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L. J. Esserman ,C. Perou, M. Cheang, L. J. van 't Veer, J. Gray, E. Petricoin, K. Conway,

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

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L. J. Esserman ,C. Perou, M. Cheang, L. J. van 't Veer, J. Gray, E. Petricoin, K. Conway,

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  1. 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 INVESTIGATORS

  2. CALGB INTERSPORE ACRIN NCICB Investigation of Serial studies to Predict Your Therapeutic Response with Imaging and And moLecularanalysis I SPY WITH MY LITTLE EYE . . . . . . . A BIO-MARKER BEGIN-ING WITH X . . . .

  3. Anthracycline Taxane Surgery & RT Tamif ER+ I-SPY 1 Clinical Trial Backbone Layered Imaging/Molecular Biomarker Studies Onto Standard Clinical Care Serial MRI Scans Serial Core Biopsies

  4. 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

  5. + AXILLARY NODAL BURDEN Residual Cancer Burden RCB = 1.4 x [fcell x (d1 d2)] 0.17 + [dmet x (1 - (1 -  ) LN ) / ] 0.17 PRIMARY TUMOR BURDEN PRIMARY TUMOR BURDEN Area (cm x cm) Area (cm x cm) % CANCER CELLULARITY % CANCER CELLULARITY Number of positive LNs Diameter of largest metastasis (mm) Symmans et al. J ClinOncol. 2007 Oct 1;25(28):4414-22.

  6. 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 2007

  7. I-SPY 1 Biomarker Platforms CGH 1q 20q 1p 17p 19p Tissue: Core or Surgical Protein Arrays (RPMA) p53 GeneChip Expression Arrays H&E,IHC,FISH UNC, Penn UNC, UCSF, NKI GMU UNC Serum Id1 proteins autoantibodies phospho proteins UCSF

  8. 1042 frozen cores from 201 patients • 1301 paraffin cores from 223 patients • 948 serum samples from 158 patients.

  9. Results

  10. I-SPY: Poor Prognosis Tumors 70 significant prognosis genes Mean Tumor Size= 6.0 Present as clinical mass 55% < Age 50 van´t Veer et al., Nature ,2002

  11. Relapse-free Proportion Years since surgery Relapse-free Proportion Years since surgery Relationship of pCR and RCB with Early Relapse for all I-SPY Pts pCR (n=58) No pCR (n=157) RCB 0 (n=56) RCB I (n=18) RCB II (n=86) RCB III (n=41)

  12. pCR and RCB in context of molecular features

  13. pCR: IHC vs Molecular Subtypes HR = Hormone Receptor

  14. pCR Rates: RNA Classifiers

  15. pCR Rates: DNA Classifiers

  16. pCR and RCB are VERY significant predictors of early relapse in the context of a poor prognosis profile

  17. Among Basal-like Tumors RCB I (n = 2) RCB 0 (n = 16) RCB II (n = 17) RCB III (n= 9) Log-rank P = 5.5 x 10-7

  18. Among NKI-70 High Risk RCB I (n = 10) RCB 0 (n= 35) RCB II (n = 55) RCB III (n = 22) Log-rank P = 5.9 x 10-5

  19. Among Activated-Wound Signature RCB I (n = 5) RCB 0 (n = 33) RCB II (n = 45) RCB III (n= 20) Log-rank P = 4.4 x 10-4

  20. Among p53 Mutation Profile RCB I (n= 4) RCB 0 (n= 27) RCB II (n = 24) RCB III (n = 12) Log-rank P = 4.5 x 10-7

  21. 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

  22. Integrated score is a good predictor of prognosis

  23. Integrated Score: Good Prognosis Distributed across RCB 0-III All do well REGARDLESS of RCB

  24. Integrated score poor prognosis patients associate with RCB Integrated Score, Intermediate prognosis p = 0.158 P=0.16 Integrated Score, Poor prognosis P=1.89e-07 p = 1.89e-07

  25. 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).

  26. 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)

  27. 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

  28. BACK-UP

  29. Quantitative and serial measurement of tumor response by MRI Pre Treatment Complete response Partial response Progressive disease Post Treatment

  30. Patients Accrued n=237 Patients Withdrawn n=16 Patients Available for Analysis n=221 Patients who didn’t have surgery n=6 Patients with pathology assessment after Neoadjuvant Therapy n=215 Patients without RCB n=14 Patients with pCR and RCB n=201

  31. Tissue Distribution & Analyses Schema Tumor UNC: Dressler Lab UCSF Check for Tumor Presence Initial H&E 2 Paraffin Cores 2 Frozen Cores Tumor Present Check for Tumor Presence Storage Proteomics Initial H&E Core Remainder GMU: Liotta/Petricoin Lab RNA UNC: Livasy,Dressler Lab PENN: DeMichele Lab DNA FISH IHC Gene Expression Gene Chip For P53 Her2, TopoII Amplification CGH Her2 Protein Over expression UCSF: Gray Lab UNC: Carey/ Dorsey Lab UNC: Perou Lab UCSF: HaqqLab MDACC: Pusztai/ Symmans Lab NKI: van’t Veer Lab Data uploaded in: NCI caIntegrator UCSC Cancer Genomics Browser NCI: caBIG, Madhavan UCSC: Haussler, Kent, Zhu, Wang

  32. Data Integration: NCI caINTEGRATOR

  33. Among ROR-S High Risk RCB I (n = 5) RCB 0 (n = 21) RCB II (n = 18) RCB III (n= 7) Log-rank P = 4.3 x 10-9

  34. Integrated score based prognosis classes: ER+/ER- distributions

  35. 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?

  36. Integrating Molecular Profiles Poor prognosis Intermediate prognosis Good prognosis • Based on NKI-70, ROR-S, Wound Healing Signature,, p53 mutation profile: +1 , 0, -1 based upon score; Sum the scores

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