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.

项目概要 该提案解决了 PQ2：免疫功能的变化是如何引起的 不同人群中观察到的合并症会影响对癌症的反应 治疗？ 虽然免疫系统在控制和根除肿瘤方面的作用已经 免疫疗法已经被人们所知几十年了，直到最近几年才出现 作为一种临床上可行的癌症靶向方法。人们对免疫反应如何进行知之甚少 按性别和种族定义的人群之间存在差异，无论是在 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来剖析不同水平的影响 浸润白细胞对癌症结果的影响。 PRECOG 是基因大纲要 表达数据集包含 39 种不同癌症的近 40,000 个患者样本 组织学，可获得总体生存信息（和其他结果）。 之前我们使用 PRECOG 来评估免疫细胞水平对整体的影响 生存，识别癌症的共性和差异。其中许多 关联与治疗无关，强调免疫系统如何发挥关键作用 即使在标准化疗的情况下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。没有发表的研究系统地分析相似性和差异 免疫细胞类型对这些群体临床结果的影响。在这里我们识别 不同人群的肿瘤之间的浸润免疫水平有何不同，以及如何 它们对特定疗法的反应以及总体生存率产生不同的影响。这 将产生关于免疫浸润和功能变化的可检验假设 人群之间。这些也与对特定疗法的反应有关， 以及总体生存率。我们将使用新颖的反卷积方法进一步剖析 免疫功能与生存和治疗反应有关。这张预测图将 阐明癌症人群的相似点和差异，并将 成为癌症免疫学界强大的新资源。