with singular BM treated with neurosurgical resection as first
line treatment approach for newly diagnosed brain metastasis [148]. So far, only
clinical factors like number of BM, age, status of extracranial disease and Karnofsky
performance score are used for the estimation of the survival prognosis in patients
with BM [149]. However, radiological findings might add valuable additional
information as they can function as surrogate parameter of tissue characteristics.
Indeed, hyperintense diffusion weighted imaging showed correlation with high
extracellular fibrosis, measured by the density of reticulin fibers [132]. Importantly,
the reticulin fiber network is part of the collagen-rich tumour stroma, underscoring the
biological and prognostic importance of the tumour stroma and the involved
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! (%!
microenvironment [35, 150]. Accordingly, presence of a dense stromal matrix was
shown to be associated with impaired survival prognosis in frequent primary tumour
of BM like triple negative breast cancer [151, 152]. The prognostic value of
radiological finding should be investigated within prospective clinical trials.
We were able to characterize invasion patterns of BM in a unique large cohort of
autopsy specimens. Here, a well-demarcated border towards the surrounding brain
parenchyma was observed in approximately half of the investigated cases. Further,
we found a significant fraction of specimens presenting with infiltrative growth via
vascular co-option (18%) or gliomas like single-cell infiltration (32%) [136]. So far, the
general textbook knowledge classified BM as predominantly growing expansively
[153]. However, preclinical BM mouse models postulated the growth via vascular co-
option especially for melanoma BM, indication that the growth kinetic might differ
according to the primary tumour [43, 145]. In line, we observed a high fraction of
melanoma BM growing via vascular co-option [136]. The presence of depth invasion
into the surrounding brain parenchyma is of therapeutically importance as local
recurrence is a major complication in locally treated BM. Selection of patients
needing expanded safety margin treatment e.g. in a local radiosurgical treatment, is
challenging as so far no reliable radiological surrogate markers for invasion
behaviour could be identified. We observed in a previous study that patients with
description of infiltrative growth in the neurosurgical report presented with small
peritumoural brain oedema in the preoperative imaging [74]. Further, presence of a
small brain oedema correlated with an impaired survival prognosis, underscoring the
importance of further clinical investigation on the correlation of radiological finding
and BM invasion patterns.
Although the brain is considered as an immune privileged organ, we observed a
dense inflammatory reaction to BM, which is characterized by activation of
microglia/macrophages [139, 154]. The interaction of cancer and the immune system
gained attention in oncology research as recently the introduction of new immune
checkpoint inhibitors showed high and durable response rates [155-157]. In patients
with BM, response rates of up to 27% were observed, indicating that immune
checkpoint inhibitors might be a treatment option in selected patients with BM [107,
115, 116]. Currently, we are investigating the specific immune response including
effector, cytotoxic, memory and regulatory T-cell and the prognostic impact in BM.
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! (&!
Although, we were able to investigate a large real life patient cohort our studies have
some limitations. The clinical characteristics were collected retrospectively with all
the resulting shortcomings. Treatment strategies especially in the systemic therapy
improved during the time of investigation as we included patients over a time period
of more than 20 years. However, the RTOG studies, which were used for
establishment of the clinically used prognostic assessment, were conducted over a
comparable time period from 1985-2007 facing similar bias problems. Concerning
our histological studies, it would be highly interesting to study the matched primary
tumours. However, as patients were treated in different hospitals the tissue was
frequently not available. Despite this obstacle, we were still able to investigate a quite
large cohort of matched NSCLC samples in comparison to previous studies.
7.2 Conclusion & future prospects
In conclusion, this thesis could provide additional information on the clinical and
pathological prognostic factors in patients with BM of solid cancer. Inclusion of the
identified clinical, tissue based and radiological factors might have additional value
for the prognostic estimation of patients with BM. We could gain insight in the growth
characteristics of BM and the interaction of the immune system and BM. Further
prospective clinical studies might use the acquired knowledge for the appropriate
selection of patients.
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! ('!
8 Material & Methods !!8.1 Materials
For conduction of the brain metastasis cohort, all patients with histologically
confirmed BM from a solid tumour are identified from the database of Institute of
Neurology (Neuropathology), Medical University of Vienna. In each case, histological
diagnosis was made during routine diagnostic work-up at the Institute of Neurology
by a board-certified neuropathologist. Only patients with distinct intraparenchymal
BM are included in further analysis. As a consequence patients with osseous
metastases of the scalp are excluded. Further, only patients with availability of at
least one formalin-fixed paraffin embed tissue block containing viable brain
metastasis tumour tissue were included.
For conduction of the breast cancer BM cohort all patients receiving neurosurgical
resection of a BM from breast cancer or receiving whole brain radiation therapy for
BM from breast cancer were identified from a clinical database.
First diagnosis of BM of the included patients was between 1990 and 2012. All
patients were treated according to the current evidence-based standard of care for
primary tumour as well as BM. Treatment for BM was applied either at the Medical
University of Vienna, the Christian Doppler clinic (Salzburg) or the Wagner-Jauregg
Provincial Neuropsychiatric Clinic (Linz).
8.2 Methods Tissue based analysis Tissue stainings
For each included tissue block a hematoxylin & eosin staining according to standard
procedure was performed. Further a Gomorri silver impregnation stain was
performed according to laboratory standards to investigate reticulin.
Immunohistochemistry
Table 3 gives an overview on performed immunohistochemical protocols and used
antibodies.
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Table 3: Overview on used antibodies and protocols
MARKER ANTIBODY ANTIBODY DILUTION
ANTIGEN RETRIEVAL
HIF 1 alpha - hypoxia-inducible factor
Anti-Human HIF 1 alpha/ 610959 BD Transduction LaboratoriesTM
1:10 Standard cell conditioner 2 (pH 6) Ventana Benchmark ULTRA
Ki-67 Ki-67 Clone MIB-1/ M7240 Dako
1:200 EnVision Flex Target Retrieval Solution (pH6) AutostainerPlusLink/ Dako
CD 34 NovocastraTM Lyophilized Endothelial Cell Marker (CD34) NovocastraTM
1:50 Standard cell conditioner 1 (pH8) Ventana Benchmark ULTRA
GFAP Anti-Glial Fibrillary Acidic Protein/ Z 0334 DakoCytomation
1:3000 Proteinase K ready to use DakoCytomation
HLA ABC/ MHC I
Stam et al. [158] 1:2000 tris-EDTA puffer (ph 8.5)
HLA-DR/ MHC II
HLA-DR, DQ, DP Antigen/ M 0775 DakoCytomation
1:400 EnVision Flex Target Retrieval Solution (pH6) AutostainerPlusLink/ Dako
CD68 CD68/ Clone KP1/ M0814 DakoCytomation
1:5000 EnVision Flex Target Retrieval Solution (pH6) AutostainerPlusLink/ Dako
CD163 CD 163; NCL-CD163 Novocastra
1:1000 Citrate puffer (ph 6)
IBA-1 – ionized calcium binding adaptor molecule 1
Anti IBA 1; Wako 1:3000 tris-EDTA puffer (ph 8.5)
AIF-1 – allograft inflammatory factor
AIF-1, BMA Biomedicals AG
1:500 tris-EDTA puffer (ph 8.5)
SIGLEC-11 – sialic acid-binding Ig-like lectin
Bien et al. [159] 1:10 tris-EDTA puffer (ph 8.5)
HMGB1 – high-mobility group box 1
Affinity purified rabbit anti-HMG1 polyclonal antibody BD Biosciences Pharmingen TM
1:1000 tris-EDTA puffer (ph 8.5)
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! ()!
