In this proposal, we will identify clinically-translatable predictive and early-response biomarkers for the development of immune-related adverse events (irAEs) caused by immune checkpoint inhibitor (ICI) therapy in cancer patients. Using both focused and unbiased screening approaches, we will leverage a large inter-institutional and multi-disciplinary team of investigators, as well as a large (>350 patients) retrospective and prospectively growing tissue and peripheral blood bank of specimens from ICI treated patients, many of whom developed severe irAEs. Using this tissue bank, as well as additional specimens prospectively collected at our institution and through collaborating institutions, we will identify TCRs and autoantibodies that are expanded or upregulated in HLA-matched patients experiencing severe irAEs. Using wide-net technologies (whole-proteome peptide microarray, 1 billion yeast pMHC display libraries, digital spatial profiling), we will identify pathogenic T and B cell antigens in peripheral blood and tissue before and after ICI therapy. In longitudinal studies, changes in TCR clonality, changes in autoantibody screening, and CyTOF for T cell compartments will be performed in patients experiencing irAE and in clinically/HLA-matched controls. Findings will be compared to treatment outcomes (clinical response and organ-specific irAEs) and we will test whether these biomarkers can be detected prior to ICI therapy initiation. Translatable autoantibody biomarkers will be validated with a novel point-of-care custom array technology for clinical utility. Finally we will profile the TCR repertoire in matched tumor and site-of-irAE specimens using single-cell RNA sequencing of T cells, coupled with antigen identification through a highly novel ~1 billion yeast pMHC display library approach to identify the pathogenic mechanism behind irAEs. Using these data, we will address three specific aims in this proposal: 1) we will prospectively characterize on-treatment cell-mediated mechanisms of irAEs; 2) we will determine whether irAE-associated autoantibodies or TCRs can be identified prior to treatment with ICIs; and 3) we will identify the antigen targets of pathogenic TCRs and profile their expression across tumor and diseased tissue. Due to the overwhelming success of ICIs, these treatments will be used in increasing numbers of patients and moved to earlier lines of therapy. Thus, the numbers of patients at risk for irAEs will continue to rise; this proposal will address the growing unmet need of how to identify and manage patients at risk for severe adverse sequelae from ICIs, while making new discoveries that identify the pathogenic mechanism of irAEs.
Immune checkpoint inhibitors (ICIs) have transformed cancer treatment and provide benefit in a large number of cancer patients. However, due to the mechanism of action of these agents, severe immune-related adverse events (irAEs) can occur and limit therapeutic use. This proposal seeks to identify predictive biomarkers through wide-net technologies and elucidate novel mechanisms underlying these irAEs that can be leveraged for clinical utility and appropriate risk management of cancer patients.
