T cell landscape of non-small cell lung cancer revealed by deep single-cell RNA sequencing. Homo sapiens

Cancer immunotherapies have shown sustained clinical responses in treating non-small cell lung cancer (NSCLC), but the clinical outcome is not uniform among patients, with complex tumour-immune interactions playing key roles. To depict and dissect the baseline landscape of the composition, lineage and functional states of tumor-infiltrating lymphocytes (TILs) in lung cancer, here we generated deep single-cell RNA sequencing data for 12346 T cells from the tumour, adjacent normal tissues and peripheral blood from 14 treatment-naïve NSCLC patients. Based on expression and TCR-based lineage tracking, we found a significant proportion of effector memory T cells with the same origin and similar functional states across peripheral blood and tumours, indicating the existence of systemic T cell immunity. We also observed tumour-infiltrating CD8+ T cells undergoing extensive clonal expansion and exhaustion in tumours, with two clusters of cells exhibiting states preceding exhaustion. Survival analysis on independent datasets suggested that high ratio of “pre-exhausted” to exhausted T cells was associated with better prognosis of lung adenocarcinoma. In addition, we observed a specific cluster of tumour-specific regulatory T cells (Tregs), characterized by a set of immunosuppressive genes, and high expression of their signature genes, including IL1R2, correlated with poor prognosis of lung adenocarcinoma. These findings and the accompanying compendium of single cell data will help the research community to gain further insight into the functional states and dynamics of T cell responses in lung cancer. Overall design: T cells from NSCLC patients were sorted, profiled by Smart-seq2 and sequenced on Illumina HiSeq2500/HiSeq4000. Based on FACS analysis, single cells of different subtypes, including CD8+ T cells (CD3+ and CD8+), T helper cells (CD3+, CD4+ and CD25-), and regulatory T cells (CD3+, CD4+ and CD25high) were sorted to perform RNA sequencing. The categories （"sampleType" column in the SAMPLES section） contain PTC(CD8+ T cells from peripheral blood), NTC(CD8+ T cells from adjacent normal lung tissues) ,TTC (CD8+ T cells from tumor), PTH(CD3+, CD4+ and CD25- T cells from peripheral blood), NTH(CD3+, CD4+ and CD25- T cells from adjacent normal lung tissues), TTH(CD3+, CD4+ and CD25- T cells from tumor), PTR(CD3+, CD4+ and CD25high T cells from peripheral blood), NTR(CD3+, CD4+ and CD25high T cells from adjacent normal lung tissues), TTR(CD3+, CD4+ and CD25high T cells from tumor), PTY(CD3+, CD4+ and CD25mediate T cells from peripheral blood), NTY(CD3+, CD4+ and CD25mediate T cells from adjacent normal lung tissues), TTY(CD3+, CD4+ and CD25medate T cells from tumor). Raw data access provided at: European Genome-phenome Archive (EGA) under accession EGAS00001002430

癌症免疫疗法在非小细胞肺癌（non-small cell lung cancer, NSCLC）的治疗中已展现出持久的临床应答，但不同患者的临床结局并不均一，复杂的肿瘤-免疫互作在此过程中发挥关键调控作用。
为刻画并解析肺癌中肿瘤浸润淋巴细胞（tumor-infiltrating lymphocytes, TILs）的组成、谱系及功能状态的基线图谱，本研究对14名初治非小细胞肺癌患者的肿瘤组织、癌旁正常组织及外周血中的12346个T细胞开展了深度单细胞RNA测序。基于基因表达谱及基于T细胞受体（T cell receptor, TCR）的谱系追踪分析，我们发现外周血与肿瘤组织中存在大量源自同一谱系、功能状态相似的效应记忆T细胞，这提示系统性T细胞免疫的存在。我们还观察到肿瘤内的CD8+浸润性T细胞发生了广泛的克隆扩增与功能耗竭，其中存在两个细胞簇，其功能状态处于耗竭前阶段。对独立数据集的生存分析显示，“耗竭前”T细胞与耗竭T细胞的高比例与肺腺癌的良好预后显著相关。此外，我们鉴定到一群特异性的肿瘤特异性调节性T细胞（regulatory T cells, Tregs），该细胞群以表达一系列免疫抑制基因为特征；其特征基因（包括IL1R2）的高表达与肺腺癌的不良预后显著相关。本研究的上述发现及配套的单细胞数据集将助力科研领域进一步解析肺癌中T细胞应答的功能状态与动态变化。
实验整体设计：
T细胞从非小细胞肺癌患者体内分选获得，采用Smart-seq2技术进行转录组分析，并在Illumina HiSeq2500/HiSeq4000测序平台上完成测序。基于荧光激活细胞分选（fluorescence-activated cell sorting, FACS）分析，本研究分选了不同亚型的单个细胞，包括CD8+ T细胞（CD3+且CD8+）、辅助性T细胞（CD3+、CD4+且CD25-）以及调节性T细胞（CD3+、CD4+且CD25high），并对其进行RNA测序。
样本类别（SAMPLES板块中的"sampleType"列）包含以下类型：PTC（外周血来源CD8+ T细胞）、NTC（癌旁正常肺组织来源CD8+ T细胞）、TTC（肿瘤组织来源CD8+ T细胞）、PTH（外周血来源CD3+、CD4+且CD25- T细胞）、NTH（癌旁正常肺组织来源CD3+、CD4+且CD25- T细胞）、TTH（肿瘤组织来源CD3+、CD4+且CD25- T细胞）、PTR（外周血来源CD3+、CD4+且CD25high T细胞）、NTR（癌旁正常肺组织来源CD3+、CD4+且CD25high T细胞）、TTR（肿瘤组织来源CD3+、CD4+且CD25high T细胞）、PTY（外周血来源CD3+、CD4+且CD25mediate T细胞）、NTY（癌旁正常肺组织来源CD3+、CD4+且CD25mediate T细胞）、TTY（肿瘤组织来源CD3+、CD4+且CD25medate T细胞）。
原始数据可于欧洲基因组-表型组档案库（European Genome-phenome Archive, EGA）中获取，登录号为EGAS00001002430。