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

项目概要/摘要 免疫检查点抑制剂治疗显著增加了转移性乳腺癌患者的生存率。 黑色素瘤、肺癌、头颈癌、膀胱癌、肾细胞癌等。但 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 具有显著的副作用，包括免疫相关不良事件（irAE）。体细胞突变负荷， 新抗原负荷和一些特定的体细胞突变可以帮助预测对治疗的反应;然而， 目前可用的预测器仅具有适度的预测响应的能力，并且没有好的预测器 irAE。因此，新的生物标志物可能有助于预测irAE和了解其病因。我们 假设irAE是遗传易感个体自身免疫的表现， 自身免疫性疾病和遗传变异的基础上常见的自身免疫性疾病也将 irAE的有用预测因子。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， 对免疫治疗和irAE的潜在应答。我们将在超过3000人的队列中测试这些假设 接受程序性细胞死亡1（PD-1）抑制剂的非小细胞肺癌患者。 我们将进行人类白细胞抗原（HLA）区域的靶向测序和基因分型， 全基因组单核苷酸多态性（SNP）阵列。我们将用这些数据来检验关联性 HLA和irAE之间的关系。我们还将确定已知的SNP和HLA单倍型的组合是否 与自身免疫性疾病相关的基因可用于预测irAE。最后，我们将寻找新的SNP 与irAE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HLA序列数据和GWAS数据来搜索与 总体生存率。我们还将利用癌症基因组图谱（TCGA）项目的数据， 影响肿瘤免疫特征的变异体，已知与免疫治疗反应相关 如淋巴细胞浸润和PDL 1表达。我们将调查是否遗传变异确定 影响对免疫疗法反应。最后，我们将研究是否有共同的遗传 irAE和PD-1抑制剂有益应答的易感性。在这项工作结束时，我们将 了解患者irAE风险的遗传特征。

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.