Neoadjuvant Drug Treatment for Breast Cancer … Output Report.pdf · 2 Executive Summary Neoadjuvant chemotherapy (NAC) may help to further improve survival of stage II and III breast

1

Neoadjuvant Drug Treatment for Breast

Cancer Response Prediction and Response

Monitoring

22

Executive Summary

Neoadjuvant chemotherapy (NAC) may help to further improve survival of stage II and III breast

cancer, as it allows adaptation of the drug regimen to the response of the primary tumor. To do this

with optimal efficacy, biomarkers to guide treatment selection are urgently required, and a strategy to

monitor and quantify the treatment response must be defined. In addition, NAC presents specific

problems and opportunities for radiation oncology, as only part of the usual staging information is

available (e.g., the number of initially tumor-positive lymph nodes is unknown).

This project has addressed these problems and opportunities in a program that involved a total of 479

patients who underwent NAC in the Netherlands Cancer Institute. Candidate biomarkers were

identified in experiments with genetically engineered mice. Genomic and proteomic analyses were

done on biopsies of the primary tumors and additional genomic analyses were done on tumors of

patients with M1 disease. Imaging studies were performed to design and standardize response

monitoring by a combination of Magnetic Resonance and Positron-Emission Tomography and to

employ molecular imaging in an experimental setting .

In the biomarker field, the most definitive progress was made for triple-negative tumors. A aCGH

assay for BRCAness was successfully converted into a low-cost and rapid MLPA test. This test was

validated in retrospective series and put to the final test in an ongoing multi-center phase III trial, that

aims to show that tumors with BRCAness are exquisitely sensitive to DNA damaging chemotherapy.

Additional predictive markers were identified and are currently in varying stages of development. A

functional assay was developed that is able to predict the significance of unclassified variants of the

BRCA1 gene. A strategy to identify genes in clinical tumor samples, whose expression levels may

cause chemotherapy resistance was designed, and validated.

Contrast-enhanced MRI remains the best approach for response monitoring. Its performance can be

significantly enhanced by taking the breast cancer subtype into account, and when automated image

analysis is employed, particularly in the ‘ luminal’ subtype (Computer Assisted Response Prediction,

CARP). The added value of PET/CT was shown to strongly depend on the breast cancer subtype; it

may also help to interpret MRI findings in certain cases. A tumor control probability model for breast

cancer irradiation was completed and a novel image-guided radiotherapy correction strategy was

designed and implemented, which is currently employed in the PAPBI (Preoperative Accelerated

Partial Breast Irradiation) study.

Prof. Dr. S. Rodenhuis

Principal Investigator project BREASTCARE

"Adjuvant chemotherapy is steadily improving the

cure rate of breast cancer. Preoperative

chemotherapy allows adaptation of the regimen to

response and , increasingly, the tailoring of the

treatment to the individual tumor. This project has

yielded novel tools to predict and to monitor

response. Cure is the primary objective: there is

no substitute!"

33

Neoadjuvant drug therapy in breast cancer. The recent fall in breast cancer mortality is mainly

caused by the addition of drug treatment (“adjuvant therapy”) to the local treatment modalities surgery

and radiation therapy. Drug treatment aims to eradicate microscopic disease, the presence of which

cannot be detected at the time of local treatment, but which may eventually give rise to distant

metastases. Adjuvant drug therapy has been shown to reduce breast cancer mortality by nearly 50%.

Both chemotherapy and targeted agents are used and are often administered after local treatment,

when their efficacy in the individual tumor can no longer be determined. The use of adjuvant therapy

before surgery is often called “neoadjuvant therapy”. In this setting, the effect of the drugs on the

tumor can be assessed, and the complete disappearance of all tumor cells at microscopic examination

(pathologic complete remission, or pCR) correlates closely with overall survival. Thus, achieving a

pCR is an appropriate intermediate goal. Current drug treatment schedules achieve pCR in about 10%

of luminal type breast cancers, and in 33% of basal-like and in half of the HER2/neu-positive tumors.

The optimal neoadjuvant treatment regimen is unknown, and is almost certainly different for each

individual tumor. In addition, the optimal dose, duration and sequence of drug combinations are not

usually adapted to individual tumor properties.

Clinical Need Tools

• Array CGH, high-complexity gene expression arrays, MLPA, next generation sequencing,

proteomics

• Conversion of research tool to clinical tests (e.g., employing MLPA)

• Chemotherapy trials in mouse-models, controlled clinical studies in humans

• Computer-aided response prediction, Computerized image interpretation

Improving the survival of stage II

and III breast cancer through:

(i) the selection of chemotherapy

(ii) the adaptation of the regimen

based on response monitoring

Translational Concept

4

Public-Private Partnership

Development of new imaging tools and

specific biomarkers that guide the selection

and adaptation of neoadjuvant

chemotherapy

APPLICATION

SCIENCE

…NEW CURE/CARE SOLUTIONS…TRANSLATE INTO APPLICATIONSGENERATE KNOWLEDGE…

Industrial partnersAcademic partners Supporting Foundations

PATIENT

55

Organization and Partners

Advisory board

ISAC CTMM

CTMMWorkpackage leaders

WP1: Dr. S. Rottenberg (NKI)

WP2: Dr. J.M.M. Jonkers (NKI)

WP3: Dr. F.W. van Leeuwen (NKI)

WP4: Dr. J.M.M. Jonkers (NKI)

WP5: Prof.dr. S. Rodenhuis (NKI)

WP6: J. Foekens (EUMC)

WP7: Prof.dr.M.J. v.d. Vijver (AMC)

WP8: Dr. K.G.A. Gilhuijs (UMCU)

