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 该提案解决了PQ2：免疫功能的变化是如何引起的 合并症或在不同人群中观察到的合并症影响对癌症的反应 心理治疗 虽然免疫系统在控制和根除肿瘤中的作用已经被证实， 几十年来，免疫疗法一直被人们所知，只是在过去的几年里才出现 临床上可行的治疗癌症的方法。关于免疫反应是如何 按性别和种族划分的人口之间存在差异， 免疫浸润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，以剖析不同程度的 白细胞浸润对癌症预后的影响。PRECOG是一个大型的基因纲要， 包括39种不同癌症的近40，000例患者样本的表达数据集 组织学，可获得总生存信息（和其他结局）。 以前，我们使用PRECOG来评估免疫细胞水平对整体免疫系统的影响。 生存，确定癌症之间的共性和差异。许多这些 相关性是独立于治疗的，强调免疫系统是一个关键的 即使在标准化疗的背景下，患者反应的组成部分。 在这里，我们将扩展PRECOG，以纳入患者性别和 种族没有发表的研究系统地分析了相似性和差异性 免疫细胞类型对这些人群临床结果的影响。在这里我们确定 不同人群肿瘤之间的浸润免疫水平如何变化，以及 它们不同地影响对特定疗法的反应以及总存活率。这 将产生关于免疫浸润和功能变化的可检验假设 在人群之间。这些也将与对特定疗法的反应有关， 和总体生存率。使用新的反卷积方法，我们将进一步剖析 与存活和治疗反应相关的免疫功能。这张预测图将 阐明癌症人群的相似性和差异，并将 成为癌症免疫学界的强大新资源。