GLUT-5 Rabbit anti-GLUT 5 polyclonal antibody (AB 1041) Chemicon
1:1000 Citrate puffer (ph 6)
iNOS – inducible nitric oxide synthase
Rabbit anti-inducible nitric oxide synthase (iNOS) polyclonal antibody Chemicon International
1:30000 tris-EDTA puffer (ph 8.5)
p22phox p22-phox (FL-195): sc-20781 Santa Cruz Biotechnology, INC.
1:100 Citrate puffer (ph 6)
NCF-1 – neutrophil cytosolic factor 1 (p47-phox, NOXO2)
NCF1/p47phox Goat anti-Human Polyclonal (C-Terminus) Antibody-LS-B2365-LSBio Lifespan Biosciences
1:100 Citrate puffer (ph 6)
NOX-1 Anti-NOX1 rabbit Sigma-Aldrich
1:200 none
NOXO-1 Anti-NOXO rabbit Sigma-Aldrich
1:200 Citrate puffer (ph 6)
CD 3 CD3 (Clone SP7); Thermo Scientific
1:2000 EnVision Flex Target Retrieval Solution (pH9) AutostainerPlusLink/ Dako
CD 4 CD4/ Clone 4B12/M7310 DakoCytomation
1:100 EnVision Flex Target Retrieval Solution (pH9) AutostainerPlusLink/ Dako
CD 8 CD8/ Clone C8/144b/ M7103 DakoCytomation
1:00 EnVision Flex Target Retrieval Solution (pH6) AutostainerPlusLink/ Dako)
Granzym B GZB01; Thermo Scientific
1:1000 Tris-EDTA puffer (pH 9)
CD 20 CD20cy/ Clone L26/ M0755 DakoCytomation
1:400 EnVision Flex Target Retrieval Solution (pH6) AutostainerPlusLink/ Dako
CD 79A CD79 alpha/ Clone JCB117/ M7050 DakoCytomation
1:100 EnVision Flex Target Retrieval Solution (pH6) AutostainerPlusLink/ Dako
#v subunit EM013-09, [160] 1:1000* Standard cell
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! )+!
conditioner 1 (pH8) Ventana Benchmark ULTRA
$3 subunit EM002-12, [160] 1:500* Standard cell conditioner 1 (pH8) Ventana Benchmark ULTRA
#v$3 EM227-03, [160] 1:500 Standard cell conditioner 1 (pH8) Ventana Benchmark ULTRA
#v$5 EM099-02, [160] 1:800* Standard cell conditioner 1 (pH8) Ventana Benchmark ULTRA
#v$6 EM052-01, [160] 1:1000* Standard cell conditioner 1 (pH8) Ventana Benchmark ULTRA
#v$8 EM133-09, [160] 1:1000* Standard cell conditioner 1 (pH8) Ventana Benchmark ULTRA
E cadherin Ab15148; Abcam 1:30 EnVision Flex Target Retrieval Solution (pH9) AutostainerPlusLink/ Dako
N cadherin Ab18203; Abcam 1:500 EnVision Flex Target Retrieval Solution (pH9) AutostainerPlusLink/ Dako
Pan-Cytokeratin
Lu5, BMA Biomedicals 1:100 EnVision Flex Target Retrieval Solution (pH6) AutostainerPlusLink/ Dako)
HMBG45 HMB45, Dako 1:50 EnVision Flex Target Retrieval Solution (pH6) AutostainerPlusLink/ Dako)
* protein concentration 1mg/ml
Analysis of immunohistochemical stainings
All specimens were analyzed with a standard light microscope.
! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !
! )*!
HIF 1 alpha was scored according to the intensity of nuclear staining (none, weak,
moderate, strong) and the percentage of cells showing a specific
immunohistochemical signal (0-100%) [161]. For conduction of the HIF 1 alpha score
the multiplication of the percentage and the corresponding intensity was added,
resulting in an HIF 1 alpha index ranging from 0 to 300. Ki67 proliferation index was
evaluated by counting 500 cells within the area of the highest density of cells with a
specific, nuclear immunohistochemical signal and by giving the percentage of cells
showing a specific immunohistochemical signal (0-100%) [162]. The microvascular
density was assed by counting the amount of CD34 positive vessels within the area
of the highest density at a 20x magnification (“hot spot”) [163]. The vascular pattern
was analysed using the immunohistochemistry for CD34 as an endothelial marker.
The “active, angiogenic type” was defined by the predominance of sprouting vessels,
presenting with a multi-layered endothelium. The “silent type” was defined by the
predominance of vessels with thin, mono-layered endothelium. Specimens with no
clear predominance of either angiogenic patter were classified as “balanced type”.
For evaluation of inflammatory markers the regions of interest were defined as
follows: within the vital brain metastasis tumour tissue, peritumoural region, adjacent
brain parenchyma a least 0,5mm from the brain metastasis boarder. Within each
region of interest number of immunoreactive cells was counted in eight high power
fields at a magnification of x 400 (0.5 mm2).
Analyses of integrin #v subunit, cytoplasmic $3, #v$3, #v$5, #v$6, #v$8 complexes,
and of E cadherin and N cadherin were performed according to previously published
standards [164, 165]. In brief, intensity of membranous staining was multiplied by the
percentage of cells showing a specific, complete, membranous immunoreactivity,
resulting in an H-score ranging from o to 300. Further, integrin and cadherin
expression of the vascular structures of the surrounding brain parenchyma, tumour
vessels, peritumoural vessel and stroma was evaluated semi-quantitatively and
recorded as either positive or negative.
Evaluation of diffusion weighted imaging Diffusion weighted imaging was semiquantitatively jugged to be hypointense,
isointense or hyperintense compared the non pathological brain parenchyma. In BM
presenting with a heterogonous signal behaviour, diffusion intensity was determined
! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !
! )"!
according tot the predominant signal behaviour. Further, as available, apparent
diffusion coefficient (ADC) values were derived in 5 non-overlapping areas of interest
in solid, non-necrotic areas of the investigated brain metastasis. For further analysis,
the mean ADC value was calculated for each case [130].
Clinical data For the secure handling of patient data, a database was programmed using
FileMaker Pro (version 11.0v3, FileMaker Inc.). The database is password secured to
maintain data privacy protection. A Pub Med search was performed to evaluate
clinical factors with potential prognostic impact in patients with BM. Clinical data was
obtained by chart review. Survival data was retrieved from the database of the
National Cancer Registry of Austria and the Austrian Brain Tumour Registry [166,
167].