WP9: Dr. J.J. Sonke (NKI)

WP10: Dr. L.F.A. Wessels (NKI)

PartnersCoordinationFinancePublications

SteeringCie

Partner Representatives

CTMM

Project Team

PI: Prof.dr. S. Rodenhuis, PI (NKI)

IP manager: K. Verhoef (NKI)

WP leaders

Industrial partners

Dr. E. Caldenhoven (CTMM)

AMCNKIMRC

EUMC

Philips

CTMM

MSD

UMCU

AD

VIC

ED

EC

ISIO

NS

OP

ER

AT

ION

S

66

Budget: CTMM manages the flow of funds

Project costs:- Personnel

- Materials

- Use of existing equipment

- Investments

- Third parties

- Management (5%)

Project costs:- Personnel

- Materials

- Use of existing equipment

- Investments

- Third parties

- Management (5%)

Funding:

- 25% Academia

- 25% Industrial

- 50% Government Subsidy

Funding:

- 25% Academia

- 25% Industrial

- 50% Government Subsidy

77

CA

SH

CO

ST

SK

IND

CO

ST

SFacts & Figures

Distribution of the

BreastCARE consortium

budgets to perform the

R&D activities

Budget 12.6 M €

Start 2008

End 2014

Partners 7

Academic Partners

Industrial Partners Large

Industrial Partners SME

0

1.000.000

2.000.000

3.000.000

4.000.000

PhD PostDoc Sen. Staff Supp. Staff IT Staff M&S Investments

Academic in kind costs

Industrial in kind costs

0

1.000.000

2.000.000

3.000.000

4.000.000

PhD PostDoc Sen. Staff Supp. Staff IT Staff M&S Investments

Academic cash costs

Industrial cash costs

88

Facts & Figures

Output No

Papers 50 2 papers in submission - mean impact factor all published BREASTCARE papers: 6,9

Theses 3 7 planned for 2015/2016

Personal Grants 1 2011; Vidi for Sven Rottenberg; 2014 Vici for Jos Jonkers

Patent

Applications2

2 IDF/patent applications in preparation: WP1 – XIST gene expression predicts chemotherapy sensitivity; WP3 - Development of

hybrid imaging labels for PET and fluorescence imaging

Spin-off

Companies0

Raising Capital

(> 1 M€)4

ERC Grant 2012 (F.W. van Leeuwen, NKI) - ERC advanced Grant 2011 (Prof. Dr. J.A. Foekens, EMC) – EU FP7 project

ARTFORCE 2011 (Jan-Jakob Sonke, NKI) – NOW Zenith Roadmap subsidy 2012, 18,6 miljon euro for Mouse Clinic for Cancer

and Aging (Jos Jonkers, NKI).

Awards 1 AACR – Translational Cancer Medicine Award for Sven Rottenberg in 2010;

Public

Media1 Press release 2013 – Test classificeert DNA varianten erfelijke borstkanker (NKI)

Budget 12.6 M €Start 2008End 2014Partners 7Charity 0Persons 46FTE 83 (5 years period)

99

1. Kuil J. et al (2012), Chem. Soc. Rev., 2012, 41, 5239-5261

2. Ronde de J. et al (2010), Lancet Oncology 11(4):339-49

3. Jaspers J.E. et al (2013), Cancer Discov. 2013 Jan;3(1):68-81

4. Bouwman, P. et al ( 2013), Cancer Discov. 2013 Oct;3(10):1142-55

5. Loo C.E. et al (2011), J Clin Oncol. 2011 Feb 20;29(6):660-6.

Highest Impact Papers – mean 21,8

• 2011: CTMM researchers at NKI and UMCU have shown that the accuracy to monitor treatment response of positron emission tomography (PET) and magnetic resonance imaging (MRI) depends on the breast-cancer subtype.

• 2012: Workers at the NKI generate models of mouse mammary tumors that cannot acquire drug resistance by restoration of BRCA1 function or by Pgp-mediated drug efflux , allowing the study of additional clinically relevant resistance mechanisms

• 2012: CTMM researches at MRC Holland and NKI collaborate to develop and validate a simple MLPA test that detects ‘BRCAness’ and BRCA1 promoter methylation in small tumor samples.

• 2013: CTMM Investigators at the NKI develop and validate a screening tool that links detects genes whose expression levels in tumor tissue are closely linked with clinical chemotherapy resistance.

• 2013: CTMM investigators at the EMC complete a comparative tissue proteomics pipeline for in-depth proteome profiling and biomarker discovery using high resolution mass spectrometry

• 2013: CTMM researchers at NKI have shown that in patients with ER-positive breast cancer receiving neoadjuvantchemotherapy, MRI after chemotherapy is a better predictor of recurrence-free survival than pathological complete remission (pCR)

• 2013: CTMM researchers at the NKI have developed a functional assay that determines the clinical significance of unclassified BRCA1 variants in germ line DNA .

• 2014: Investigators at the NKI have established a database of a large cohort of patients who underwent neoadjuvantchemotherapy for stage II or III breast cancer (N > 500) , linked to databases with molecular data of pre-chemotherapy tumor biopsies, MRI and PET-CT imaging details, and many other features.

