Biomarkers for Predicting Immunotherapy Response in Breast Cancer

Abstract

Recent clinical studies have demonstrated that combining neoadjuvant chemotherapy with immune checkpoint inhibitors can improve the response rate in early-stage breast cancer patients. Despite these advances, most patients do not respond to immunotherapy, highlighting the need for better biomarkers to optimize treatment benefit. This thesis aims to identify peripheral blood and tumor biomarkers that predict breast cancer immunotherapy outcomes. Using patient derived biopsy, we measured the expression of antigen presentation protein MHC-I on tumor cells and identified a positive correlation between MHC-I expression and immunotherapy response. We also observed significant MHC-I expressional heterogeneity across races and breast cancer subtypes. In addition, systemic immunity also significantly affects immunotherapy response, making peripheral immune biomarkers potential candidates for immunotherapy prediction. Using >500 peripheral blood RNA sequenced transcriptomes collected longitudinally from over 150 patients in the control and pembrolizumab arms of the ISPY-2 trial, we demonstrated the interconnected nature of systemic and tumoral immune response, and showed that the dynamics of immune gene expression patterns derived from peripheral blood as baseline and on-therapy can predict clinical outcomes. These findings highlight the potential of integrating peripheral and tumoral biomarkers to guide immunotherapy decisions, advancing the field of precision oncology.