The prognostic landscape of gender- and ethnicity-specific immune influences on cancer outcomes

性别和种族特异性免疫对癌症结果影响的预后情况

• 批准号: 9888350
• 负责人: Andrew J. Gentles
• 金额: $ 20.42万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-04-01 至 2022-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9888350
• 关键词: Address; Affect; Age; Automobile Driving; CTLA4 gene; Cancer Histology; Cancer Patient; Cells; Clinical; Communities; Data; Data Set; Ethnic Origin; Expression Profiling; Follow-Up Studies; Gender; Gene Expression; Gene Expression Profile; Genetic Transcription; Immune; Immune checkpoint inhibitor; Immune response; Immune system; Immunologics; Immunotherapy; Leukocytes; Malignant Neoplasms; Maps; Meta-Analysis; Methods; Molecular; Outcome; Patients; Population; Prognostic Factor; Publishing; Race; Resources; Role; Sampling; Subgroup; Survival Analysis; Testing; Tissue-Specific Gene Expression; Tumor stage; Tumor-infiltrating immune cells; Variant; anticancer research; cancer therapy; cell type; chemotherapy; comorbidity; differential expression; digital; genomic data; immune function; neoplasm resource; novel; patient response; patient subsets; prognostic; programmed cell death ligand 1; programs; response; survival outcome; tumor

Project Summary This proposal addresses PQ2: How do variations in immune function caused by comorbidities or observed among different populations affect response to cancer therapy? While the role of the immune system in controlling and eradicating tumors has been known for decades, it is only in the past few years that immunotherapy has emerged as a clinically viable way to target cancer. Little is known about how the immune response differs between populations defined by gender and ethnicity, either in terms of levels of immune infiltration or the intrinsic functionality of specific immune cell types. We are developing resources and methods to dissect the impact of levels of infiltrating leukocytes on cancer outcomes. PRECOG is a large compendium of gene expression datasets comprising nearly 40,000 patient samples across 39 distinct cancer histologies, for which overall survival information (and other outcomes) is available. Previously we used PRECOG to assess the influence of immune cell levels on overall survival, identifying commonalities and differences across cancer. Many of these associations were therapy-independent, emphasizing how the immune system is a critical component of patient response even in the context of standard chemotherapy. Here we will extend PRECOG to incorporate information on patient gender and ethnicity. No published studies have systematically analyzed similarities and differences in the impact of immune cell types on clinical outcomes in these groups. Here we identify how infiltrating immune levels vary between tumors from different populations, and how they differentially affect responses to specific therapies as well as overall survival. This will generate testable hypotheses regarding variations in immune infiltration and function between populations. These will also be associated with response to specific therapies, and with overall survival. Using novel deconvolution approaches we will further dissect immune function in relation to survival and therapy response. This prognostic map will illuminate similarities and differences across the landscape of cancer populations and will be a powerful new resource for the cancer immunologic community.

项目摘要 这项建议解决了PQ2：如何导致免疫功能的变化 不同人群之间的共病或观察到的影响对癌症的反应 治疗？ 而免疫系统在控制和根除肿瘤方面的作用 几十年来一直为人所知的免疫疗法直到最近几年才出现 作为一种临床上可行的治疗癌症的方法。关于免疫反应是如何产生的，我们知之甚少 在由性别和种族定义的人口之间存在差异，无论是在 免疫渗透或特定免疫细胞类型的内在功能。 我们正在开发资源和方法来分析不同水平的 白细胞渗入对癌症预后的影响。Precg是一个很大的基因概要 包含39种不同癌症的近40,000个患者样本的表达数据集 组织学，其总体生存信息(和其他结果)是可用的。 之前，我们使用PRECOG来评估免疫细胞水平对总体的影响 生存，识别癌症之间的共性和差异。其中许多 协会是不依赖于治疗的，强调免疫系统是如何关键的 即使在标准化疗的情况下，这也是患者反应的组成部分。 在这里，我们将扩展PRECOG，以纳入有关患者性别和 种族问题。目前还没有发表的研究对异同进行系统的分析。 在这些群体中，免疫细胞类型对临床结果的影响。在这里，我们确定 来自不同人群的肿瘤之间的浸润性免疫水平如何不同，以及如何 它们对特定治疗的反应以及总体存活率有不同的影响。这 将产生关于免疫渗透和功能变化的可测试假说 在种群之间。这些也将与对特定疗法的反应有关， 以及整体的生存。使用新的反卷积方法，我们将进一步剖析 免疫功能与生存和治疗反应的关系。这张预测地图将 阐明不同癌症人群和意愿的异同 为癌症免疫学社区提供强大的新资源。