Scientific Value Creation - Breakthroughs

Mean Impact Factor

5,7

4,4

0 2 4 6 8 10

CTMM - oncology

International - oncology

1010

Scientific Value Creation - Theses

BreastCARE Thesis Partner Year

J.J de Ronde NKI 2013

B.B. Koolen NKI 2013

J.E. Jaspers NKI 2013

K.E. Pengel NKI planned

H.R. Zhang NKI planned

A.M.C. Miquel Cases NKI planned

C.E. Loo NKI planned

W. Chen NKI planned

C.D. Savci Heijink AMC planned

R.B.H. Braakman EMC planned

11

Animal

ModelsData-driven

Methods

Cohorts

Biobanks

Molecular

Diagnostics

& Imaging

Scientific Value Creation - Infrastructure

• Spontaneous K14cre;Brca1F/F;p53F/F mouse model

for hereditary breast cancer (NKI)

• Novel genetically engineered cell lines and mouse

models for breast cancer, including the development

of an ER+ breast cancer mouse model (NKI)

• Genetically engineered mouse models for Brca1-

mutated hereditary breast cancer and E-cadherin-

mutated lobular breast cancer (NKI)

• Generation of mouse mammary tumors that cannot

acquire drug resistance by restoration of BRCA1

function or Pgp-medited drug efflux (NKI)

• Introduction of a tumor cell-specific GFP reporter to

discriminate tumor from stromal cells (NKI)

• CARP (Computer Aided Response Prediction)

(UMCU)

• DIDS (Detection of chemotherapy resistance

markers by imbalance of differential signals) (NKI)

• Data Mining in Imaging

(combining principal component analysis,

Bayesian neural networks and Binary logistic

regression) (UMCU)

• Radiation therapy planning infrastructure to

tailor the dose distribution to specific residual

microscopic disease distributions and residual

geometric uncertainties (NKI, Philips).

• N08RMB imaging database: prospective cohort of

patients undergoing neoadjuvant chemotherapy

N=295 (NKI & UMCU)

• Neoadjuvant chemotherapy patients – clinical

database: N= 479 (NKI)

• Pre-neoadjuvant chemotherapy tumor bank (NKI)

• A collection of more than 1000 fresh-frozen samples

of drug-sensitive or –resistant mouse mammary

tumors. Of these samples FFPE material and small

tumor fragments for orthotopic transplantation into

syngeneic animals is available (NKI)

• Development of a comparative tissue proteomics

pipeline for in-depth proteome profiling and biomarker

discovery using high resolution mass spectrometry

(EMC)

• MLPA for BRCAness and for BRCA1 methylation

(NKI, MRC Holland)

• Functional test for unclassified BRCA1 variants (NKI)

• MRI/PET-CT combination – Response prediction

(NKI/ UMCU)

• A proteomics signature to predict neo-adjuvant and

advanced chemotherapy resistance in ER negative

breast cancer’. (EMC)

• Dose calculation on CBCT scans in Pinnacle

treatment planning system and advanced CBCT

reconstruction techniques for improved target

definition (NKI, Philips)

1212

Clinical and Economic Value Creation of

BREASTCARE

New ‘products’ for clinical care

1313

Main Product Pipelines

Discovery biomarkers

Selection of promising markers

Clinical & ExperimentalVerification

Final measurement platform/protocol

Clinical Validationplatform

Not financed by CTMM

Partially financed by CTMM

Not financed by CTMM

Partially financed by CTMM

MLPA BRCAness

Functional test

for unclass.

BRCA1 variants

Prot. Profile

anthracycline

resistance

PI3K pathway

Perturbation

(NGS)

Comp. aided

response pred.

Image-guided

preop. breast

irradiation

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Thera

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innovatio

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Number Breast cancer patientsB

Yearly Costs M€

Main results in CTMM

• The 191-probe aCGH BRCA1-like classifier was

translated into a 34-probe MLPA assay

• The MLPA assay performs equally well as the

aCGH to detect a BRCA1-like pattern in both

clinical genetic testing as in treatment benefit

prediction.

• In a randomized controlled trial, patients with a

BRCA1-like tumor showed a remarkably better

survival upon intensified alkylating chemotherapy

compared to standard dose.

• The assay is rapid and robust, can be multiplexed

and works well with FFPE material, prerequisites

for a clinical application.

MLPA for BRCAness in triple-negative tumors

BRCA1 and BRCA2 can be inactivated in sporadic

cancers as well, which is referred to BRCAness. In

BRCA1 mutation carriers breast tumour samples

have a characteristic pattern of DNA gains and

losses. BRCA1ness profile is present in about half of

all triple negative sporadic breast cancers and is

predictive for benefit from intensified chemotherapy

Product

For clinical purposes, it is desirable to have a simple

test based on the MLPA technology of MRC

Holland. Such a test has been developed in 2010

This MLPA assay is rapid and robust, it can easily

be multiplexed, and it works well with DNA derived

from paraffin-embedded tissues.

Leading company:

MRC Holland

Current Diagnostics

Currently, the BRCA1-like aCGH assay is used in

two multicenter clinical trials. Patient biopsies are

tested for BRCAness, and BRCA1-like patients are

randomised between different chemotherapy

regimens. As such, the aCGH BRCA1-like assay

has already impact on clinical desicion making. In

addition the assay is used in the clinical genetic

testing.

Future Outlook

• Selection of patients with BRCA1/2-like breast

cancer for treatment with intensified chemotherapy

Progess obtained in translational pipeline

PATIENTPARTNERSHIPPRODUCT

DiscoveryPathwaysbiomarkers

Market accesClinicalEvaluationcohorts

DemonstratorDevelopmentdevice

SelectionPathwaysbiomarkers

Progress within CTMM

2014

Treatment& monitoring

Screeningprevention

Patientstratification

Earlydiagnosis

2008

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Identification of clinical limitations:

Researchers at NKI and UMCU have shown that

the accuracy to monitor treatment response using

positron emission tomography (PET) and

magnetic resonance imaging (MRI) depends on

the breast-cancer subtype.

