Integrated Discovery Pipeline for Tumor Neoantigens

项目摘要 癌症免疫疗法现在被确立为主要的治疗方式。重大进展 检查点抑制剂单克隆抗体在转移性黑色素瘤中显示出持久的肿瘤消退， 肺癌和其他恶性肿瘤。一个明显的局限性是缺乏有效的肿瘤抗原， 这阻碍了临床研究者寻求开发新的癌症免疫疗法。肿瘤 编码的非同义突变可提供潜在靶抗原的新来源。T细胞识别 肿瘤错义突变作为氨基酸取代的肽，在主要 癌细胞表面的组织相容性分子，从而暗示错义突变是癌细胞的来源。 患者特异性新抗原。我们最近描述了第一次在人体研究中使用下一代 测序技术来鉴定和验证肿瘤错义突变作为新抗原。我们的研究 表明疫苗接种增加了新抗原特异性T细胞的广度和多样性，导致免疫应答。 独特区分突变抗原与野生型肽的效应CD 8 + T细胞的广泛库 确保肿瘤特异性。该提案旨在通过以下方式找到解决肿瘤抗原稀缺的独特解决方案： 开发整合基因组学和蛋白质组学技术的新抗原发现管道。在这 一个独特的学术-工业合作伙伴关系，由一个成熟的专家团队组成，在癌症领域 基因组学、癌症蛋白质组学、人类免疫学和临床肿瘤学，旨在解决具有挑战性的问题 肿瘤新抗原的发现长期目标是开发一个强大的管道， 技术与机器学习算法相结合，为临床研究提供肿瘤新抗原。 本提案的目标将在以下具体目标的实验中得到解决：1）确定 通过下一代测序技术检测黑色素瘤表达的体细胞突变库; 2） 开发新的蛋白质组学平台以鉴定由HLA I类分子呈递的黑色素瘤新抗原; 3） 以验证疫苗接种方案中的新抗原鉴定。 拟议的管道将为肿瘤抗原识别提供一个变革性的解决方案， 可转化为其他“免疫反应”恶性肿瘤，并使新生学科的精确 为癌症患者提供有效和安全的免疫疗法。

Project Summary Cancer immunotherapy is now established as a major therapeutic modality. Significant progress with checkpoint inhibitor monoclonal antibodies demonstrates durable tumor regression in metastatic melanoma, lung cancer and other malignancies. One conspicuous limitation is the paucity of validated tumor antigens, which impedes clinical investigators in their pursuit of developing new cancer immunotherapies. Tumor encoded non-synonymous mutations may provide a new source of potential target antigens. T cells recognize tumor missense mutations as amino acid substituted peptides presented in the context of major histocompatibility molecules on the cancer cell surface, thus implicating missense mutations as a source of patient-specific neoantigens. We recently described the first-in-human study to use next generation sequencing technologies to identify and validate tumor missense mutations as neoantigens. Our study demonstrates that vaccination increases the breadth and diversity of neoantigen-specific T cells resulting in a broad repertoire of effector CD8+ T cells that uniquely discriminates mutated antigens from wild type peptides ensuring tumor specificity. This proposal aims to find a unique solution to the scarcity of tumor antigens by developing a neoantigen discovery pipeline that integrates genomic and proteomic technologies. In this proposal, a unique academic-industry partnership comprised of an established team of experts, in cancer genomics, cancer proteomics, human immunology, and clinical oncology, aim to solve the challenging problem of tumor neoantigen discovery. The long-term goal is to develop a robust pipeline using cutting-edge technologies merged with machine learning algorithms to supply tumor neoantigens for clinical investigation. The goal of this proposal will be addressed in the experiments of the following specific aims: 1) to identify the repertoire of melanoma expressed somatic mutations by next generation sequencing technologies; 2) to develop a novel proteomics platform to identify melanoma neoantigens presented by HLA class I molecules; 3) to validate neoantigen identification in a vaccination protocol. The proposed pipeline will deliver a transformative solution for tumor antigen identification, should be translatable to other “immune responsive“ malignancies and enable the nascent discipline of precision medicine to provide effective and safe immunotherapies for cancer patients.