Admin Core

ABSTRACT: Immunotherapy has led to remarkable improvements in patient survival for many tumor types. In particular, immune checkpoint inhibitors have shown efficacy in many cancer types. These drugs act by turning off pathways that inactivate T-cells and allow patients’ adaptive immune response to attack tumors,. However, very little is known about how immunotherapy affects different racial and ethnic populations. Breast cancer is a disease with substantial disparities in outcomes. Black women have particularly high risk of mortality from breast cancer and also have higher risk of “triple negative” (estrogen receptor, progesterone receptor and Her2 negative) breast cancer (TNBC) which is more responsive to immunotherapy. The tumor immune microenvironment is a strong prognostic factor among women with breast cancer and a strong predictor of benefit from immunotherapy. In preliminary data, we have found that breast tumors from women of African ancestry have higher rates of lymphocytic infiltration which is generally associated with better response to immunotherapy. However, there is no clear data on how well Black women, Hispanic/Latina or Asian women do on checkpoint inhibitors. In this application, we will focus on breast cancer disparities and immuno-oncology in the Research Project. First, we will population based (cancer registry) data to determine how frequently women of different racial, ethnic and ancestry groups with TNBC are treated with immunotherapy. We will also leverage an existing trial of locally advanced breast cancer, ISPY2, which includes an immune checkpoint inhibitor. The trial will allow us to examine genetic ancestry in addition to race and ethnicity. Second, we will examine the tumor immune microenvironment among women with breast cancer in relation to genetic ancestry and in relation to genetic variants that we have identified as associated with the tumor immune microenvironment. We will perform deep characterization using single nuclear RNA-sequencing of a subset of the trial women, comparing responders to non-responders selected by stratification on race and ethnicity. We will integrate all of these data and leverage the organizational structure of the accompanying Administrative Core to interpret these data within the context of what is already known about cancer immunology, immunotherapy and health disparities. We will build on these results and other projects and datasets to plan larger projects to address more ambitious questions of how different populations respond to immunotherapy, how their rates of adverse events compare.