Large-Scale Genetic Analyses of Human Cancer

项目摘要 人类癌症是由特定基因突变的积累引起的。前一 在2000年的资助期内，我们的研究小组是第一个确定人类癌症中蛋白质编码基因序列的研究小组。 并将这种方法扩展到许多肿瘤类型。通过这项工作，我们能够识别候选基因 以前与肿瘤发生无关，定义了基本的基因组和新抗原景观 并指出了个体癌症中复杂基因改变的基础途径。 肿瘤类型最近，我们已经确定了基因组的改变是重要的敏感性， 常见的靶向治疗以及免疫治疗的耐药性。我们率先开发了 非侵入性循环肿瘤DNA方法来检测和监测肿瘤，并已表明，这些 可广泛应用于许多癌症患者。这些分析提供了新的见解 肿瘤发生的潜在机制，并描绘了临床干预的新途径。 最近癌症基因组学与新的免疫学方法的交叉很有希望， 彻底改变癌症治疗方法免疫检查点抑制剂已显示出显著的临床益处， 各种肿瘤类型，并且认为这些疗法在很大程度上通过肿瘤细胞发挥其作用。 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中获益， 初步反应后产生耐药性。我们的初步数据表明，免疫治疗的临床结果 检查点阻断可由癌症中不断演变的基因组和新抗原格局决定， T细胞受体库的动力学可能是治疗结果的有用量度。目的 这种竞争性更新应用的目的是扩大我们的大规模测序工作， 了解不断演变的基因组和免疫景观如何调节对免疫系统的反应和抵抗力， 免疫检查点阻断。首先，我们提出了肿瘤的全基因组分析，以检查癌症基因组 在这些疗法的选择性压力下发生变化。我们将开发和利用计算 预测突变相关的新抗原并通过新的方法在功能上验证它们的方法 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， 循环肿瘤DNA和T细胞受体库，以动态测量对 免疫检查点阻断。从本申请中描述的研究中获得的知识将有助于 扩大我们对免疫疗法的反应和抵抗的潜在机制的理解。 我们设想，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和用于开发新的治疗方法 战略布局

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.