(8) Genetics of Immune Related Adverse Events and Response to Immunotherapy

(8) 免疫相关不良事件的遗传学和免疫治疗的反应

• 批准号: 10655507
• 负责人: Elad Ziv
• 金额: $ 30.99万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-07-01 至 2024-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10655507
• 关键词: Adverse event; Affect; Antibodies; Apoptosis; Autoimmune; Autoimmune Diseases; Autoimmunity; Biological; CTLA4 gene; California; Cancer Patient; Data; Data Set; Disseminated Malignant Neoplasm; Etiology; Foundations; Gene Expression Profile; Genetic; Genetic Predisposition to Disease; Genotype; Germ-Line Mutation; HLA Antigens; Haplotypes; Head and Neck Cancer; Histologic; Hypothyroidism; Immune; Immune checkpoint inhibitor; Immune response; Immune system; Immunotherapy; Individual; Inflammatory Bowel Diseases; Inherited; Link; Lymphocytic Infiltrate; Malignant neoplasm of lung; Malignant neoplasm of urinary bladder; Memorial Sloan-Kettering Cancer Center; Metastatic Melanoma; Molecular; Neck Cancer; Non-Small-Cell Lung Carcinoma; Patient risk; Patients; Pharmaceutical Preparations; Prediction of Response to Therapy; Predisposition; Renal Cell Carcinoma; SNP array; Sampling; San Francisco; Single Nucleotide Polymorphism; Somatic Mutation; Testing; The Cancer Genome Atlas; Thyroid Gland; Tissues; Universities; Variant; Work; bak protein; checkpoint inhibition; cohort; disorder risk; gastrointestinal; genetic variant; genome wide association study; genome-wide; genomic locus; immune-related adverse events; improved; inhibitor; neoantigens; novel; novel marker; novel strategies; patient subsets; polygenic risk score; predicting response; programmed cell death ligand 1; programmed cell death protein 1; response; side effect; targeted sequencing; treatment response; tumor

PROJECT SUMMARY/ ABSTRACT Therapy with immune checkpoint inhibitors has substantially increased survival of patients with metastatic melanoma, lung cancer, head and neck cancer, bladder cancer, renal cell carcinoma and others. However, a majority of patients have very limited or no response to these drugs. In addition, a large fraction of patients have significant side effects including immune related adverse events (irAEs). Somatic mutation load, neoantigen burden, and some particular somatic mutations can help predict response to therapy; however, currently available predictors have only modest power to predict response and there are no good predictors of irAEs. Thus, novel biomarkers may be helpful in predicting irAEs and understanding their etiology. We hypothesize that irAEs are manifestations of autoimmunity in individuals who are genetically susceptible to autoimmune disorders and that the genetic variants underlying common autoimmune disorders will also be useful predictors for irAEs. Separately, we and others have demonstrated that autoimmunity may be associated with response to immunotherapies. Thus, we hypothesize that there will be shared genetic factors underlying response to immunotherapy and irAEs. We will test these hypotheses in a cohort of over 3000 patients with non-small lung cancer receiving programmed cell death 1 (PD-1) inhibitors. We will perform both targeted sequencing of the human leukocyte antigen (HLA) region and genotyping with a genome wide single nucleotide polymorphism (SNP) array. We will use these data to test the association between HLA and irAEs. We will also determine whether combinations of SNPs and HLA haplotypes known to be associated with autoimmune diseases can be used to predict irAEs. Finally, we will search for novel SNPs associated with irAEs. We will also investigate whether genetic factors that may affect survival of patients on immunotherapy. We will use the HLA sequence data and GWAS data to search for variants associated with overall survival. We will also leverage data from The Cancer Genome Atlas (TCGA) Project to identify genetic variants that affect immune signatures in the tumor known to be associated with response to immunotherapies such as lymphocyte infiltration and PDL1 expression. We will investigate whether the genetic variants identified in TCGA affect response to immunotherapies. Finally, we will investigate whether there is shared genetic predisposition to irAEs and to beneficial response from PD-1 inhibitors. At the conclusion of this work, we will develop an understanding of the genetic profile that underlies patients' risk of irAEs.

项目摘要/摘要 免疫检查点抑制剂治疗显著提高了转移性癌症患者的存活率 黑色素瘤、肺癌、头颈癌、膀胱癌、肾癌等。然而，a 大多数患者对这些药物的反应非常有限或没有反应。此外，很大一部分患者 有显著的副作用，包括免疫相关不良事件(IrAEs)。体细胞突变负荷， 新的抗原负荷和一些特殊的体细胞突变可以帮助预测治疗的反应；然而， 目前可用的预测因子只有适度的能力来预测反应，而且没有好的预测因子 这就是我们的工作。因此，新的生物标志物可能有助于预测irAEs并了解其病因。我们 假设irAEs是遗传易感人群自身免疫的表现 自身免疫性疾病和常见自身免疫性疾病的遗传变异也将是 对irAEs有用的预测指标。另外，我们和其他人已经证明，自身免疫可能是 与免疫疗法的反应有关。因此，我们假设将会有共同的遗传因素 对免疫治疗和irAEs的潜在反应。我们将在3000多人的队列中检验这些假设 接受程序性细胞死亡1(PD-1)抑制剂治疗的非小细胞肺癌患者。 我们将进行人类白细胞抗原(HL A)区域的定向测序和基因分型 全基因组单核苷酸多态(SNP)阵列。我们将使用这些数据来测试两者之间的关联 在人类白细胞抗原和免疫球蛋白Es之间。我们还将确定SNPs和人类白细胞抗原单倍型的组合是否已知 与自身免疫性疾病相关，可用于预测irAEs。最后，我们将寻找新的SNPs 与irAEs相关。我们还将调查可能影响患者生存的遗传因素 免疫疗法。我们将使用人类白细胞抗原序列数据和GWAS数据来搜索与 总体存活率。我们还将利用癌症基因组图谱项目(TCGA)的数据来识别基因 已知与免疫治疗反应相关的影响肿瘤免疫信号的变异 如淋巴细胞浸润、PDL1表达等。我们将调查是否发现了基因变异 TCGA会影响免疫疗法的反应。最后，我们将调查是否有共同的基因 对irAEs的易感性和PD-1抑制剂的有益反应。在这项工作结束时，我们将 了解导致患者发生irAEs风险的基因特征。