Breast cancer molecular profiles and tumor response of neoadjuvant doxorubicin and paclitaxel: The I-SPY TRIAL (CALGB 150007/150012, ACRIN 6657)

Abstract

LBA515 Background: I-SPY is a multi-center trial designed to identify predictive markers of pathological complete response (pCR) and survival of women with locally advanced breast cancers (3cm or greater). Women received neoadjuvant doxorubicin and cyclophosphamide then paclitaxel. Methods: 237 women enrolled, 216 completed serial imaging and core biopsies. Pre-treatment assays include: Agilent expression arrays, MIP aCGH, p53 gene chip and sequencing, IHC and reverse phase protein arrays (RPMA). Response to therapy was measured by serial MRI, pCR and residual cancer burden (RCB). Associations among molecular markers, pCR, RCB and survival were evaluated using chi-square test, Kaplan-Meier curves and log-rank test. Results: Median tumor size was 6cm, % pCR and RCB 0/1 was 27% and 36% for the entire study; % pCR rate for the 144 Agilent arrays was 25%. Distribution, rates of pCR and RCB 0/1 are shown in the Table for molecular and IHC markers. DFS and OS will be presented. Several molecular subtypes, including NKI 70 gene low, luminal A, 21 gene set low and IHC HR+, define 15–28% of patients with 3–10% pCR, yet excellent early survival. Wound healing, most discriminatory for prognosis, is not predictive of chemotherapy response. By RPMA, patients with pCR had increased phosphorylation of 4EBP1, eNOS, cAbl, STAT5, EGFR, AKT (p<0.05). In ER+ patients with poor MR response, pIRS, pIGFR, p706S were activated (p<0.05). RCB is a more refined way to measure pCR and was more predictive of DFS and OS (p=0.01) than pCR alone with a mean follow up of 3.9 years. MR volume is highly predictive of pCR and RCB. For specific subtypes, e.g. basal, RCB is predictive of DFS (p<0.00001). Conclusions: LABC have aggressive biology. Response to therapy and outcome can be predicted by many biomarkers. The I-SPY data set provides a platform to compare, contrast and combine marker signatures to tailor therapy and demonstrates the power of the neoadjuvant setting. Support: ACRIN U01 CA079778; CALGB CA31964, CA33601; NCI SPORE CA58207. Profile rates of pCR and RCB Distribution pCR RCB 0,1 pCR p-value RCB p-value Intrinsic Subtypes Luminal A 28% −5% −14% <0.001 <0.001 n=144 LuminalB 21% 13% −21% . . Basal 31% 34% −40% . . Her 2 15% 55% −73% . . Normal −4% 50% −67% . . NKI 70 gene Good 15% 10% −17% 0.16 0.07 n=144 Poor 85% 27% −39% . . IHC HR+ Her2− 29% 10% −21% Effect HR 0.0002 n=189 HR+ Her2+ 20% 28% −48% Effect Her2 0.009 HR− Her2− 34% 36% −41% HR− Her2− 17% 48% −79% MIP No Amplification 17q 86% 17% . n=127 Amplification 17q 14% 61% <0.0001 p53 Mutation Any Mutation 43% 38% −43% . n=181 MissenseZn-binding 39% 75% 100% 0.02 Null 27% 57% −53% 0.0003 ROR-S Low 22% −6% −21% 0.001 0.005 n=144 Medium 38% 17% −27% . . High 40% 43% −52% . . Wound Healing Quiescent 49% 19% −34% 0.12 0.72 n=144 Activated 51% 31% −38% . . 21 gene set Low 22% −3% −12% <0.001 0.002 n=144 Intermediate 10% −0% −20% . . High 68% 36% −46% . . Author Disclosure Employment or Leadership Consultant or Advisory Role Stock Ownership Honoraria Research Funding Expert Testimony Other Remuneration Agendia Agendia