Large-Scale Genetic Analyses of Human Cancer

项目总结 人类癌症是由特定基因的突变积累引起的。在上一次 在资助期间，我们小组第一个确定了人类癌症的蛋白质编码基因序列 并将这种方法扩展到许多肿瘤类型。通过这项工作，我们能够确定候选基因 定义了基本的基因组和新的抗原图景 ，并指出了个体复杂的基因改变背后的途径 肿瘤类型。最近，我们已经确定了在敏感性和易感性中重要的基因组改变 对常见靶向治疗和免疫治疗的抵抗力。我们率先开发了 检测和监测肿瘤的非侵入性循环肿瘤DNA方法，并已表明这些方法 可能广泛适用于许多癌症患者。这些分析为我们提供了对 肿瘤发生的潜在机制，并为临床干预勾勒出新的途径。 癌症基因组学与新的免疫学方法最近的交集有望 彻底改变癌症治疗方法。免疫检查点抑制剂在以下方面显示出显著的临床益处 各种各样的肿瘤类型，人们认为这些疗法在很大程度上是通过 对癌细胞基因组中编码的突变相关新抗原的免疫识别。 不幸的是，尽管最初取得了成功，但很大一部分患者并没有从这些治疗或 在最初的反应后产生抵抗力。我们的初步数据表明，免疫的临床结果 检查点阻断可能由癌症和癌症中不断演变的基因组和新抗原图景决定 T细胞受体谱系的动态变化可能是衡量治疗结果的有用指标。目的 这项竞争性续订申请的目的是将我们的大规模测序工作扩展到专注于 了解进化中的基因组和免疫环境如何调节对 免疫检查站封锁。首先，我们建议对肿瘤进行全基因组分析以检查癌症基因组。 在这些疗法的选择压力下的变化。我们将开发和利用计算 预测突变相关新抗原并通过新的方法进行功能验证的方法 患者特异性T细胞培养的方法。最后，我们将开发非侵入性方法，包括 循环肿瘤DNA和T细胞受体谱系动态测量对 免疫检查站封锁。从本申请表中描述的研究中获得的知识将有所帮助 以扩大我们对免疫治疗反应和抵抗的潜在机制的理解。 我们预计，这些分析将迅速转化为临床环境，提供新的方法 用于预测患者对当前免疫靶向治疗的反应并开发新的治疗方法 战略。

PROJECT SUMMARY Human cancers are caused by the accumulation of mutations in specific genes. During the previous funding periods, our group was the first to determine the sequence of protein coding genes in human cancer and extended this approach to many tumor types. Through this work, we were able to identify candidate genes which had not been previously linked to tumorigenesis, define the basic genomic and neoantigen landscape of common human cancers, and point to pathways that underlie the complex genetic alterations in individual tumor types. More recently, we have identified genomic alterations that are important in the sensitivity and resistance of common targeted therapies as well as immunotherapy. We have pioneered the development of non-invasive circulating tumor DNA approaches to detect and monitor tumors, and have shown that these may be broadly applicable to many cancer patients. These analyses provided new insights into the mechanisms underlying tumorigenesis and have delineated novel avenues for clinical intervention. The recent intersection of cancer genomics with novel immunologic approaches is promising to revolutionize cancer therapeutics. Immune checkpoint inhibitors have demonstrated notable clinical benefit in a variety of tumor types and it is thought that these therapies exert their effects in large part through the immune recognition of mutation associated neoantigens encoded in the genomes of cancer cells. Unfortunately, despite initial successes, a large fraction of patients do not benefit from these treatments or develop resistance after an initial response. Our preliminary data suggest that clinical outcome to immune checkpoint blockade may be determined by the evolving genomic and neoantigen landscape in cancer and that dynamics of the T cell receptor repertoire may be a useful measure of therapeutic outcome. The purpose of this competitive renewal application is to extend our large-scale sequencing efforts to focus on understanding how the evolving genomic and immune landscapes regulate response and resistance to immune checkpoint blockade. First, we propose genome-wide analyses of tumors to examine cancer genome changes under the selective pressure of these therapies. We will develop and utilize computational approaches to predict mutation-associated neoantigens and functionally validate these through novel approaches in patient-specific T cell cultures. Finally, we will develop non-invasive approaches involving circulating tumor DNA and the T cell receptor repertoire to dynamically measure response and resistance to immune checkpoint blockade. The knowledge gained from the studies described in this application will help to broaden our understanding of the underlying mechanisms of response and resistance to immunotherapy. We envision that these analyses will be rapidly translated into the clinical setting, providing new approaches for predicting patient response to current immune-targeted therapies and for development of new treatment strategies.