Statistical analysis All clinical data as well as results of immunohistochemical staining were collected in
the programmed database. Results were entered into the statistical package for the
social sciences (SPSS) 17.0 software (SPSS Inc., Chicago, IL, USA). Survival time
was defined as time from diagnosis of BM to death or last follow up. For estimation
survival analysis the Kaplan-Meier product limit method was used. To test differences
between groups respective to survival, the log-rank test was used. P-values , 0.05
were considered to indicate statistical significance. Variables that had significant
influence on survival in the univariate analysis were entered in a Cox proportional
hazard model. For correlation of two parameters the X2-Test, the Student’s T-Test
and the Mann-Whitney-U-Test were used as appropriate. Due to the exploratory and
hypothesis generating approach of the conducted projects no adjustment for multiple
testing was applied [168].
! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !
! )#!
9 List of figures Figure 1: Frequency of primary tumours causing BM!!10 List of tables Table 1: Diagnosis specific prognostic assessment Table 2: Estimated survival according to DS-GPA class Table 3: Overview on used antibodies and protocols
! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !
! )$!
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119. Berghoff, A., et al., Alleviation of brain edema and restoration of functional
independence by bevacizumab in brain-metastatic breast cancer: a case
report Breast Care, 2014: p. in press.
120. Winkler F, et al., IncIdence of braIn metastases In patIents treated wIth
bevacIzumab.
121. Heon, S., et al., Development of central nervous system metastases in
patients with advanced non-small cell lung cancer and somatic EGFR
! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !
! *+&!
mutations treated with gefitinib or erlotinib. Clinical cancer research : an official
journal of the American Association for Cancer Research, 2010. 16(23): p.
5873-82.
122. Lin, N.U., J.R. Bellon, and E.P. Winer, CNS metastases in breast cancer. J
Clin Oncol, 2004. 22(17): p. 3608-17.
123. Berghoff, A., et al., Brain metastases free survival differs between breast
cancer subtypes. British journal of cancer, 2012. 106(3): p. 440-6.
124. Bartsch, R., A.S. Berghoff, and M. Preusser, Optimal management of brain
metastases from breast cancer. Issues and considerations. CNS drugs, 2013.
27(2): p. 121-34.
125. Preusser, M., et al., Brain metastasis: opportunity for drug development? Curr
Opin Neurol, 2012. 25(6): p. 786-94.
126. Berghoff, A.S., et al., Brain-only metastatic breast cancer is a distinct clinical
entity characterised by favourable median overall survival time and a high rate
of long-term survivors. British journal of cancer, 2012. 107(9): p. 1454-8.
127. Jubb, A.M., et al., Vascular phenotypes in primary non-small cell lung
carcinomas and matched brain metastases. Br J Cancer, 2011. 104(12): p.
1877-81.
128. Berghoff, A.S., et al., Prognostic significance of Ki67 proliferation index, HIF1
alpha index and microvascular density in patients with non-small cell lung
cancer brain metastases. Strahlenther Onkol, 2014.
129. Lee, E.K., et al., Intracranial metastases: spectrum of MR imaging findings.
Acta Radiol, 2012. 53(10): p. 1173-85.
130. Arvinda, H.R., et al., Glioma grading: sensitivity, specificity, positive and
negative predictive values of diffusion and perfusion imaging. J Neurooncol,
2009. 94(1): p. 87-96.
131. Asao, C., et al., Diffusion-weighted imaging of radiation-induced brain injury
for differentiation from tumour recurrence. AJNR Am J Neuroradiol, 2005.
26(6): p. 1455-60.
! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !
! *+'!
132. Berghoff, A.S., et al., Preoperative diffusion-weighted imaging of single brain
metastases correlates with patient survival times. PLoS One, 2013. 8(2): p.
e55464.
133. Wesseling, P., A. von Deimling, and K. Aldape, Metastatic tumours of the
CNS. 4th ed. WHO Classification of Tumours of the Central Nervous System,
ed. D. Louis, et al. 2007, Lyons, France: IARC Press.
134. Neves, S., et al., Pseudogliomatous growth pattern of anaplastic small cell
carcinomas metastatic to the brain. Clin Neuropathol, 2001. 20(1): p. 38-42.
135. Friedl, P. and S. Alexander, Cancer invasion and the microenvironment:
plasticity and reciprocity. Cell, 2011. 147(5): p. 992-1009.
136. Berghoff, A.S., et al., Invasion patterns in brain metastases of solid cancers.
Neuro Oncol, 2013. 15(12): p. 1664-72.
137. Dal Bianco, A., et al., Multiple sclerosis and Alzheimer's disease. Ann Neurol,
2008. 63(2): p. 174-83.
138. Preusser, M., et al., Presence of D110 antigen expressing immunocompetent
cells in glioblastoma associates with prolonged survival. Neuropathol Appl
Neurobiol, 2004. 30(6): p. 608-14.
139. Berghoff, A.S., et al., Characterization of the inflammatory response to solid
cancer metastases in the human brain. Clinical & experimental metastasis,
2013. 30(1): p. 69-81.
140. Pestalozzi, B.C., et al., Identifying breast cancer patients at risk for Central
Nervous System (CNS) metastases in trials of the International Breast Cancer
Study Group (IBCSG). Ann Oncol, 2006. 17(6): p. 935-44.
141. Buyukhatipoglu, H., et al., Is prophylactic cranial irradiation a possible option
for human epidermal growth factor receptor 2-positive breast cancer? J Clin
Oncol, 2007. 25(10): p. 1292; author reply 1293.
142. Huang, F., et al., Prophylactic cranial irradiation in advanced breast cancer: a
case for caution. Int J Radiat Oncol Biol Phys, 2009. 73(3): p. 752-8.
! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !
! *+(!
143. Jakobsen, J.N. and J.B. Sorensen, Clinical impact of ki-67 labeling index in
non-small cell lung cancer. Lung Cancer, 2013. 79(1): p. 1-7.
144. Kreuter, M., et al., Prognostic relevance of angiogenesis in stage III NSCLC
receiving multimodality treatment. The European respiratory journal, 2009.
33(6): p. 1383-8.
145. Fidler, I.J., et al., The seed and soil hypothesis: vascularisation and brain
metastases. The lancet oncology, 2002. 3(1): p. 53-7.
146. Langley, R., et al., Investigators Does Whole Brain Radiotherapy Impact on
the Survival and Quality of Life of Patients with Brain Metastases from Non-
Small Cell Lung Cancer? Interim Results from the MRC QUARTZ Trial. Lung
Cancer 2012: p. (in press).
147. Soffietti, R., et al., A European Organisation for Research and Treatment of
Cancer phase III trial of adjuvant whole-brain radiotherapy versus observation
in patients with one to three brain metastases from solid tumours after surgical
resection or radiosurgery: quality-of-life results. Journal of clinical oncology :
official journal of the American Society of Clinical Oncology, 2013. 31(1): p.
65-72.
148. Berghoff, A., et al., Preoperative diffusion-weighted imaging of single brain
metastases correlates with patient survival times. . PLOS one 2013(in press).
