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

(PQ8) 患者和肿瘤特异性生物标志物和预测检查点抑制引起的 irAE 的机制

基本信息

批准号：
10133451
负责人：
Justin M Balko
金额：
$ 51.74万
依托单位：
VANDERBILT UNIVERSITY MEDICAL CENTER
依托单位国家：
美国
项目类别：
财政年份：
2019
资助国家：
美国
起止时间：
2019-04-01 至 2024-03-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10133451
关键词：
Address Adverse reactions Affect Antigen Targeting Antigens Autoantibodies Autoantigens Autoimmune Diseases Autoimmunity Autopsy B-Lymphocytes Biological Markers Biological Specimen Banks Biopsy CTLA4 gene Cancer Patient Cell Compartmentation Cells Clinical Clonal Expansion Clone Cells Colitis Coupled Custom Data Development Disease Encephalitis Etiology Frequencies Genetic Immune checkpoint inhibitor Immunotherapy Incidence Institution Libraries Longitudinal Studies Lymphocyte Malignant Neoplasms Mediating Metastatic Melanoma Methods Muscle Myocarditis Myocardium Myositis Nature Nivolumab Normal tissue morphology Organ Outcome PD-1/PD-L1 Pathogenicity Pathology Patients Peptide/MHC Complex Peptides Peripheral Prospective Studies Proteome RNA Refractory Reporting Research Personnel Risk Risk Factors Risk Management Role Sampling Self Tolerance Site Skeletal Muscle Neoplasm Specimen T cell clonality T cell receptor repertoire sequencing T-Cell Activation T-Cell Receptor T-Lymphocyte T-Lymphocyte Epitopes T-cell receptor repertoire Technology Testing Therapeutic Uses Time Tissue Banks Tissues Transcript Translating Treatment outcome Tumor Markers Tumor Tissue Validation Yeasts anti-tumor immune response autoimmune toxicity autoreactivity biomarker development cancer therapy case control checkpoint inhibition checkpoint therapy clinical biomarkers clinically translatable digital exhaustion experience immune checkpoint blockade immune-related adverse events insight inter-institutional ipilimumab multidisciplinary novel novel therapeutics peripheral blood point of care predictive marker prevent prospective protein aminoacid sequence reconstitution repository response response biomarker screening sensor single-cell RNA sequencing success transcriptome transcriptomics tumor

项目摘要

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.

项目总结/文摘