USING DEEP MUTATIONAL SCANNING TO CHARACTERIZE TUMOR-IMMUNE INTERACTIONS - Triple negative breast cancer (TNBC) is the most aggressive subtype of breast cancer, and there are few available treatment options for patients with this disease. Recently, immunotherapy has shown promise in a subset of TNBC patients. However, identifying which patients will benefit from immunotherapy is currently extremely challenging. In order to understand why certain patients respond to immunotherapy and others do not, we need to develop a better understanding of the tumor microenvironment (TME). The TME is made up of cancer cells, as well as the immune and stromal cells which surround them. Previous work has demonstrated that changes in the relative abundance of certain cell types in the TME can predict whether patients will respond to treatment. However, we have lacked the tools to develop a comprehensive understanding of the patterns of interaction between the different cells in the TME. For the F99 phase of this proposal, I will combine multiplexed imaging with exome sequencing to comprehensively profile the TME in TNBC patients. I will analyze 100 TNBC patient samples from a clinical trial testing the anti-PD-1 immunotherapy. I will first link genetic alterations to changes in the localization of cells in the TME, to increase our understanding of the relationship between cancer genetics and host cell infiltration. I will then use these relationships to generate biomarkers of response to immunotherapy. For the K00 phase of this proposal, I will develop an organoid model of the TNBC TME. Using this organoid model, I will determine how the absence of myeloid cells alters the phenotype of the organoid. I will then use single-cell sequencing to identify the transcriptional changes that myeloid cells undergo following treatment with anti-PD-1. This fellowship will provide me with the necessary training in both computational analysis and experimental methods to lead my own group studying the interaction between the immune system and cancer.