149. Sperduto, C.M., et al., A validation study of a new prognostic index for patients
with brain metastases: the Graded Prognostic Assessment. Journal of
neurosurgery, 2008. 109 Suppl: p. 87-9.
150. Langley, R.R. and I.J. Fidler, The seed and soil hypothesis revisited--the role
of tumour-stroma interactions in metastasis to different organs. Int J Cancer,
2011. 128(11): p. 2527-35.
151. Moorman, A.M., et al., The prognostic value of tumour-stroma ratio in triple-
negative breast cancer. Eur J Surg Oncol, 2012. 38(4): p. 307-13.
152. de Kruijf, E.M., et al., Tumour-stroma ratio in the primary tumour is a
prognostic factor in early breast cancer patients, especially in triple-negative
carcinoma patients. Breast Cancer Res Treat, 2011. 125(3): p. 687-96.
! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !
! *+)!
153. Louis, D., et al., WHO Classification of Tumours of the Central Nervous
System. 4th ed. WHO Health Organization Classification of Tumours, ed. F.
Bosman, et al. 2007, Lyon: International Agency for Research on Cancer.
154. Felgenhauer, K., The blood-brain barrier redefined. J Neurol, 1986. 233(4): p.
193-4.
155. Hodi, F.S., et al., Improved survival with ipilimumab in patients with metastatic
melanoma. N Engl J Med, 2010. 363(8): p. 711-23.
156. Robert, C., et al., Ipilimumab plus dacarbazine for previously untreated
metastatic melanoma. N Engl J Med, 2011. 364(26): p. 2517-26.
157. Wolchok, J.D., et al., Nivolumab plus ipilimumab in advanced melanoma. N
Engl J Med, 2013. 369(2): p. 122-33.
158. Stam, N.J., et al., HLA-A- and HLA-B-specific monoclonal antibodies reactive
with free heavy chains in western blots, in formalin-fixed, paraffin-embedded
tissue sections and in cryo-immuno-electron microscopy. Int Immunol, 1990.
2(2): p. 113-25.
159. Bien, C.G., et al., Destruction of neurons by cytotoxic T cells: a new
pathogenic mechanism in Rasmussen's encephalitis. Ann Neurol, 2002. 51(3):
p. 311-8.
160. Goodman, S.L., H.J. Grote, and C. Wilm, Matched rabbit monoclonal
antibodies against alphav-series integrins reveal a novel alphavbeta3-LIBS
epitope, and permit routine staining of archival paraffin samples of human
tumours. Biology open, 2012. 1(4): p. 329-40.
161. Zhong, H., et al., Overexpression of hypoxia-inducible factor 1alpha in
common human cancers and their metastases. Cancer Res, 1999. 59(22): p.
5830-5.
162. Preusser, M., et al., Ki67 index in intracranial ependymoma: a promising
histopathological candidate biomarker. Histopathology, 2008. 53(1): p. 39-47.
163. Weidner, N., et al., Tumour angiogenesis and metastasis--correlation in
invasive breast carcinoma. N Engl J Med, 1991. 324(1): p. 1-8.
! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !
! **+!
164. Cappuzzo, F., et al., Epidermal growth factor receptor gene and protein and
gefitinib sensitivity in non-small-cell lung cancer. Journal of the National
Cancer Institute, 2005. 97(9): p. 643-55.
165. Hirsch, F.R., et al., Epidermal growth factor receptor in non-small-cell lung
carcinomas: correlation between gene copy number and protein expression
and impact on prognosis. Journal of clinical oncology : official journal of the
American Society of Clinical Oncology, 2003. 21(20): p. 3798-807.
166. Woehrer, A., Brain tumour epidemiology in Austria and the Austrian Brain
Tumour Registry. Clin Neuropathol, 2013. 32(4): p. 269-85.
167. Wohrer, A., et al., The Austrian Brain Tumour Registry: a cooperative way to
establish a population-based brain tumour registry. Journal of neuro-oncology,
2009. 95(3): p. 401-11.
168. Bender, R. and S. Lange, Adjusting for multiple testing--when and how?
Journal of clinical epidemiology, 2001. 54(4): p. 343-9.
! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !
! ***!
12 Curriculum vitae Dr. med. Univ. Anna Sophie Berghoff
Medical University of Vienna, Department of Medicine I
Comprehensive Cancer Center Vienna
Währinger Gürtel 18-20
A-1097 Vienna , Austria
Tel: +431-40400-5595 or +43 6606566391
Fax: +431-40400-5511
Email: [email protected]
Date of birth: 13.11.1987 (Bonn/Germany)
Citizenship: Austrian/German
School education 1993-1996 Elementary school, Bonn/Germany
1997-2003 High School, Bonn/Germany
2003-2004 High School, Justin, Tx/USA
2004-2005 High School, Vienna/Austria
Academic education 2005-2011 Medical University of Vienna (n202)
05.07.2011 Medical Doctor (MD) degree
Diploma thesis: Outcome measurements in metastatic breast
cancer
(Supervisor: Priv.-Doz. Dr. Rupert Bartsch)
since 01.10.2011 Doctoral program „Clinical Neurosciences“
PhD thesis: Brain Metastases: Brain metastases: systematic
exploration of prognostic and predictive factors (Supervisor: Priv.-Doz. Dr. Matthias Preusser)
! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !
! **"!
Clinical education 10.2011-12.2012 Fellow of Neuropathology, Institute of Neurology, Medical
University of Vienna
since 01.01.2013 Fellow of Internal Medicine, Department of Medicine I,
Medical University of Vienna
Memberships Society of Austrian Neurooncology (SANO)
Austrian Society of Haematology and Oncology (ÖGHO)
American Society of Clinical Oncology (ASCO)
European Society of Medical Oncology (ESMO)
European Association of Neurooncology (EANO)
European Organisation of Research and Treatment of Cancer (EORTC)
Publications 45 articles in scientific journals with peer-review system (cumulative impact factor
175.7, H index 8)
16 articles as first author in scientific journal with peer-review system (cumulative
impact factor 41.5)
5 oral and 13 poster presentations at international and national scientific meetings
other 2011-2013 Chairperson of the office for postgraduate studies, Austrian
Student Union
2009- 2011 Chairperson of the office for human medicine studies, Austrian
Student Union
2007-2010 Chairperson of the office for social affairs, Austrian Student
Union
2010-2011 Member of the academic senate, Medical University of Vienna
2008-2011 Member of the academic committee for human medicine studies,
Medical University of Vienna
! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !
! **#!
Publications All original articles: 45 Cumulative Impact Factor: 175.7
Average Impact Factor: 3.9
First authorship: 16 Cumulative Impact Factor: 41.5
Average Impact Factor: 2.6
Congress Activities Poster presentations: 13 Oral presentations: 5
Grants and Prices Poster prices: 4 Travel grants: 5 Research grants: 4
! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !
! **$!
Original Articles A. First authorship
1. Berghoff AS, Ilhan-Mutlu A, Wöhrer A, Hackl M, Widhalm G, Hainfellner JA,
Dieckmann K, Melchardt T, Dome B, Heinzl H, Birner P, Preusser M
Prognostic significance of Ki67 proliferation index, HIF1 alpha index and
microvascular density in patients with non-small cell lung cancer brain
metastases.
