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

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momoLLecularecular analysisanalysis

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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

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-2

-1

0

1

2

3

4

5

Genome location

re

lativ

e c

op

y n

um

be

r (

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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