Improving Breast Cancer Outcomes by Understanding How Immune Age Impacts Tumor Evolution and Response to Therapy


Sandra McAllister, PhD, Brigham & Women’s Hospital; Kornelia Polyak, MD, PhD; Rachel Freedman, MD, Dana-Farber Cancer Institute

Sandra McAllister, PhD

Kornelia Polyak, MD, PhD

Rachel Freedman, MD

Breast cancer risk rises with age, with older patients experiencing worse outcomes once diagnosed. However, the underlying reasons for this age-related discrepancy remain incompletely understood. This research team proposes that the aging tissue environment, characterized by escalating immune dysfunction, might establish a more conducive milieu for tumorigenesis. The project aims to delve into the impact of aging on breast cancer initiation and progression, specifically focusing on the normal cell-of-origin of mammary tumors and immune evasion mechanisms. Utilizing a lineage tracing system and single-cell profiling, the team will meticulously monitor mammary tumor evolution in rats across different age groups. Age-related distinctions in luminal progenitors, immune cell composition, and TCR clonotype diversity in breast cancer will be thoroughly compared. The insights gained from the rat model will be corroborated using human breast tumor samples from diverse age brackets, involving extensive analyses of gene expression patterns and biomarker discovery.

Additionally, the team aims to ascertain the influence of immune age on therapy response. Understanding age-related variations in treatment response will involve characterizing breast cancer clones in young and aged mice, coupled with assessing clonal dynamics in response to therapy. Subsequent isolation and in-depth analysis of subclones, with a focus on epithelial progenitor properties and cancer stem cell phenotypes, will be instrumental in identifying tumor-intrinsic factors and immune drivers. The ultimate objective is to pinpoint specific targets among these factors that could enhance immunotherapy responses, particularly in aged individuals. The acquired insights are anticipated to contribute to the development of age-stratified therapeutic strategies and clinical assays, offering a more nuanced understanding of breast cancer risk and treatment response prediction.