Strahlenther Onkol. 2014 (in press)
ISI 2011: IF 4.2
2. Berghoff AS, Rajky O, Winkler F, Bartsch R, Furtner J, Hainfellner JA,
Goodman SL, Weller M, Schittenhelm J, Preusser M.
Invasion patterns in brain metastases of solid cancers.
Neurooncol (in press)
ISI 2011: IF 5.7
3. Berghoff AS, Birner P, Streubel B, Kenner L, Preusser M
ALK gene aberrations and the JUN/JUNB/PDGFR axis in metastatic NSCLC
APMIS. 2014 (in press)
ISI 2011: IF 2.0
4. Berghoff AS, Stefanits H, Woehrer A, Heinzl H, Preusser M, Hainfellner JA.
Clinical Neuropathology practice guide 3-2013: levels of evidence and clinical
utility of prognostic and predictive candidate brain tumour biomarkers
Clin Neuropathol 2013 May-Jun;32(3):148-58.
ISI 2011: IF 1.0
5. Berghoff AS, Spanberger T, Ilhan-Mutlu A, Magerle M, Hutterer M, Woehrer A,
Hackl M, Widhalm G, Dieckmann K, Marosi C, Birner P, Prayer D, Preusser M
Preoperative diffusion-weighted imaging of single brain metastases correlates
with patient survival times.
PLOS one 2013;8(2):e55464
ISI 2011: IF 4.1
6. Berghoff AS, Lassmann H, Preusser M, Höftberger R.
Characterization of the inflammatory response to solid cancer metastases in
the human brain.
Clin Exp Metastasis. 2013 Jan;30(1):69-81
ISI 2011: IF 3.5
! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !
! **%!
7. Berghoff AS, Bago-Horvath Z, Ilhan-Mutlu A, Magerle M, Dieckmann K,
Marosi C, Birner P, Widhalm G, Steger GG, Zielinski CC, Bartsch R,
Preusser M.
Brain-only metastatic breast cancer is a distinct clinical entity characterized by
favourable median overall survival time and a high rate of long-term survivors
Br J Cancer 2012 Oct 23;107(9):1454-8.
ISI 2011: IF 5.0
8. Berghoff A, Bago-Horvath Z, De Vries C, Dubsky P, Pluschnig U, RudasM,
Rottenfusser A, Knauer M, Eiter H, Fitzal F, Dieckmann K, Mader RM, Gnant
M, Zielinski CC, Steger GG, Preusser M, Bartsch R.
Brain Metastases free survival differs between breast cancer subtypes.
Br J Cancer 2012 Jan 31;106(3):440-6
ISI 2011: IF 5.0
9. Berghoff AS, Magerle M, Ilhan-Mutlu A, Dinhof C, Widhalm G, Dieckman K,
Marosi C, Wöhrer A, Hackl M, Zöchbauer-Müller S, Preusser M, Birner P,
Frequent overexpression of erbb- receptor family members in brain
metastases of non-small cell lung cancer patients
AMPIS (in press)
ISI 2011: 2.0
10. Berghoff A, Bago-Horvath Z, Dubsky P, Rudas M, Pluschnig U, Wiltschke C,
Gnant M, Steger GG, Zielinski CC, Bartsch R.
Impact of Her2-targeted therapy on overall survival in patients with Her2-
positive metastatic breast cancer
Breast J 2013 Mar-Apr;19(2):149-55.
ISI 2011: IF 1.6
11. Berghoff AS, Capper D, Preusser M.
Lack of BRAF V600E Protein Expression in primary central nervous system
lymphoma
Appl Immunohistochem Mol Morphol 2013 Jul;21(4):351-3
ISI 2011: IF 1.6
12. Berghoff AS, Preusser M.
Clinical neuropathology practice guide 06-2012: MGMT testing in elderly
glioblastoma patients--yes, but how?
Clin Neuropathol. 2012 Nov-Dec;31(6):405-8.
ISI 2011: 1.0, Invited Review
! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !
! **&!
13. Berghoff AS, Stefanits H, Heinzl H, Preusser M.
Clinical Neuropathology Practice News 4-2012: levels of evidence for brain
tumor biomarkers.
Clin Neuropathol. 2012 Jul-Aug;31(4):206-9.
ISI 2011: 1.0, Invited Review 14. Berghoff AS, Preusser M.
Biology in Prevention and Treamtent of Brain Metastases. Exp Rev Anticancer Ther (in press)
ISI 2011: 2.1, Invited Review 15. Berghoff AS, Sax C, Klein M, Furtner J, Dieckmann K, Gatterbauer B,
Widhalm G, Rudas M, Zielinski CC, Barsch R, Preusser M
Alleviation of brain edema and restoration of functional independence by
bevacizumab in brain-metastatic breast cancer
Breast care (in press)
ISI 2011: 0.7
16. Berghoff AS, Ricken G, Widhalm G, Rajky O, Hainfellner JA, Birner P,
Raderer M, Preusser M.
PD1 (CD279) and PD-L1 (CD274, B7H1) expression in primary central
nervous system lymphomas (PCNSL).
Clin Neuropathol (in press)
ISI 2011: 1.0
B. Co-authorship 1. Tschandl P, Berghoff AS, Preusser M, Burgstaller-Mühlbacher S, Okamoto I,
Pehamberger H, Kittler H.
NRASQ61 and BRAFV600E mutations in melanoma-associated nevi and
uninvolved nevi
PLOS one (in press)
ISI 2011: IF 4.1
1. Zagouri F, Sergentanis TN, Bartsch R, Berghoff AS, Chrysikos D, de
Azambuja E, Dimopoulos MA, Preusser M.
Intrathecal administration of trastuzumab for the treatment of meningeal
carcinomatosis in HER2-positive metastatic breast cancer: A systematic
review and pooled analysis.
Breast Cancer Res Treat 2013 May;139(1):13-22
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! **'!
ISI 2011: IF 4.4
2. Preusser M, Berghoff AS, Capper D, von Deimling A, Maroske F, Brodowicz
T, Hejna M, Birner P, Schoppmann SF.
No evidence for braf-v600e mutations in gastro-eosophageal tumors: results
from a high-throughput analysis of 534 cases using a mutation-specific
antibody
Appl Immunohistochem Mol Morphol (in press)
ISI 2011: IF 1.6
3. Preusser M, Berghoff AS, Ilhan-Mutlu A, Magerle M, Dinhof C, Widhalm G,
Dieckmann K, Marosi C, Wöhrer A, Hackl M, Zöchbauer-Müller S, von
Deimling A, Schoppmann SF, Zielinski CC, Streubel B Birner P
ALK gene translocations and amplifications in brain metastases of non-small
cell lung cancer
Lung Cancer 2013 Jun;80(3):278-83.
ISI 2011: 3.4
4. Preusser M, Berghoff AS, Ilhan-Mutlu A, Dinhof C, Magerle M, Marosi C, Hejna
M, Capper D, von Deimling A, Schoppmann SF, Birner P
Brain metastases of gastro-oesophageal cancer: evaluation of molecules with
relevance for targeted therapies.
