Single-cell transcriptomic profiling reveals the tumor heterogeneity of small-cell lung cancer

转录组 癌症研究 生物 仿形(计算机编程) 肺癌 细胞 计算生物学 病理 基因表达 基因 医学 遗传学 计算机科学 操作系统
作者
Yanhua Tian,Qingqing Li,Zhenlin Yang,Shu Zhang,Jiachen Xu,Zhijie Wang,Hua Bai,Jianchun Duan,Bo Zheng,Wen Li,Yueli Cui,Xin Wang,Rui Wan,Kailun Fei,Jia Zhong,Shugeng Gao,Jié He,Carl M. Gay,Jianjun Zhang,Jie Wang
出处
期刊:Signal Transduction and Targeted Therapy [Springer Nature]
卷期号:7 (1) 被引量:82
标识
DOI:10.1038/s41392-022-01150-4
摘要

Abstract Small-cell lung cancer (SCLC) is the most aggressive and lethal subtype of lung cancer, for which, better understandings of its biology are urgently needed. Single-cell sequencing technologies provide an opportunity to profile individual cells within the tumor microenvironment (TME) and investigate their roles in tumorigenic processes. Here, we performed high-precision single-cell transcriptomic analysis of ~5000 individual cells from primary tumors (PTs) and matched normal adjacent tissues (NATs) from 11 SCLC patients, including one patient with both PT and relapsed tumor (RT). The comparison revealed an immunosuppressive landscape of human SCLC. Malignant cells in SCLC tumors exhibited diverse states mainly related to the cell cycle, immune, and hypoxic properties. Our data also revealed the intratumor heterogeneity (ITH) of key transcription factors (TFs) in SCLC and related gene expression patterns and functions. The non-neuroendocrine (non-NE) tumors were correlated with increased inflammatory gene signatures and immune cell infiltrates in SCLC, which contributed to better responses to immune checkpoint inhibitors. These findings indicate a significant heterogeneity of human SCLC, and intensive crosstalk between cancer cells and the TME at single-cell resolution, and thus, set the stage for a better understanding of the biology of SCLC as well as for developing new therapeutics for SCLC.
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