PROJECT 2 SUMMARY Immune checkpoint inhibitor (ICI) adjuvant therapies—including ipilimumab (IPI; targets cytotoxic T lymphocyte- antigen 4) and nivolumab (NIVO; targets programmed death protein 1)—increase relapse-free survival (RFS) in melanoma patients. Nonetheless, 35–40% of these patients relapse within 24 months after completing ICI therapy, and no biomarkers—either alone or together—can predict RFS after ICI therapy and potentially identify novel targets for more effective adjuvant treatments. Efforts to identify biomarkers of ICI efficacy have centered mainly on the tumor microenvironment in the metastatic setting, leaving putative biomarkers of adjuvant ICI treatments largely unexplored. Because anti-tumor T-cell immunity is the primary target of ICI, the focus has been predominantly on tumor T-cell infiltration. Here we propose the novel hypothesis that underlying inherited factors that influence host immunity impact RFS after adjuvant ICI. It has been demonstrated that phenotypic variation in T-cell subsets, including CD8+ T cells, can be attributed to germline genetic variation. In a recent study, we showed that this inherited component maps to the non-coding regulatory genome, impacting transcriptional regulation of T-cell differentiation and function. Based on these data, we hypothesize that germline genetic variation in the T-cell-specific non-coding regulatory genome (regulome) controls circulating CD4+ and CD8+ T cells (the primary targets of NIVO and NIVO+IPI ICI), and that this genetic variability is associated with RFS after ICI treatment. We propose to discover inherited signatures of the CD4+- and CD8+- T-cell regulome that predict ICI relapse and RFS. Using samples from 600 melanoma patients treated in an adjuvant clinical trial of NIVO compared to NIVO+IPI, we will perform whole-genome (WGS) and whole-transcriptome sequence analyses of CD4+ and CD8+ T cells from peripheral blood collected before ICI treatment to identify non-coding transcriptome signatures that predict RFS after adjuvant ICI (Aim 1). We will also comprehensively assess open chromatin states in pre-treatment CD4+ and CD8+ T cells from the same 600 patients to identify epigenetic signatures controlled by inherited genetic variation, and predict RFS after adjuvant ICI (Aim 2), and integrate these data with microbiome, immuno-phenotyping, and seromics profiles from Project 1 (Aim 3). Our preliminary data have revealed novel genomic imprints in the non-coding regulome that predict ICI response with high clinical accuracy, thus substantially supporting our hypotheses and study design. For the first time, we will elucidate the effect of inherited anti-tumor host immunity on ICI outcomes in the adjuvant setting. Besides having applicability to personalized prediction of ICI benefit, the integration of genomic information from all three aims of this project promises to reveal novel T-cell-specific transcriptional networks that potentially affect ICI resistance and ...