Anticancer Res 2013 Mar;33(3):1065-71.
ISI 2011: 1.7
5. Sahm F, Capper D, Preusser M, Meyer J, Stenzinger A, Lasitschka F,
Berghoff AS, Habel A, Schneider M, Kulozik A, Anagnostopoulos I, Müllauer L,
Mechtersheimer G, von Deimling A.
BRAFV600E mutant protein is expressed in cells of variable maturation in
Langerhans cell histiocytosis.
Blood 2012 Sep 20;120(12):e28-34.
ISI 2011: 9.9
5. Ilhan-Mutlu A, Wöhrer A, Berghoff AS, Widhalm G, Marosi C, Wagner L,
Preusser M
Comparison of microRNA expression levels between initial and recurrent
glioblastoma specimens.
J Neurooncol 2013 May;112(3):347-54
ISI 2011: 3.2
! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !
! **(!
6. Capper D, Berghoff AS, Magerle M, Ilhan A, Wöhrer A, Hackl M, Pichler J,
Pusch S, Meyer J, Habel A, Petzelbauer P, Birner P, von Deimling A,
Preusser M.
Immunohistochemical testing of BRAF V600E status in 1,120 tumor tissue
samples of patients with brain metastases.
Acta Neuropathol 2012; 123 (2): 223-33
ISI 2011: IF 9.3
7. Bartsch R, Berghoff A, Pluschnig U, Bago-Horvath Z, Dubsky P, Rottenfusser
A, Devries C, Rudas M, Fitzal F, Dieckmann K, Mader RM, Gnant M, Zielinski
CC, Steger GG.
Impact of anti-HER2 therapy on overall survival in HER2-overexpressing
breast cancer patients with brain metastases.
Br J Cancer 2012; 106(1): 25-31
ISI 2011: IF 5.0
8. Spanberger T, Berghoff AS, Dinhof C, Ilhan-Mutlu A, Magerle M, Hutterer M,
Pichler J, Wöhrer A, Hackl M, Widhalm G, Hainfellner JA, Dieckmann K,
Marosi C, Birner P, Prayer D, Preusser M.
Extent of peritumoral brain edema correlates with prognosis, tumoral growth
pattern, HIF1a expression and angiogenic activity in patients with single brain
metastases.
Clin Exp Metastasis. 2013 Apr;30(4):357-68
ISI 2011: IF 3.5
9. Preusser M, Capper D, Ilhan-Mutlu A, Berghoff AS, Bartsch R, Birner P,
Marosi C, Zielinski C, Mehta MP, Winkler F, Wick W, von Deimling A.
Brain metastases: pathobiology and emerging targeted therapies.
Acta Neuropathol 2012; 123 (2): 205-22, Invited Review
ISI 2011: IF 9.3
10. Capper D, Berghoff AS, von Deimling A, Preusser M.
Clinical neuropathology practice news 2-2012: BRAF V600E testing.
Clin Neuropathol 2012; 31(2):64-6, Invited Review
ISI 2011: IF 1.0
11. Koperek O, Kornauth C, Capper D, Berghoff AS, Asari R, Niederle B, Deimling
A, Birner P, Preusser M.
Immunohistochemical detection of the BRAF V600E mutated protein in
papillary thyroid carcinoma.
! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !
! **)!
Am J Surg Pathol 2012 Jun;36(6):844-50.
ISI 2011: IF 4.4
12. Birner P, Schoppmann A, Schindl M, Dinhof C, Jesch B, Berghoff A,
Schoppmann S.
Human homologue for Caenorhabditis elegans CUL-4 protein overexpression
is associated with malignant potential of epithelial ovarian tumors and poor
outcome in carcinoma.
J Clin Pathol 2012 Jun;65(6):507-11.
ISI 2011: IF 2.3
13. Bartsch R, Bago-Horvath Z, Pluschnig U, Devries C, Berghoff A, Dubsky P,
Rudas M, Mader RM, Rottenfusser A, Fitzal F, Gnant M, Zielinski CC, Steger
GG.
Ovarian function suppression and fulvestrant as endocrine therapy in
premenopausal women with metastatic breast cancer.
Eur J Cancer 2012 Sep;48(13):1932-8.
ISI 2011: IF 5.5
14. Preusser M, Fülöp G, Berghoff AS, Heinzl H, Steger GG, Greil R, Zielinski CC,
Bartsch R.
International influence of the American ODAC statement upon prescription
practive of bevacizumab in metastatic breast cancer.
Oncologist. 2012;17(7):e13-7.
ISI 2011: IF 3.9
15. Schoppmann S, Berghoff AS, Jesch B, Zacherl J, Nirtl N, Jomrich G, Maroske
F, Streubl B, Mesteri I, Birner P.
Expression of podoplanin in sporadic gastrointestinal stromal tumors.
Future Oncol 2012 Jul;8(7):859-66.
ISI 2011: 3.2
16. Schoppmann S, Berghoff A, Dinhof C, Jakesz R, Gnant M, Dubsky P, Jesch
B, Birner P.
Podoplanin expressing cancer associated fibroblasts are associated with poor
prognosis in invasive breast cancer
Breast Cancer Res Tr 2012 Jul;134(1):237-44.
ISI 2011: IF 4.4
17. Preusser M, Capper D, Berghoff AS, Horvat R, Wrba F, Schindl M,
Schoppmann S, von Deimling A, Birner P.
! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !
! *"+!
Expression of BRAF V600E mutant protein in epithelial ovarian tumors.
Appl Immunohistochem Mol Morphol 2013 Mar;21(2):159-64
ISI 2011: IF 1.6
18. Preusser M, Berghoff AS, Schadendorf D, Lin NU, Stupp R.
Brain metastasis: opportunity for drug development?
Curr Opin Neurol. 2012 Dec;25(6):786-794.
ISI 2011: IF 4.9
19. Preusser M, Winkler F, Collette L, Haller S, Marreaud S, Soffietti R, Klein M,
Reijneveld JC, Tonn JC, Baumert BG, Mulvenna P, Schadendorf D,
Duchnowska R, Berghoff AS, Lin N, Cameron DA, Belkacemi Y, Jassem J,
Weber DC.
Trial design on prophylaxis and treatment of brain metastases: Lessons
learned from the EORTC Brain Metastases Strategic Meeting 2012.
Eur J Cancer. 2012 Dec;48(18):3439-47
ISI 2011: IF 5.5
20. Bartsch R, Berghoff AS, Preusser M.
Optimal Management of Brain Metastases from Breast Cancer : Issues and
Considerations.
CNS Drugs. 2013 Feb;27(2):121-34.
ISI 2011: IF 4.8 Invited Review 21. Sahm F, Bissel J, Kölsche C, Schweizer L, Capper D, Reuss D, Böhmer K,
Lass U, Göck T, Kalis K, Meyer J, Habel A, Brehmer S, Mittelbronn M, Jones
DT, Schittenhelm J, Urbschat S, Ketter R, Heim S, Mawrin C, Hainfellner JA,
Berghoff AS, Preusser M, Herold-Mende C, Unterberg A, Hartmann C,
Kickingereder P, Collins P, Pfister SM, von Deimling A.
