View
52
Download
0
Category
Preview:
DESCRIPTION
Breast Cancer Molecular Profiles Predict Tumor Response of Neoadjuvant Doxorubicin and Paclitaxel, the I-SPY TRIAL (CALGB 150007/150012, ACRIN 6657). L. J. Esserman ,C. Perou, M. Cheang, L. J. van 't Veer, J. Gray, E. Petricoin, K. Conway, L. Carey, A. DeMichele, D. Berry, N. Hylton - PowerPoint PPT Presentation
Citation preview
Breast Cancer Molecular Profiles Predict Tumor Response of
Neoadjuvant Doxorubicin and Paclitaxel, the I-SPY TRIAL
(CALGB 150007/150012, ACRIN 6657)
L. J. Esserman ,C. Perou, M. Cheang, L. J. van 't Veer, J. Gray, E. Petricoin, K.
Conway, L. Carey, A. DeMichele, D. Berry, N. Hylton
I-SPY INVESTIGATORSI-SPY INVESTIGATORS
IInvestigation ofnvestigation ofSSerial studies toerial studies toPPredictredictYYourour
TTherapeuticherapeuticRResponse withesponse withIImaging andmaging andAAndnd
momoLLecularecular analysisanalysis
CALGB INTERSPORE ACRIN NCICB
I SPY I SPY
WITH MY WITH MY
LITTLE LITTLE
EYE . . . . EYE . . . .
. . . A . . . A
BIO-BIO-
MARKER MARKER
BEGIN-BEGIN-
ING ING
WITH XWITH X
. . . .. . . .
Surgery
& RT
Anthracycline Taxane
Tam if ER+
I-SPY 1 Clinical Trial Backbone
Serial MRI ScansSerial Core Biopsies
Layered Imaging/Molecular Biomarker Studies Onto Standard Clinical Care
Trial Endpoints• Early (ASCO POSTER 529)
– MRI response after 1 cycle of chemotherapy• Longest Diameter, Volume
• Intermediate• pCR Pathologic Complete Response• RCB Residual Cancer Burden• % change in MR volume
• Late• 3 year Recurrence Free Survival • 3 year Overall Survival
Residual Cancer Burden
Area (cm x cm) % CANCER CELLULARITY
PRIMARY TUMOR BURDEN
Symmans et al. J Clin Oncol. 2007 Oct 1;25(28):4414-22.
RCB = 1.4 x [fcell x (d1 d2)] 0.17 + [dmet x (1 - (1 - ) LN ) / ] 0.17
AXILLARY NODAL BURDEN+
% CANCER CELLULARITY
PRIMARY TUMOR BURDEN
Number of positive LNsDiameter of largest metastasis (mm)
Area (cm x cm)
Residual Cancer Burden• Integrates several pathologic features
– Lymph node status– Extent of Tumor Bed– Tumor size– Tumor cellularity
• Output is continuous or 4 discrete categories– RCB 0 pCR, no invasive tumor– RCB I scattered residual disease– RCB II moderate tumor burden– RCB III significant tumor burder
Symmans et al JCO 2007Symmans et al JCO 2007
I-SPY 1 Biomarker Platforms
Expression Arrays
)
-2
-1
0
1
2
3
4
5
Genome location
re
lativ
e c
op
y n
um
be
r (
Lo
g2
)
1 3 5 7 9 11 13 15 17 19 21 X
1q 20q
1p 17p 19p
CGH
Protein Arrays (RPMA)
Tissue: Core or Surgical
H&E,IHC,FISH
UNC, Penn UNC, UCSF, NKI GMU
UCSF
Id1 proteinsautoantibodies
phospho proteins
Serum
p53 GeneChip
UNC
• 1042 frozen cores from 201 patients• 1301 paraffin cores from 223 patients • 948 serum samples from 158 patients.
Total Accrual: 237Institution Name Accrual
University of Pennsylvania Medical Center 36
Georgetown University Hospital 4
University of North Carolina 36
Memorial Sloan Kettering Cancer Center 22
University of Washington 5
University of Alabama at Birmingham Medical Center
51
University of Chicago 2
University of Texas Southwestern 14
University of California San Francisco 66
Results
I-SPY: Poor Prognosis Tumors
Mean Tumor Size= 6.0Present as clinical
mass55% < Age 50
70 significant prognosis genes
van´t Veer et al., Nature ,2002
Years since surgery
Rel
apse
-fre
e Pr
opor
tion
Years since surgeryRela
pse-
free
Pro
porti
on
RCB 0 (n=56)RCB 0 (n=56)RCB I (n=18)RCB I (n=18)RCB II (n=86)RCB II (n=86)RCB III (n=41)RCB III (n=41)
pCR (n=58)pCR (n=58)
No pCR (n=157)No pCR (n=157)
Relationship of pCR and RCB with Early Relapse for all I-SPY
Pts
pCR and RCB in context of molecular features
pCR: IHC vs Molecular Subtypes
IHCDistribution
(n = 190)pCR
(n = 190) P-value
HR+HER2- 48% 10%HR+HER2+ 12% 32%HR-HER2+ 12% 50%HR-HER2- 28% 33%
Gene ProfileIntrinsic Subtypes
Distribution ( n = 149)
pCR (n = 144) P-value
Luminal A 29% 2%
<0.0001
Luminal B 19% 15%Her2-enriched 15% 52%
Basal 32% 34%Normal-like 5% 43%
HR = Hormone Receptor
pCR Rates: RNA Classifiers
pCR Rates: DNA Classifiers
pCR and RCB are VERY significant predictors of early relapse in the context of a poor prognosis profile
Log-rank P = 5.5 x 10-7
RCB 0 (n = 16)
RCB I (n = 2)
RCB II (n = 17)
RCB III (n= 9)
Among Basal-like Tumors
Log-rank P = 5.9 x 10-5
RCB III (n = 22)
RCB II (n = 55)
RCB I (n = 10)
RCB 0 (n= 35)
Among NKI-70 High Risk
RCB I (n = 5)
