整合多种单细胞技术解析肿瘤浸润免疫细胞的耗竭机制

Cancer immunotherapy is one of the most promising and exciting approaches for treating cancers, among which one approach uses immune checkpoint inhibitors to reinvigorate tumor infiltrating immune cells (especially tumor-infiltrating lymphocytes) to enhance the immunity system for killing cancer cell. In order to develop efficient approaches for reinvigorating the tumor infiltrating immune cells, systematically examining the cell subtypes among tumor infiltrating immune cells and investigating the mechanisms of cell exhaustion are essential. In this proposal, we will sort infiltrating immune cells and normal leukocytes (CD45+) from cell suspension cultures that derived from tumor tissue and adjacent normal tissue of colorectal cancer patients, respectively. Then conduct single cell RNA-seq and single cell DNase-seq on tumor infiltrating immune cells and normal leukocytes for generating cell atlas of tumor infiltrating immune cells. We will analyze the high-throughput single cell data to perform cell clustering, detect cell subpopulation, identify subpopulation specific genes and subpopulation specific epigenetic tags, construct single cell regulatory network and so on. We will identify the major axis of genetic variation associated with cell exhaustion among PCs, and identify the genes and transcriptional factors associated with the variation axis. We could further infer the transcriptional factors that change the landscape of epigenetics among single cells by motif analysis, which are more likely to play causal role in cell exhaustion. By integrating pseudotime inference, we will build a cell exhaustion model for predicting key signal pathways and transcriptional factors during cell exhaustion. After completion of this project, we could provide a comprehensive cell atlas of tumor infiltrating immune cells. We also could provide the unique expression tags and unique epigenetic tags of each subpopulation of tumor infiltrating immune cells, which could greatly facilitate comprehensive clinical diagnosis of cancer. Especially, this study about cell exhaustion will promote the development of new immunotherapy approach that targeted tumor infiltrating immune cells.

肿瘤免疫治疗（Cancer immunotherapy）被认为是最有希望彻底征服癌症的方法，其中一类重要方法是将丧失杀伤力的肿瘤浸润免疫细胞（特别是耗竭T细胞）作为免疫治疗的靶点。发展高效激活肿瘤浸润免疫细胞杀伤力方法的关键是掌握这些免疫细胞的亚型特征及其耗竭机制。本项目将对大肠癌组织内肿瘤浸润免疫细胞和癌旁组织内免疫细胞进行单细胞RNA测序和单细胞DNase测序，利用单细胞数据解析肿瘤浸润免疫细胞的细胞亚型、亚型特异性基因、亚型特异性表观标签、亚型特异性信号通路等，最终构建大肠癌肿瘤浸润免疫细胞的详细图谱。利用数据降维鉴定与细胞耗竭过程相关的主变量轴，寻找与该变量轴高度相关的基因和关键调控因子，整合单细胞假时间分析建立细胞耗竭过程的数学模型。通过模型预测细胞耗竭发生的关键信号通路和免疫治疗靶点，并对预测结果进行初步实验验证。本项目的结果将为寻找激活耗竭细胞的新途径和新方法提供指导。

单细胞测序技术的快速发展为我们研究肿瘤免疫微环境和肿瘤发生提供了新的手段。我们开发了检测同一细胞的染色质可及性和基因表达的单细胞多模态测序技术ISSAAC-seq，建立了两种单细胞染色质可及性测序技术。我们开发了基于图形自编码器的单细胞组学数据降维方法scGAE。针对组学大数据开发了序列数据素描法kssd对其实时分析。这些新的单细胞测序技术使得我们建立了完善的且独特的单细胞组学平台。我们招募了20个结直肠癌患者并对结直肠癌的肿瘤组织和癌旁组织进行了单细胞转录组测序。基于单细胞测序数据构建了结直肠癌的肿瘤免疫微环境细胞图谱，我们筛选了耗竭T细胞特异性标签来检测肿瘤浸润免疫细胞的耗竭程度。我们发现肿瘤相关髓系细胞高表达携带ITIM域的受体如SIRPA, CLEC4A 和 SIGLEC9等。建立这些基因的敲除小鼠模型分别作分析，发现Sirpa-/-小鼠能够强烈抑制肿瘤的形成。我们发现Sirpa敲除使得小鼠形成抑制肿瘤发生的免疫微环境。使用抗PDL1处理荷瘤Sirpa-/-小鼠后，肿瘤消失。说明Sirpa是肿瘤免疫治疗的潜在靶点，我们与合作者正在研发Sirpa的新型单抗进一步开展免疫治疗的实验。另一方面，我们对血癌的骨髓微环境进行了刻画，分析了每个血癌患者的癌细胞状态和骨髓微环境。利用单细胞测序对一名急性淋系血癌患者在诊断、治疗、缓解、复发四个时期的样本进行分析，解析了其体内癌细胞动态。开发了综合对应指数CCI对血癌分型和治疗效果预测。我们把癌细胞亚群映射到造血分化树上的位置推演癌细胞亚群的谱系来源、癌细胞分化状态和血癌亚型等信息。我们发现当癌细胞映射的位置离造血发育分化树的树根越近，其预后越差，相反预后越好。这些成果发表在Nature Methods、Cell Discovery、 Genome Biology、Nature Protocols等期刊。申请专利 3 项。

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