AKT1E17K mutations cluster with meningothelial and transitional
meningiomas and can be detected by SFRP1 immunohistochemistry
Acta Neuropathol (in press)
ISI 2011: IF 9.7
22. Ilhan-Mutlu A, Berghoff AS, Furtner J, Dieckmann K, Slavc I, Czech T, Marosi
C, Wagner L, Preusser M
High plasma-GFAP levels in metastatic myxopapillary ependymoma.
J Neurooncol 2013 Jul;113(3):359-63.
ISI 2011: IF 3.2
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! *"*!
23. Bartsch R, Berghoff AS, Stellenberger J, Rudas M, Dieckmann K, Roth D,
Steger GG, Zielinski CC, Preusser M
Breast cancer brain metastases responding to primary systemic therapy with
T-DM1
J Neurooncol 2013 (in press)
ISI 2011: IF 3.2
24. Bartsch R, Frings S, Marty M, Awada A, Berghoff AS, Conte P, Dickin S,
Enzmann H, Gnant M, Hasmann M, Hendriks HR, Llombart A, Massacesi C,
von Minckwitz G, Penult-Llorca F, Scaltriti M, Yarden Y, Zwierzina H and
Zielinski CC for the Biotherapy Development Association (BDA)
Present and Future Breast Cancer Management - Bench to Bedside and
Back: A Positioning Paper of Academia, Regulatory Authorities and
Pharmaceutical Industry
Ann Oncol 2013 (in press)
ISI 2011: IF 7.4
25. Preusser M, Berghoff AS, Berger W, Ilhan-Mutlu A, Dinhof C, Widhalm G,
Dieckmann K, Wöhrer A, Hackl M, von Deimling A, Streubel B, Birner P.
High rate of FGFR1 amplifications in brain metastases of squamous and non-
squamous lung cancer
Lung Cancer 2013 (in press)
ISI 2011: IF 3.4
26. Tezcan G, Tunca B, Bekar A, Preusser M, Berghoff AS, Egeli U, Cecener G,
Ricken G, Budak F, Taskapilioglu MO, Kocaeli H, Tolunay S
microRNA Expression Pattern Modulates Temozolomide Response in GBM
Tumors with Cancer Stem Cells
Cell Mol Neurobiol. 2014 (in press)
ISI 2011: IF 2.2
27. Mathilde Foedermayr M, Sebesta M, Rudas M, Berghoff AS, Promberger R,
Preusser M, Dubsky P, Fitzal F, Gnant M, Steger GG, Weltermann A, Zielinski
CC, Zach O, Bartsch R.
BRCA-1 methylation and TP53 mutation in triple-negative breast cancer
patients without pathological complete response to taxane-based neoadjuvant
chemotherapy
Cancer Chemother Pharmacol. 2014 Apr;73(4):771-8.
ISI 2011: IF 2.8
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28. Kovacs GG, Peden A, Weis S, Höftberger, Berghoff AS, Yull H, Ströbel T,
Koppi S, Katzenschlager R, Langenscheidt D, Assar H, Zaruba E, Gröner A,
Voigtländer T, Puska G, László L, Ironside JW, Head MW, Budka H
Rapidly progressive dementia with thalamic degeneration and peculiar cortical
Prion protein immunoreactivity, but absence of Proteinase K resistant PrP: A
new disease entity?
Acta Neuropathol Commun. 2013 Nov 11;1(1):72
ISI 2011: not listed
29. Preusser M, Berghoff AS, Hottinger AF
High-grade meningiomas: new avenues for drug treatment?
Curr Opin Neurol (in press)
ISI 2011: 5.4, Invited Review
C. Manuscripts currently under review 1. Berghoff AS, Bartsch R, Preusser M, Ricken G, Steger GG, Bago-Horvath Z,
Rudas M, Streubel B, Dubsky P, Gnant M, Fitzal F, Zielinski CC, Birner P.
Co-overexpression of HER3 is a predictor of impaired survival in breast cancer
patients
Submitted
2. Bartsch R, Berghoff AS, Preusser M, Steger GG, C. Zielinski CC
Anti-angiogenic treatment approaches in breast cancer
Submitted
3. Ilhan-Mutlu A, Berghoff AS, Wrba F, Preusser M
Characterization of Candidate Tissue Biomarkers in a Rare Series of
Myxopillary Ependymoma Specimens
Submitted
4. Birner P, Berghoff AS, Dinhof C, Capper D, Schoppmann SF, Petzelbauer P,
von Deimling A, Berger W, Preusser M.
ETV1 protein expression is not associated with ETV1 gene amplification but
with BRAFV600E in brain metastases of malignant melanoma
Submitted
5. Bartsch R, Berghoff AS, Rudas M, Dubsky P, De Vries C, Sattlberger C, Mader
RM, Zagouri F, Sparber C, Fitzal F, Gnant M, Rottenfusser A, Zielinski CC,
Preusser M, Steger GG
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! *"#!
Taxanes plus trastuzumab compared to oral vinorelbine plus trastuzumab in
her2-overexpressing metastatic breast cancer patients
Submitted
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! *"$!
13 Congress Activities 1. Berghoff AS, Bartsch R, Stellenberger J, Rudas M, Dieckmann K, Roth D,
Steger GG, Zielinski CC, Preusser M Breast cancer brain metastases responding to primary systemic therapy with
T-DM1
Oral Presentation; 3rd Annual Brain Metastases Research and Emerging
Therapy Conference
September 2013, Marseille, France 2. Berghoff AS, Fuchs E, Ricken G, Ilhan-Mutlu A, Magerle M, Spanberger T,
Wöhrer A, Hackl M, Pichler J, Hutterer M, Widhalm G, Dieckmann K, Birner P,
Prayer D, Bartsch R, Preusser M.
Characterization of T-ell infiltrates in brain metastases of solid tumors
Poster Presentation; 3rd Annual Brain Metastases Research and Emerging
Therapy Conference
September 2013, Marseille, France
3. Berghoff AS, Ilhan-Mutlu A, Wöhrer A, Hackl M, Widhalm G, Hainfellner JA,
Dieckmann K, Zielinski CC, Birner P, Preusser M.
Proliferation and microvascular density predict survival in patients with brain
metastases of non-small cell lung cancer.
Poster Presentation, European Cancer Congress
October 2013, Amsterdam, Netherland
4. Berghoff AS, Ilhan-Mutlu A, Wöhrer A, Hackl M, Widhalm G, Hainfellner JA,
Dieckmann K, Zielinski CC, Birner P, Preusser M.
Proliferation and microvascular density predict survival in patients with brain
metastases of non-small cell lung cancer.
Poster Presentation, Jahrestagung der Deutschen, Schweizer und
Österreichischen Gesellschaft für Hämatologie und Onkologie
October 2013, Vienna, Austria
4. Berghoff AS
Clinical practice: Choosing a PCV schedule and toxicity management
Oral Presentation, Serono Foundation Central Nervous System (CNS)
Malignancies Meeting,
October 2013, Vienna, Austria
5. Berghoff AS, Rajky O, Winkler F, Bartsch R, Furtner J, Hainfellner JA,
Goodman SL, Weller M, Schittenhelm J, Preusser M
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! *"%!
