Klocke Christopher, Moran Amy, Adey Andrew, McWeeney Shannon, Wu Guanming
Division of Bioinformatics and Computational Biomedicine, Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, OR, USA.
Department of Cell, Developmental and Cancer Biology, Oregon Health & Science University, Portland, OR, USA.
bioRxiv. 2023 Nov 13:2023.11.09.566384. doi: 10.1101/2023.11.09.566384.
While immune checkpoint inhibitors show success in treating a subset of patients with certain late-stage cancers, these treatments fail in many other patients as a result of mechanisms that have yet to be fully characterized. The process of CD8 T cell exhaustion, by which T cells become dysfunctional in response to prolonged antigen exposure, has been implicated in immunotherapy resistance. Single-cell RNA sequencing (scRNA-seq) produces an abundance of data to analyze this process; however, due to the complexity of the process, contributions of other cell types to a process within a single cell type cannot be simply inferred. We constructed an analysis framework to first rank human skin tumor samples by degree of exhaustion in tumor-infiltrating CD8 T cells and then identify immune cell type-specific gene-regulatory network patterns significantly associated with T cell exhaustion. Using this framework, we further analyzed scRNA-seq data from human tumor and chronic viral infection samples to compare the T cell exhaustion process between these two contexts. In doing so, we identified transcription factor activity in the macrophages of both tissue types associated with this process. Our framework can be applied beyond the tumor immune microenvironment to any system involving cell-cell communication, facilitating insights into key biological processes that underpin the effective treatment of cancer and other complicated diseases.
虽然免疫检查点抑制剂在治疗某些晚期癌症的部分患者中取得了成功,但由于尚未完全明确的机制,这些治疗方法在许多其他患者中失败。CD8 T细胞耗竭过程,即T细胞因长期暴露于抗原而功能失调,与免疫治疗耐药性有关。单细胞RNA测序(scRNA-seq)产生了大量数据来分析这一过程;然而,由于该过程的复杂性,不能简单推断其他细胞类型对单一细胞类型内某一过程的贡献。我们构建了一个分析框架,首先根据肿瘤浸润性CD8 T细胞的耗竭程度对人类皮肤肿瘤样本进行排名,然后识别与T细胞耗竭显著相关的免疫细胞类型特异性基因调控网络模式。使用这个框架,我们进一步分析了来自人类肿瘤和慢性病毒感染样本的scRNA-seq数据,以比较这两种情况下的T细胞耗竭过程。在此过程中,我们确定了与该过程相关的两种组织类型巨噬细胞中的转录因子活性。我们的框架不仅可以应用于肿瘤免疫微环境,还可以应用于任何涉及细胞间通讯的系统,有助于深入了解支撑癌症和其他复杂疾病有效治疗的关键生物学过程。