Merit of computerized image interpretation:

Automated analysis of treatment response using

computer interpretation is not affected by breast

cancer subtype and significantly raises the

accuracy to monitor treatment response in ER-

positive breast cancers.

Quality of Life (QoL):

Better tools to monitor tumor response to

therapy will reduce exposure of patients to

ineffective drug regimens, avoiding side

effects that reduce QoL and offering them a

second change for cure

Accessibility:

Ultimately, all doctors must be able to

purchase this technology and have access to

these tools

Computer-Aided Response Prediction (CARP)

Breast cancer response monitoring

PET/MR response Imaging interpretation for

tumor response monitoring based on MRI

and PET/CT is complex and prone to

differences in interpretation between medical

specialists. This limits the efficacy to switch

patients away from ineffective drug regimens,

hence compromising benefits of neoadjuvant

drug therapy.

CARP workstation

It is desirable to have a standardized tool to

assess the risk of a breast cancer treatment

failure on the basis of MRI and PET/CT early

after initiating drug therapy. This tool should

minimize user interaction in order to reduce

clinical workload and to achieve uniformity

across medical centres worldwide. Together

with the University Medical Center Utrecht,

Philips has developed such a system, known

as CARP (Computer-Assisted Response

Prediction).

Future Outlook

- Prospective validation

- Incorporation into commercial products








2014


Screeningprevention


Earlydiagnosis

2009

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Setup and calibration:

Deviations in the trajectory of the biopsy needle

have been calibrated and stored in a correction

table, taking tangential forces into account

exerted on the needle tip by surrounding breast

tissue as function of distance to the template.

Longitudinal image registration:

Breast images in compressed and uncompressed

state were successfully registered using robust

automated deformable registration. Proof of

concept to detect inhomogeneity in Her2/Neu

receptor status has been reported1.

1. Dmitriev et al., PMB, 1221-33, 2013

Quality of Life (QoL):

Sampling of the most malignant part of the

tumor may speed up discovery of predictive

tissue biomarkers and help reduce exposure

of patients to potentially ineffective drug

regimens, thus improving their quality of life

and increasing their changes of disease-free

overall survival.

Accessibility:

We currently have a prototype of the system

and are in the process of defining its potential

place in the clinical logistics trajectory.

MRI-PET/CT Breast Biopsy System

Breast cancer biopsy

Breast cancer is a highly heterogeneous

disease. Systemic drug therapy is tailored to

breast cancer subtype that is defined by the

status of the receptors on the cancer-cell

membranes. Tissue sampling by core needle

biopsy may yield an estimate of breast

cancer subtype that is not representative for

the whole tumor, thus potentially limiting the

efficacy of neoadjuvant drug therapy.

MRI-PET/CT biopsy system

In collaboration with Phillips, a prototype

breast biopsy system was developed to

obtain tissue samples guided to the most

representative part of the cancer under

PET/CT and MRI guidance. The system is

based on a replica of the 7-channel MRI

breast biopsy coil, and uses advanced

automated deformable registration of PET/CT

and previously acquired MRI.

Future Outlook

- Define the potential place of this technology in

the workflow logistics of breast cancer therapy








2014


Screeningprevention


Earlydiagnosis

2010

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Number patients per year: 20 families


Assay development:

A functional assay was developed to test pathogenicity

of BRCA1 variants of uncertain significance (VUS).

This assay is based on complementation of inducible

Brca1-knockout embryonic stem cells with human

BRCA1 genes.

Demonstrator development:

The assay was validated using various BRCA1

variants of known significance. The assay system was

subsequently used to classify 74 BRCA1 VUS.Quality of Life (QoL):

Better classification of BRCA1 mutation carriers

results in better QoL. Women with non-pathogenic

mutations are not exposed to prophylactic

mastectomy and ovariectomy. Women with

pathogenic mutations may opt for increased

cancer surveillance or preventive surgery.

Accessibility:

Additional funding is currently requested from

NutsOhra to run the assay for families with

BRCA1 VUS.

Functional test for unclassified BRCA1 variants

Approximately 2–3% of all breast and ovarian

cancer cases are attributable to mutations in

BRCA1. For most BRCA1 mutations it is known

whether they increase the risk of cancer or not.

However, for approximately 10% of all BRCA1

mutations the effect is unclear. The NKI has now

developed a functional test to determine which of

these so-called unclassified mutations result in a

defective BRCA1 gene and which don’t. Using this

test, they have determined the effect of 74 of

these unclassified BRCA1 mutations. This

information may provide clarity concerning the

risks of cancer for the patient and her relatives.

The test may also provide information for the

tailored treatment of breast or ovarian cancer

patients with unclassified BRCA1 mutations.

Current Diagnostics

In current clinical practice, genetic counselors

determine the hereditary breast and ovarian

cancer risk of women via assessment of medical

records and family history of cancer, and via

genetic testing of the BRCA1 and BRCA2 genes.

This information is used to estimate the risk of

breast and ovarian cancer for the family members

and give advice on medical management, which

can range from increased cancer surveillance to

preventive surgery to reduce cancer risk.

Future Outlook:

• Functional classification of all BRCA1 VUS in the

Netherlands








2014


Screeningprevention


Earlydiagnosis

2008

18

(1) Von Minckwitz et al (2013).* Pp - Per patient. US: ultrasound, MRI: magnetic resonance imaging, PET/CT: positron emission

tomography/computed tomography, ICER: Incremental cost-effectiveness ratio – the comparator is the standard of care.

Note: Differences in costs and QALYs between tables are due to differences in the chemotherapeutic regimens used (Table 1: TAC and

switch to NX ; table 2: ddAC and switch ddDC in HER2- patients, and PTC in HER2+.