Invasion patterns in brain metastases of solid cancers
Poster Presentation; Annual Meeting of the American Society of Clinical
Oncology
June 2013, Chicago, USA
5. Berghoff AS, Magerle M, Ilhan-Mutlu A, Wöhrer A, Hackl M, Widhalm G,
Birner P, Bartsch R, Zielinski CC, Preusser M.
Clincal prognostic factors in brain metastases from colorectal cancer
Poster Presentation; Frühjahrstagung der Österreichischen Gesellschaft für
Hämatologie und Onkologie
April 2013, Linz, Austria
6. Berghoff AS, Bago-Horvath Z, Preusser M, Steger GG, Rudas M, Birner P,
Zielinski CC, Rupert Bartsch R
Co-expression of HER3 is a predictor of impaired survival in HER2-positive
breast cancer patients
Poster Presentation; Frühjahrstagung der Österreichischen Gesellschaft für
Hämatologie und Onkologie
April 2013, Linz, Austria
7. Berghoff AS, Rajky O, Winkler F, Weller M, Zielinski CC, Schittenhelm J,
Preusser M
Evaluation of invasion patterns and their correlation with integrin expression in
alphavbeta brain metastases of solid cancers
Poster presentation; EOCTC-EANO-ESMO trends in Central Nervous System
Malignancies
March 2013, Prag, Czech Republic
8. Berghoff AS, Lassmann H, Preusser M, Höftberger R.
Characterization of the inflammatory response to solid cancer metastases in
the human brain.
Oral presentation; 10th Meeting of the European Society of Neurooncology
September 2012, Marseille, France
9. Berghoff AS, Spanberger T, Ilhan-Mutlu A, Magerle M, Hutterer M, Woehrer A,
Hackl M, Widhalm G, Dieckmann K, Marosi C, Birner P, Prayer D, Preusser M
Preoperative diffusion-weighted imaging of single brain metastases correlates
with patient survival times.
Oral presentation; 17th annual Meeting of the American Society for Neuro-
Oncology
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! *"&!
November 2012, Washington, USA
10. Berghoff AS, Lassmann H, Preusser M, Höftberger R.
Characterization of the inflammatory response to solid cancer
metastases in the human brain.
Poster Presentation; Frühjahrstagung der Österreichischen Gesellschaft für
Hämatologie und Onkologie
April 2012, Graz, Austria
11. Berghoff AS, Lassmann H, Preusser M, Höftberger R.
Characterization of the inflammatory response to solid cancer
metastases in the human brain.
Poster Presentation; YSA PhD Symposium
June 2012, Vienna, Austria
12. Berghoff AS, Bago-Horvath Z, Ilhan-Mutlu A, Magerle M, Dieckmann K,
Marosi C, Birner P, Widhalm G, Steger GG, Zielinski CC, Bartsch R,
Preusser M.
Brain-only metastatic breast cancer is a distinct clinical entity
characterized by favorable median overall survival Time and a high rate of
long-term survivors
Poster Discussion; Congress of the European Society for Medical Oncology
October 2012, Vienna, Austria
13. Berghoff AS, Spanberger T, Dinhof C, Ilhan-Mutlu A, Magerle M, Hutterer M,
Pichler J, Wöhrer A, Hackl M, Widhalm G, Hainfellner JA, Dieckmann K,
Marosi C, Birner P, Prayer D, Preusser M.
Extent of peritumoral brain edema correlates with prognosis, tumoral growth
pattern, HIF1a expression and angiogenic activity in patients with single brain
metastases.
Poster Presentation; 2nd Annual Brain Metastases Research and Emerging
Therapy Conference
September 2012, Marseille, France
14. Berghoff A, Bago-Horvath Z, De Vries C, Dubsky P, Pluschnig U, RudasM,
Rottenfusser A, Knauer M, Eiter H, Fitzal F, Dieckmann K, Mader RM, Gnant
M, Zielinski CC, Steger GG, Preusser M, Bartsch R, Zielinski CC.
Impact of Her2 targeted therapy on overall survival in patients with Her2
positive metastatic breast cancer
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! *"'!
Poster Presentation; Annual Meeting of the American Society of Clinical
Oncology June 2011, Chicago, USA
15. Berghoff A, Bago -Horvath Z, Dubsky P, Rudas M, Pluschnig U,
Rottenfusser A, Gnant M, Steger GG, Zielinski CC, Bartsch R.
Brain metastases-free survival in patients with Her2 positive metastatic breast
cancer.
Poster Presentation; ASCO Breast Cancer Symposium
September 2011, San Francisco, USA
16. Berghoff A, Bago-Horvath Z, De Vries C, Dubsky P, Pluschnig U, RudasM,
Rottenfusser A, Knauer M, Eiter H, Fitzal F, Dieckmann K, Mader RM, Gnant
M, Zielinski CC, Steger GG, Preusser M, Bartsch R, Zielinski CC.
Impact of Her2 targeted therapy on overall survival in patients with Her2
positive metastatic breast cancer
Oral presentation; Frühjahrstagung der Österreichischen Gesellschaft für
Hämatologie und Onkologie
May 2011, Pörtschach, Austria
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Grants and Prices
1. Initiative Krebsforschung Grant, Project “Tumorimmunologie von
Hirnmetastasen“, 40 000 %, December 2014
2. Hochschuljubiläumsstiftung Grant, Project „Das Immunsystem im Kampf
gegen den Krebs“, 7500 %, October 2013
3. Forschungsförderungsstipendium Medical University of Vienna, Project
„Inflammatory response in brain metastases of solid tumor“, 850 %, March
2013 3. Forschungsförderung der Stadt Wien, Project „Preoperative diffusion-weighted
imaging of single brain metastases correlates with patient survival times“,
1000 %, January 2013 4. Poster Price 2nd Annual Brain Metastases Research and Emerging Therapy
Conference, September 2012, Marseille, France
5. Poster Price Vienna Summer School on Oncology, August 2011, Vienna,
Austria
6. Poster Price Jahrestagung der Deutschen, Schweizer und Österreichischen
Gesellschaft für Hämatologie und Onkologie, Oktober 2013, Vienna, Austria
7. Poster Price Frühjahrstagung der Österreichischen Gesellschaft für
Hämatologie und Onkologie, April 2013, Linz, Austria
4. Travel Grant European Society for Medical Oncology, November 2013,
Geneva , Switzerland
8. Methods in Clinical Cancer Research - FLIMS Workshop Travel Grant, June
2013, Flims, Switzerland
9. ASCO Travel Grant Comprehensive Cancer Center Vienna, June 2012,
Chicago, USA
10. Forschungsförderungsprogramm "Internationale Kommunikation" der
Österreichischen Forschungsgemeinschaft Travel Grant, September 2012,
Vienna, Austria
EANO-SNO Travel Grant, November 2012, Washington, USA
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