Abstract No. 
PD9-04
2020 San Antonio Breast Cancer Symposium
Dec 8-11
2020

Identification of biomarkers associated with therapeutic resistance: quantitative protein/phosphoprotein analysis of ~750 patients across 8 arms of the neoadjuvant I-SPY 2 TRIAL for high-risk early stage breast cancer

Wulfkuhle J, Wolf D, Yau C, Brown-Swigart L, Gallagher RI, Hirst G, Sit L, Asare S, I-SPY 2 TRIAL Investigators, Hylton N, DeMichele A, Yee D, Chien J, Rugo H, Park J, Albain K, Nanda R, Tripathy D, Schwab R, Berry D, Esserman L, van t' Veer L, Petricoin, III E.

Background: The goal of I-SPY 2 is to rapidly test novel therapies in addition to standard of care in high-risk breast cancer patients. It has resulted in increasing response rates, where pCR rates in TNBC and HR-HER2+ subsets have reached ~60% and ~75%, respectively. Yet, there remains a sizeable subset of non-responders, especially among HR+ patients. Identification of ‘universal’ resistance mechanisms may guide rational selection of agents   to improve these patient's outcomes. Thus, we analyzed reverse phase protein array (RPPA) based quantitative protein/phosphoprotein data across arms to assess whether there are common mechanisms rendering these cancers resistant to all agent classes tested to date.

Methods: 736 patients (260 HR+HER2-, 252 TN, 142 HR+HER2-, and 82 HR-HER2+; over 8 arms: 194 Ctr, 105 neratinib (N), 63 veliparib/carboplatin (VC), 128 AMG386 (anti-ANG1/2), 87 MK2206 (anti-AKT), 43 TH/pertuzumab (P), 49 TDM1/P, and 67 pembrolizumab (Pembro)) with pCR and RPPA data at the pre-treatment time point were considered for this analysis. 141 RPPA endpoints representing key cancer pathways     were assessed for association with pCR using logistic regression modeling, with HR, HER2 and treatment arm as covariates (likelihood ratio test; p<0.05). Analysis was also performed in HR/HER2 subsets and within treatment arms. Markers were analyzed individually; multiple comparison correction (Benjamini-Hochberg) was applied to p-values. Our analysis is exploratory, and does not adjust for other biomarkers outside this study.

Results: Prior to FDR correction, high levels of Cyclin D1, a cell cycle protein implicated in estrogen-mediated DNA damage repair, associate with non-pCR in the population as a whole and within all subtypes except for the HR-HER2+ subset; an association that retains significance after FDR correction overall as well as in HER2- and HR+HER2- subsets. Within individual arms, high Cyclin D1 predicted non-response in VC, control, and AMG386; and trends toward association in Pembro and N. In addition, high quantitative ER and phospho-androgen receptor (pAR; S650) associate with non-pCR in the population as a whole and in the HR+HER2- subset. For both ER and pAR the strongest association with non-pCR was in the Pembro arm. Candidates for universal sensitivity signals include immune proteins JAK-STAT (pSTAT5 (Y694) and pSTAT1 (Y701)) overall; and pERBB2/pEGFR for HER2+ patients.

Conclusions: High levels of Cyclin D1, but not other cell cycle proteins, predict non-response to chemo-/targeted-therapy across arms and subtypes, suggesting that agents specifically targeting Cyclin D1 may increase chemo-sensitivity. ER/phospho-AR as global resistance signals suggest inclusion of anti-AR agents in combination therapy, and the need for new endocrine-based approaches.

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