Population Monitoring Costs (pp*) QALYs (pp*) ICERCost-

effective?Source

All breast

cancer

No 103.625€ 12.23 - - (1)

Yes 111.441€ 14.25 3.875 Yes (1)

1. Switching chemotherapy based on ultrasound is contributing

to cost-effectiveness

PopulationMonitoring Costs (pp*) QALYs (pp*) ICER

Cost-

effective?Source

All breast

cancerYes 85.716 € 7.99 - - (1)

Stratified by

ER statusYes 85.526€ 8.15

Dominant

(-1.174)Yes (1)

2. Switching chemotherapy by breast cancer subgroups is more cost-

effective.

Value of response guidance by imaging

18

19

3. Switching chemotherapy based on MRI and PET/CT (separately) is

expected to be cost-effective, when compared to US, for its higher

sensitivity (MRI&PET/CT) and specificity (PET/CT).

with additional costs (fusion software (~110.000 € ), training of the

personnel (time & creation of new working paths), and (often) purchase of a

new scanner (MRI or PET/CT ~ 3 million €)) is likely to be cost-effective if:

�The combined PET/MRI parameter(s) have higher sensitivity and

specificity than that of cheaper alternatives (e.g. ultrasound, MRI, etc)

�Research focuses on subpopulations of breast cancer.

(2) CTMM - Loo et al (2011), (3) Cheng X et al (2012). * Assuming a hospital with the activity of the NKI (195 NACT /year) and buying

one scanner. T.b.d: To be determined.

PopulationMonitoring

techniqueCosts (pp*) QALYs (pp*) ICER

Cost-

effective?Source

All breast

cancer

US 85.716 € 7.99 - - (1)

MRI 84.994 € 7.69 2.436 Yes (2)

PET/CT 83.729 € 8.40Dominant

( -4.884)Yes (3)

PET/MRI

(CARP SOFTWARE)99.641 €* t.b.d t.b.d t.b.d assumption

CARP SOFTWARE?

19

20

Value of novel biomarkers for response prediction:

MLPA for BRCAness, MLPA for XIST and IHC for 53BP1

Population Biomarker Costs (pp*) QALYs (pp*) ICER Cost-

effective?

Probability of

cost-

effectiveness*

Source

Triple

negative

breast

cancer

(TNBC)

No 29.439 € 7.30 - - 5% (4)

BRCAness

(MLPA)

63.859 € 10.23 11.742 Yes 23% (4)

BRCAness

(MLPA) +

XIST (MLPA)

+ 53BP1

(IHC)

49.929 € 9.10 11.380 Yes 19% (4)

(4) CTMM & Linn’s lab data (NKI). * Under the designed threshold in the Netherlands, 80.000€.

Using the BRCAness MLPA alone (11.742 €/QALY) or combined with XIST

and 53BP1 (11.380 €/QALY) has the potential to be cost-effective. Yet, due

to the early stage of development of these biomarkers, there is a high

degree of uncertainty in these results.

�Further research on the performance of the biomarkers and on the

survival benefit, would increase its probability of cost-effectiveness.

20

2121

Academic Medical Center (AMC) Amsterdam

Erasmus University Medical Center (EUMC) Rotterdam

Netherlands Cancer Institute (NKI) Amsterdam

University Medical Center Utrecht (UMCU) Utrecht

Merck Sharp & Dohme BV (MSD) Oss

MRC-Holland BV Amsterdam

Royal Philips Eindhoven

Partners

2222

List of Publications

1. Liu NQ, Stingl C, Look MP, Smid M, Braakman RB, De Marchi T, Sieuwerts AM, Span PN, Sweep FC, Linderholm BK, Mangia A, Paradiso A, Dirix LY, Van Laere SJ, Luider TM, Martens JW, Foekens JA, Umar A. Comparative proteome analysis revealing an 11-protein signature for aggressive triple-negative breast cancer. J Natl Cancer Inst. 2014 Feb;106(2):djt376

2. Chen W, Gilhuijs K, Stroom J, Bartelink H, Sonke JJ. A simulation framework for modeling tumor control probability in breast conserving therapy. Radiother Oncol. 2014 May;111(2):289-95

3. Zhang H, Tan W, Sonke JJ. Effect of compressed sensing reconstruction on target and organ delineation in cone-beam CT of head-and-neck and breast cancer patients. Radiother Oncol. 2014 Sep;112(3):413-7

4. Vollebergh MA, Lips EH, Nederlof PM, Wessels LF, Wesseling J, Vd Vijver MJ, de Vries EG, van Tinteren H, Jonkers J, Hauptmann M, Rodenhuis S, Linn SC. Genomic patternsresembling BRCA1- and BRCA2-mutated breast cancers predict benefit of intensified carboplatin-based chemotherapy. Breast Cancer Res. 2014 May 15;16(3):R47

5. Pengel KE, Koolen BB, Loo CE, Vogel WV, Wesseling J, Lips EH, Rutgers EJ, Valdés Olmos RA, Vrancken Peeters MJ, Rodenhuis S, Gilhuijs KG. Combined use of ¹⁸F-FDG PET/CT andMRI for response monitoring of breast cancer during neoadjuvant chemotherapy. Eur J Nucl Med Mol Imaging. 2014 Aug;41(8):1515-24

6. Koolen BB, Pengel KE, Wesseling J, Vogel WV, Vrancken Peeters MJ, Vincent AD, Gilhuijs KG, Rodenhuis S, Rutgers EJ, Valdés Olmos RA. Sequential (18)F-FDG PET/CT for earlyprediction of complete pathological response in breast and axilla during neoadjuvant chemotherapy. Eur J Nucl Med Mol Imaging. 2014 Jan;41(1):32-40

