(PQ8) Patient- and tumor-specific biomarkers and mechanisms that predict irAEs resulting from checkpoint inhibition

项目总结/摘要 在这项提案中，我们将确定临床上可翻译的预测和早期反应生物标志物，用于开发 癌症患者中免疫检查点抑制剂（ICI）治疗引起的免疫相关不良事件（irAE）。使用 我们将利用一个大型的跨机构和多学科的团队， 的研究者，以及大量（>350例患者）回顾性和前瞻性生长组织和外周血 ICI治疗患者的样本库，其中许多患者发生了重度irAE。利用这个组织库， 在我们的机构和通过合作机构预期收集的其他标本，我们将确定 在发生重度irAE的HLA匹配患者中扩增或上调的TCR和自身抗体。使用 广域网技术（全蛋白质组肽微阵列，10亿酵母pMHC展示文库，数字空间 分析），我们将鉴定ICI治疗前后外周血和组织中的致病性T和B细胞抗原。 在纵向研究中，TCR克隆性的变化、自身抗体筛查的变化和T细胞区室的CyTOF 将在发生irAE的患者和临床/HLA匹配的对照中进行。将结果与 治疗结果（临床反应和器官特异性irAE），我们将测试这些生物标志物是否可以 在ICI治疗开始前检测到。可翻译的自身抗体生物标志物将通过一种新的床旁检测方法进行验证 用于临床应用的定制阵列技术。最后，我们将在匹配的肿瘤和irAE位点中分析TCR库。 标本使用T细胞的单细胞RNA测序，再加上抗原鉴定通过一个高度新颖的~1 10亿酵母pMHC展示文库方法来鉴定irAE背后的致病机制。 利用这些数据，我们将在本提案中解决三个具体目标：1）我们将前瞻性地描述治疗中的 irAE的细胞介导机制; 2）我们将确定irAE相关的自身抗体或TCR是否可以 我们将在用ICI治疗之前鉴定抗原靶点;以及3）我们将鉴定致病性TCR的抗原靶点，并对其进行分析。 在肿瘤和患病组织中的表达。 由于ICIs的巨大成功，这些治疗将用于越来越多的患者，并转移到 早期的治疗方法因此，存在irAE风险的患者数量将继续增加;该提案将解决 如何识别和管理面临ICI严重不良后遗症风险的患者的需求日益未得到满足， 确定irAE致病机制的新发现。

PROJECT SUMMARY/ABSTRACT 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.