Regulators of Cancer Immunotherapy Response

项目总结 尽管在治疗几种类型的癌症上取得了巨大的成功，但免疫检查点阻滞剂(ICB)疗法仍然 仅在一小部分患者中显示疗效。识别免疫治疗反应的新调节因子 随着癌症免疫疗法应答率的提高，仍是悬而未决的问题。最近，我们使用了 CRISPR在小鼠模型中进行筛查，以研究T细胞的渗透、增殖和杀伤效果 SWI/SNF染色质重塑复合体的PBAF是T细胞介导的一种新的调节因子 细胞毒性。我们还开发了一个名为TEDE的计算模型来识别CD8T细胞的基因特征 免疫热瘤的功能障碍和免疫冷瘤的T细胞排斥。所得到的签名， 根据非免疫治疗环境中的肿瘤轮廓计算，在预测黑色素瘤方面显示出有希望的结果 基于治疗前肿瘤表达的肺癌患者对免疫检查点阻断的反应 配置文件。 这项拟议的项目旨在改进浪潮生物标记物，识别新的调节剂，并阐明它们的 ICB反应的潜在机制。在目标1中，我们将开发大规模的机器学习方法 从非ICB环境中收集临床肿瘤转录组图谱以完善潮汐预测生物标记物 ，并开发了一个Web服务器来综合评价ICB反应的不同生物标志物 所有可用的ICB队列。在目标2中，我们将在小鼠同基因肿瘤中进行体内CRISPR筛选 识别ICB反应的癌细胞内在调节因子的模型，可作为改进的新靶点 ICB回应。在目标3中，我们将阐明ICB反应和ICB反应的两个新调节因子背后的机制 用单细胞RNA-SEQ、单细胞ATAC-SEA研究它们对肿瘤免疫微环境的影响 SEQ和计算建模。我们的调查团队结合了计算方面的专业知识 方法论 免疫疗法。 免疫学 以及大数据挖掘、功能基因组学图谱分析 我们提议的研究，如果成功实施， 以及对癌症免疫治疗的翻译益处。 以及筛查、癌症免疫学和 可以为癌症提供新的见解

PROJECT SUMMARY Despite enormous success in treating several types of cancer, immune checkpoint blocker (ICB) therapy still only shows efficacies in a subset of patients. Identifying novel regulators of immunotherapy response as well as improving the response rate of cancer immunotherapies remain open questions. Recently, we used CRISPR screens in mouse models to investigate T-cell infiltration, proliferation, and killing efficacy, and identified PBAF of the SWI/SNF chromatin remodeling complex as one novel regulator of T-cell mediated cytotoxicity. We also developed a computational model, TIDE, to identify gene signatures of CD8 T-cell dysfunction in immune hot tumors and T-cell exclusion in immune cold tumors. The resulting signatures, computed from tumor profiles in non-immunotherapy setting, show promising results in predicting melanoma and lung cancer patient response to immune checkpoint blockade based on pre-treatment tumor expression profiles. This proposed project aims to improve the TIDE biomarkers, identify novel regulators, and elucidate their mechanisms underlying ICB response. In Aim 1, we will develop machine learning approaches on large collection of clinical tumor transcriptome profiles from non-ICB settings to refine the TIDE predictive biomarker of ICB response, and develop a web server to comprehensively evaluate different ICB response biomarkers in all the available ICB cohorts. In Aim 2, we will conduct in vivo CRISPR screens in mouse syngeneic tumor models to identify cancer-cell intrinsic regulators of ICB response, which can serve as novel targets to improve ICB response. In Aim 3, we will elucidate the mechanism underlying two novel regulators of ICB response and characterize their effects on the tumor immune microenvironment using single-cell RNA-seq, single-cell ATAC- seq, and computational modeling. Our investigative team has combined expertise in computational methodology immunotherapy. immunology and big data mining, functional genomics profiling Our proposed studies, if successfully executed, and translational benefits to cancer immunotherapy. and screening, cancer immunology and could provide new insights into cancer