7. Koolen BB, van der Leij F, Vogel WV, Rutgers EJ, Vrancken Peeters MJ, Elkhuizen PH, Valdés Olmos RA. Accuracy of 18F-FDG PET/CT for primary tumor visualization and staging in T1 breast cancer. Acta Oncol. 2014 Jan;53(1):50-7

8. Jaspers JE, Kersbergen A, Boon U, Sol W, van Deemter L, Zander SA, Drost R, Wientjens E, Ji J, Aly A, Doroshow JH, Cranston A, Martin NM, Lau A, O'Connor MJ, Ganesan S, Borst P, Jonkers J, Rottenberg S. Loss of 53BP1 causes PARP inhibitor resistance in Brca1-mutated mouse mammary tumors. Cancer Discov. 2013 Jan;3(1):68-81

9. Bouwman P, van der Gulden H, van der Heijden I, Drost R, Klijn CN, Prasetyanti P, Pieterse M, Wientjens E, Seibler J, Hogervorst FB, Jonkers J. A high-throughput functionalcomplementation assay for classification of BRCA1 missense variants. Cancer Discov. 2013 Oct;3(10):1142-55

10.de Ronde JJ, Rigaill G, Rottenberg S, Rodenhuis S, Wessels LF. Identifying subgroup markers in heterogeneous populations. Nucleic Acids Res. 2013 Nov;41(21):e200

11.Warmoes M, Jaspers JE, Xu G, Sampadi BK, Pham TV, Knol JC, Piersma SR, Boven E, Jonkers J, Rottenberg S, Jimenez CR. Proteomics of genetically engineered mouse mammarytumors identifies fatty acid metabolism members as potential predictive markers for cisplatin resistance. Mol Cell Proteomics. 2013 May;12(5):1319-34

12.de Ronde JJ, Lips EH, Mulder L, Vincent AD, Wesseling J, Nieuwland M, Kerkhoven R, Vrancken Peeters MJ, Sonke GS, Rodenhuis S, Wessels LF. SERPINA6, BEX1, AGTR1, SLC26A3, and LAPTM4B are markers of resistance to neoadjuvant chemotherapy in HER2-negative breast cancer. Breast Cancer Res Treat. 2013Jan;137(1):213-23

13.Liu NQ1, Dekker LJ, Stingl C, Güzel C, De Marchi T, Martens JW, Foekens JA, Luider TM, Umar A. Quantitative proteomic analysis of microdissected breast cancer tissues: comparison of label-free and SILAC-based quantification with shotgun, directed, and targeted MS approaches. J Proteome Res. 2013 Oct 4;12(10):4627-41

14.Lips EH, Mulder L, Oonk A, van der Kolk LE, Hogervorst FB, Imholz AL, Wesseling J, Rodenhuis S, Nederlof PM. Triple-negative breast cancer: BRCAness and concordance of clinicalfeatures with BRCA1-mutation carriers. Br J Cancer. 2013 May 28;108(10):2172-7

15.Rigter LS, Loo CE, Linn SC, Sonke GS, van Werkhoven E, Lips EH, Warnars HA, Doll PK, Bruining A, Mandjes IA, Vrancken Peeters MJ, Wesseling J, Gilhuijs KG, Rodenhuis S. Neoadjuvant chemotherapy adaptation and serial MRI response monitoring in ER-positive HER2-negative breast cancer. Br J Cancer. 2013 Dec 10;109(12):2965-72

16.Lips EH, Mulder L, de Ronde JJ, Mandjes IA, Koolen BB, Wessels LF, Rodenhuis S, Wesseling J. Breast cancer subtyping by immunohistochemistry and histological grade outperformsbreast cancer intrinsic subtypes in predicting neoadjuvant chemotherapy response. Breast Cancer Res Treat. 2013 Jul;140(1):63-71

17.Koolen BB, Valdés Olmos RA, Vogel WV, Vrancken Peeters MJ, Rodenhuis S, Rutgers EJ, Elkhuizen PH. Pre-chemotherapy 18F-FDG PET/CT upstages nodal stage in stage II-III breastcancer patients treated with neoadjuvant chemotherapy. Breast Cancer Res Treat. 2013 Sep;141(2):249-54

18.Koolen BB, Valdés Olmos RA, Wesseling J, Vogel WV, Vincent AD, Gilhuijs KG, Rodenhuis S, Rutgers EJ, Vrancken Peeters MJ. Early assessment of axillary response with ¹⁸F-FDG PET/CT during neoadjuvant chemotherapy in stage II-III breast cancer: implications for surgical management of the axilla. Ann Surg Oncol. 2013 Jul;20(7):2227-35

19.Buckle T, Kuil J, van den Berg NS, Bunschoten A, Lamb HJ, Yuan H, Josephson L, Jonkers J, Borowsky AD, van Leeuwen FW. Use of a single hybrid imaging agent for integration of target validation with in vivo and ex vivo imaging of mouse tumor lesions resembling human DCIS. PLoS One. 2013;8(1):e48324

20.Dmitriev ID, Loo CE, Vogel WV, Pengel KE, Gilhuijs KG. Fully automated deformable registration of breast DCE-MRI and PET/CT. Phys Med Biol. 2013 Feb 21;58(4):1221-33

21.Koolen BB, Pengel KE, Wesseling J, Vogel WV, Vrancken Peeters MJ, Vincent AD, Gilhuijs KG, Rodenhuis S, Rutgers EJ, Valdés Olmos RA. FDG PET/CT during neoadjuvantchemotherapy may predict response in ER-positive/HER2-negative and triple negative, but not in HER2-positive breast cancer. Breast. 2013 Oct;22(5):691-7

