Single Cell Genome-Wide Myeloid Response Profiling in Immunotherapy

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Project summary Tumor microenvironments are home to diverse immune cell types but current immunotherapeutic approaches are focused largely on activating cytolytic T cells. The potential of other, myeloid lineage cells in fighting cancer are hitherto much less explored. For example, we have a limited understanding of the complexity of myeloid cell subtypes, we cannot fully discriminate between tumor-promoting and tumor-suppressing cells, and we lack information about defined myeloid cell-associated molecular pathways that could be harnessed for therapy. Here, we will use cutting-edge, unbiased single cell profiling to reveal unappreciated immunoregulatory myeloid cell types, alongside in vitro and in vivo perturbations, to reveal unappreciated tumor-infiltrating myeloid (TIM) cell populations and define their functional role in lung cancer. To this end, we will first determine human TIM states, their correlation with clinical parameters, and whether these states are conserved between human and mouse lung adenocarcinoma. We will specifically test the hypotheses that i) yet-unappreciated myeloid cell states in tumors and peripheral blood of human patients correlate with patient survival (and possibly other clinical parameters), and ii) genetically engineered mouse tumor models of lung adenocarcinoma host conserved human TIM states and justify further animal studies of the function of these states. Second, we will focus on so-called GN2 and GN3 neutrophil subsets, considering our initial data showing their existence in both human and mouse lung tumors and their relevance to cancer progression (Science, 2017 in Press and our unpublished data included in this application) and that neutrophils are emerging as strong predictors of survival for diverse solid tumors and most notably lung cancer. We will specifically test the hypotheses that i) GN2 and GN3 neutrophils have distinct tumor-promoting functions, and ii) these subsets use specific molecular signaling pathways to foster lung cancer progression. To achieve our goals, we will combine efforts of two labs with complementary expertise: tumor immunobiology and myeloid cells (Pittet), and single cell RNA sequencing (scRNA-Seq) and theory/bioinformatics (Klein). We have further teamed up with clinicians to obtain both blood samples and fresh tumor biopsies from lung cancer patients (our preliminary data are also included in this application). Overall, the approaches and resources developed here could have major implications for developing new and more efficient immunotherapies. Also, by targeting the immune system beyond T cells, we will exploit the diversity of non-redundant immune components as a way to overcome limitations of current treatment options.