Abstract No. 
2018 San Antonio Breast Cancer Symposium
December 4-8

Expression-based immune signatures as predictors of neoadjuvant targeted-/chemo-therapy response: Experience from the I-SPY 2 TRIAL of ~1000 patients across 10 therapies

Yau C, Wolf D, Campbell M, Savas P, Lin S, Brown-Swigart L, Hirst G, Asare S, Zhu Z, I-SPY 2 TRIAL Consortium, Loi S, DeMichele A, Yee D, Berry D, Esserman L, van 't Veer L

Background:  Thereis ample evidence supporting expression-based immune signatures as predictorsof response to neoadjuvant targeted and/or chemotherapy in primary breastcancer.  However, further studies areneeded to disentangle the unique and overlapping genes comprising thesesignatures; and to implicate the contribution of different immune cell types intreatment and receptor subtype specific contexts.  The I-SPY 2 TRIAL is a standing neoadjuvantplatform trial which evaluates experimental agents/combinations when added tostandard chemotherapy.  In this study, wecompared T/B cell-related signatures at 3 different levels of resolution aspredictors of response in the I-SPY 2 TRIAL: (1) a T/B-cell co-expressionmodule, correlated with general lymphocytic infiltrate, (2) a T cell and a Bcell specific signature, and (3) 9 T cell subpopulation-specific signaturesgenerated from single cell sequencing of tumor associated CD8+ or CD4+lymphocytes.

Methods: Expression data from 989 I-SPY 2 patientsrandomized to one of 9 possible experimental arms or the standard chemotherapycontrol (veliparib/carboplatin (VC):72, neratinib (N):115, MK2206:94,AMG386:134, T-DM1/Pertuzumab (P) :52, THP:44, ganitumab:106, ganetespib:93,pembrolizumab (Pembro):69, control: 210) were available for analysis.  Pre-treatment biopsies were assayed usingAgilent gene expression arrays. All I-SPY 2 biomarker analyses follow apre-specified analysis plan. We used logistic modeling to assess each signatureas a predictor of pCR within each arm (likelihood ratio test p<0.05).  This analysis is also performed adjusting forHR/HER2 status, and within receptor subsets. Our sample size for each arm is small; and our statistics are descriptiverather than inferential.  Our analysis isexploratory and does not adjust for multiplicitiesof other biomarkers outside this study.

Results:  Inthe population as a whole, immune signatures predict response across multipleclasses of agents (8/10 arms), including the checkpoint inhibitor Pembro. However,the cell-type and subpopulation-specific signatures most predictive of responsevary by subtype and agent.  For instance,the T/B-cell co-expression module associates with response to Pembro andAMG-386 in both HR-HER2- and HR+ERHHER2-subtypes.  However, in the HR-HER2-subtype, the T-cell and CD8-TRM signatures are most predictive; whereas in theHR+HER2- subtype, it is the B-cell, CD8-TRM and CD4-RGCC signatures that are moststrongly associated with response. In the HER2+ subtype, the T/B-cell module andB-cell signature is associated with response to N and MK2206. Interestingly,the CD8-TEM and multiple CD4 population-specific signatures, rather thanCD8-TRM, also associates with response to MK2206 arm in this subtype.  

Conclusion: Our exploratory study suggests that immune signatures are associatedwith response to multiple I-SPY 2 experimental agents and implicates differentimmune cell types as response-predictive within breast cancer subtypes.  Single cell sequencing derived populationspecific signatures may help further de-convolute how different immune celltypes contribute to therapy responsiveness.

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