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22.Zhang H, Sonke JJ. Directional sinogram interpolation for sparse angular acquisition in cone-beam computed tomography. J Xray Sci Technol. 2013;21(4):481-96

23.Braakman RBH, Umar A. New developments in targeted analysis of protein posttranslational modifications,. Current Proteomics,2013, 10,00-00

24.Kuil J, Buckle T, van Leeuwen FW. Imaging agents for the chemokine receptor 4 (CXCR4). Chem Soc Rev. 2012 Aug 7;41(15):5239-61

25.Rottenberg S, Borst P. Drug resistance in the mouse cancer clinic. Drug Resist Updat. 2012 Feb-Apr;15(1-2):81-9

26.Rottenberg S, Vollebergh MA, de Hoon B, de Ronde J, Schouten PC, Kersbergen A, Zander SA, Pajic M, Jaspers JE, Jonkers M, Lodén M, Sol W, van der Burg E, Wesseling J, Gillet JP, Gottesman MM, Gribnau J, Wessels L, Linn SC, Jonkers J, Borst P. Impact of intertumoral heterogeneity on predicting chemotherapy response of BRCA1-deficient mammary tumors. Cancer Res. 2012 May 1;72(9):2350-61

27.Liu NQ, Braakman RB, Stingl C, Luider TM, Martens JW, Foekens JA, Umar A. Proteomics pipeline for biomarker discovery of laser capture microdissected breast cancer tissue. J Mammary Gland Biol Neoplasia. 2012 Jun;17(2):155-64

28.van Miltenburg MH, Jonkers J. Using genetically engineered mouse models to validate candidate cancer genes and test new therapeutic approaches. Curr Opin Genet Dev. 2012 Feb;22(1):21-7.

29.Oonk AM, van Rijn C, Smits MM, Mulder L, Laddach N, Savola SP, Wesseling J, Rodenhuis S, Imholz AL, Lips EH. Clinical correlates of 'BRCAness' in triple-negative breast cancer of patients receiving adjuvant chemotherapy. Ann Oncol. 2012 Sep;23(9):2301-5

30.Chen W, Stroom J, Sonke JJ, Bartelink H, Schmitz AC, Gilhuijs KG. Impact of negative margin width on local recurrence in breast conserving therapy. Radiother Oncol. 2012 Aug;104(2):148-54

31.Rottenberg S, Jonkers J. MEK inhibition as a strategy for targeting residual breast cancer cells with low DUSP4 expression. Breast Cancer Res. 2012 Nov 5;14(6):324

32.Koolen BB, Vrancken Peeters MJ, Wesseling J, Lips EH, Vogel WV, Aukema TS, van Werkhoven E, Gilhuijs KG, Rodenhuis S, Rutgers EJ, Valdés Olmos RA. (2012) Association of primary tumour FDG uptake with clinical, histopathological and molecular characteristics in breast cancer patients scheduled for neoadjuvant chemotherapy. Eur J Nucl Med Mol Imaging. 2012 Dec;39(12):1830-8.

33.Braakman RB, Tilanus-Linthorst MM, Liu NQ, Stingl C, Dekker LJ, Luider TM, Martens JW, Foekens JA, Umar A. Optimized nLC-MS workflow for laser capture microdissected breastcancer tissue. J Proteomics. 2012 Jun 6;75(10):2844-54

34.Lips EH, Mulder L, de Ronde JJ, Mandjes IA, Vincent A, Vrancken Peeters MT, Nederlof PM, Wesseling J, Rodenhuis S. Neoadjuvant chemotherapy in ER+ HER2- breast cancer: response prediction based on immunohistochemical and molecular characteristics. Breast Cancer Res Treat. 2012 Feb;131(3):827-36

35.Lips EH, Mukhtar RA, Yau C, de Ronde JJ, Livasy C, Carey LA, Loo CE, Vrancken-Peeters MJ, Sonke GS, Berry DA, Van't Veer LJ, Esserman LJ, Wesseling J, Rodenhuis S, Shelley Hwang E; I-SPY TRIAL Investigators. Lobular histology and response to neoadjuvant chemotherapy in invasive breast cancer. Breast Cancer Res Treat. 2012 Nov;136(1):35-43

36.Koolen BB, Vrancken Peeters MJ, Aukema TS, Vogel WV, Oldenburg HS, van der Hage JA, Hoefnagel CA, Stokkel MP, Loo CE, Rodenhuis S, Rutgers EJ, Valdés Olmos RA. 18F-FDG PET/CT as a staging procedure in primary stage II and III breast cancer: comparison with conventional imaging techniques. Breast Cancer Res Treat. 2012 Jan;131(1):117-26

37.Koolen BB, Valdés Olmos RA, Elkhuizen PH, Vogel WV, Vrancken Peeters MJ, Rodenhuis S, Rutgers EJ. Locoregional lymph node involvement on 18F-FDG PET/CT in breast cancerpatients scheduled for neoadjuvant chemotherapy. Breast Cancer Res Treat. 2012 Aug;135(1):231-40

38.Gilhuijs KGA, Dmitriev I, Pengel KE, Koolen BB, Loo CE. Automatische PET/MR registratie van borstkanker voor het monitoren van therapie response. Gamma

39.Zhang H, Sonke JJ. Directional interpolation for motion weighted 4D cone-beam CT reconstruction. Med Image Comput Comput Assist Interv. 2012;15(Pt 1):181-8.