Log-rank P = 4.4 x 10-4
RCB 0 (n = 33)
RCB II (n = 45)
RCB III (n= 20)
Among Activated-Wound Signature
Log-rank P = 4.5 x 10-7
RCB 0 (n= 27)
RCB I (n= 4)
RCB II (n = 24)
RCB III (n = 12)
Among p53 Mutation Profile
Published RNA Signatures• Identify good and poor risk subsets• pCR and RCB are highly predictive of
outcome in the poor risk subsets of all signatures
• Patients in the high and low subsets differ among signatures
• A composite molecular signature can be created
Integrated score is a good predictor of prognosis
Integrated Score: Good Prognosis
Distributed across RCB 0-IIIAll do well REGARDLESS of
RCB
p = 0.158
p = 1.89e-07
Integrated score poor prognosis patients associate
with RCBIntegrated Score,
Intermediate prognosis
P=0.16
Integrated Score, Poor prognosis
P=1.89e-07
Activated Proteins Provide Clues for Future Targeting
• Method:– Reverse Phase Protein Array (RPMA)– All samples laser capture microdissected
• Preliminary findings– pts with pCR: increased phosphorylation of 4EBP1,
eNOS, cAbl, STAT5, EGFR, AKT (p<0.05)• all within a linked EGFR-AKT-mTOR pathway activation
– pts ER+ with poor response: increased phosphorylation of pIRS, pIGFR, p706S (p<0.05).
Observations from I-SPY• LABC have high risk biology
– Minimum tumor size 3cm, mean size of 6cm– 91% are molecularly high risk as defined by NKI 70 gene profile– Not screen detected: 84% are interval cancers (Lin, Abstract 1503)
• Molecular features identify low and high risk subsets– Low risk subsets: low pCR rates, but good outcomes (<5 yrs)– High risk subsets: high pCR rates (28-59%) to std chemo– High risk subsets: response to therapy (pCR, RCB) is highly predictive of early
outcome
• Residual Cancer Burden (RCB)– More refined way to measure pathologic response– Highly correlated with RFS and OS
• MRI Volume change is a non-invasive way to measure pCR– Highly correlated with path CR and RCB: (Hylton, Abstract #529)
Next Steps• The molecular data, with the exception of HER2, does
not yet tell us how to treat poor responders
– Recurrence after pCR limited to HER2+ patients pre-Trastuzumab (6 of 7)
– The I-SPY repository is a resource for such discovery
• We should target improvement in pCR/RCB to improve outcomes
– I-SPY 2 is an adaptive neoadjuvant trial designed to rapidly screen agents and biomarkers to improve pCR/RCB
• Exclude patients with good prognosis profile
BACK-UP
Complete response Partial response Progressive disease
Quantitative and serial measurement of tumor
response by MRI
PreTreatment
PostTreatment
Patients Withdrawn
n=16
Patients Accruedn=237
Patients Available for
Analysisn=221
Patients with pathology assessment after
Neoadjuvant Therapyn=215
Patients without RCBn=14
Patients who didn’t have surgery
n=6
Patients with pCR and RCB
n=201
2 Paraffin Cores
2 Frozen Cores
Initial H&E
IHC FISH
Proteomics
Initial H&E
Tumor Present
RNA
Storage
DNA
Gene ChipFor P53CGH
UNC:Dressler Lab UCSF
GMU:Liotta/Petricoin Lab
Core Remainder
UNC: Perou LabUCSF: Haqq LabMDACC: Pusztai/ Symmans LabNKI: van’t Veer Lab
UCSF: Gray LabUNC: Carey/ Dorsey Lab
Check for Tumor Presence
Check for Tumor Presence
Her2 Protein Over expression
Her2, TopoII Amplification
Gene Expression
UNC: Livasy, Dressler LabPENN: DeMichele Lab
Data uploaded in: NCI caIntegratorUCSC Cancer Genomics Browser UCSC: Haussler, Kent, Zhu, Wang
NCI: caBIG, Madhavan
Tumor
Tissue Distribution & Analyses Schema
Data Integration: NCI caINTEGRATOR
RCB I (n = 5)
Log-rank P = 4.3 x 10-9
RCB 0 (n = 21)
RCB II (n = 18)
RCB III (n= 7)
Among ROR-S High Risk
Integrated score based Integrated score based prognosis classesprognosis classes:: ER+/ER- ER+/ER-
distributionsdistributionsPrognosis (Counts) ER- ER+ Indeterminate Total
Good 2 28 1 31
Intermediate 22 38 4 64
Poor 37 10 2 49
Poor RCB 0 13 6 1 20
Poor RCB I 2 0 0 2
Poor RCB II 12 4 1 17
Poor RCB III 8 0 0 8
Questions
• Does early response help us to predict early relapse?– Complete Pathologic Response: pCR – Residual Cancer Burden: RCB
• How do the molecular signatures impact on the interpretation of pCR and RCB?
0
10
20
30
40
50
60
-4 -3 -2 -1 0 1 2 3 4
Integrated score
Fre
qu
ency
•Based on NKI-70, ROR-S, Wound Healing Signature,, p53 mutation profile: +1 , 0, -1 based upon score; Sum the scores
Poorprognosis
Intermediateprognosis
Goodprognosis
Integrating Molecular Profiles
Recommended