40.Loo CE, Straver ME, Rodenhuis S, Muller SH, Wesseling J, Vrancken Peeters MJ, Gilhuijs KG. Magnetic resonance imaging response monitoring of breast cancer during neoadjuvantchemotherapy: relevance of breast cancer subtype. J Clin Oncol. 2011 Feb 20;29(6):660-6.

41.Lips EH, Mulder L, Hannemann J, Laddach N, Vrancken Peeters MT, van de Vijver MJ, Wesseling J, Nederlof PM, Rodenhuis S. Indicators of homologous recombination deficiency in breast cancer and association with response to neoadjuvant chemotherapy. Ann Oncol. 2011 Apr;22(4):870-6.

42.Huijbers IJ, Krimpenfort P, Berns A, Jonkers J. Rapid validation of cancer genes in chimeras derived from established genetically engineered mouse models. Bioessays. 2011 Sep;33(9):701-10

43.Lips EH, Laddach N, Savola SP, Vollebergh MA, Oonk AM, Imholz AL, Wessels LF, Wesseling J, Nederlof PM, Rodenhuis S. Quantitative copy number analysis by Multiplex Ligation-dependent Probe Amplification (MLPA) of BRCA1-associated breast cancer regions identifies BRCAness. Breast Cancer Res. 2011 Oct 27;13(5):R107

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44.Beekman CA, Buckle T, van Leeuwen AC, Valdés Olmos RA, Verheij M, Rottenberg S, van Leeuwen FW. Questioning the value of (99m)Tc-HYNIC-annexin V based response monitoring after docetaxel treatment in a mouse model for hereditary breast cancer. Appl Radiat Isot. 2011 Apr;69(4):656-62

45.de Ronde J, Wessels L, Wesseling J. Molecular subtyping of breast cancer: ready to use? Lancet Oncol. 2010 Apr;11(4):306-7

46.Pajic M1, Kersbergen A, van Diepen F, Pfauth A, Jonkers J, Borst P, Rottenberg S. Tumor-initiating cells are not enriched in cisplatin-surviving BRCA1;p53-deficient mammary tumor cellsin vivo. Cell Cycle. 2010 Sep 15;9(18):3780-91

47.Aukema TS, Straver ME, Peeters MJ, Russell NS, Gilhuijs KG, Vogel WV, Rutgers EJ, Olmos RA. (2010) Detection of extra-axillary lymph node involvement with FDG PET/CT in patientswith stage II-III breast cancer. (Eur J Cancer. 2010 Dec;46(18):3205-10. doi: 10.1016/j.ejca.2010.07.034. Epub 2010 Aug 16

48.Straver ME, Aukema TS, Olmos RA, Rutgers EJ, Gilhuijs KG, Schot ME, Vogel WV, Peeters MJ. Feasibility of FDG PET/CT to monitor the response of axillary lymph node metastases toneoadjuvant chemotherapy in breast cancer patients. Eur J Nucl Med Mol Imaging. 2010 Jun;37(6):1069-76.

49.de Ronde JJ, Hannemann J, Halfwerk H, Mulder L, Straver ME, Vrancken Peeters MJ, Wesseling J, van de Vijver M, Wessels LF, Rodenhuis S. Concordance of clinical and molecularbreast cancer subtyping in the context of preoperative chemotherapy response. Breast Cancer Res Treat. 2010 Jan;119(1):119-26

50.de Ronde JJ, Klijn C, Velds A, Holstege H, Reinders MJ, Jonkers J, Wessels LF. KC-SMARTR: An R package for detection of statistically significant aberrations in multi-experiment aCGHdata. BMC Res Notes. 2010 Nov 11;3:298.

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Abbreviations

AACR American Association for Cancer Research

BRCA BReast CAncer

CARP Computer Assisted Response Prediction

CBCT Cone Beam-CT

CGH Complete Genome Hybridization

CT Computer Tomogram

ER Estrogen Receptor

ERC European Research Council

FFPE Formalin-fixed, paraffin-embedded

GFP Green Fluorescent Protein

HER2 Human Epidermal growth factor Receptor

ICER Incremental Cost-Effectiveness Ratio

IDF Invention Disclosure Form

IHC Immunohistochemistry

ISAC International Scientific Advisory Committee

MLPA Multiplex Ligation-dependent Probe Amplification

MRI Magnetic Resonance Imaging

NAC Neoadjuvant Chemotherapy

NGS Next Generation Sequencing

pCR pathologic Complete Remission

PET Positron Emission Tomography

PI3K Phosphoinositide 3-kinase

SME Small and Medium-sized Enterprise

VUS Variants of Unknown Significance

QALYs Quality-Adjusted Life Years

XIST X-inactive Specific Transcript

2626

Prof. R.S. Reneman, Ph.D. (Chair)

Prof. J.A. Andersson, M.D., Ph.D.

J.P. Armand, M.D., MSc.

R.S.B. Balaban, Ph.D.

J.B. Bassingthwaighte, Ph.D.

R.G. Blasberg, M.D.

Prof. L. Degos

H. Hermjakob, Ph.D.

W.J. Jagust, Ph.D.

Prof. D.J. Kerr

Prof. U.D.A. Landegren, M.D., Ph.D.

R.I. Pettigrew, M.D., PhD.

A. Tedgui, Ph.D.

Prof. T.P. Young

Co funded by

International

Scientific Advisory

Committee

Center for Translational

Molecular Medicine

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5656 AG Eindhoven, The Netherlands

T +31 (0)40 800 23 00

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September 1, 2015

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Neoadjuvant Drug Treatment for Breast Cancer … Output Report.pdf · 2 Executive Summary Neoadjuvant chemotherapy (NAC) may help to further improve survival of stage II and III breast