颜林林 (2022-07-09 07:36):
#paper doi:10.1186/s13073-022-01079-x Genome Medicine, 2022, Identification of a cytokine-dominated immunosuppressive class in squamous cell lung carcinoma with implications for immunotherapy resistance. 这是一篇纯数据挖掘的文章,试图回答肺鳞癌中免疫检查点抑制剂耐药的机制问题。文章通过收集了来自TCGA和GEO的624例肺鳞癌转录组数据,使用无监督聚类,从中识别出与 T 细胞衰竭特征、免疫抑制细胞、临床特征和免疫治疗反应相关的表达模式,并定义了一组衰竭免疫等级 (EIC) 的免疫抑制患者。这些患者占到28%至36%,尽管他们表现出高密度的肿瘤浸润淋巴细胞,却因显著富集、高比例的免疫抑制细胞、多个免疫检查点基因同时上调等特性,表现出对ICB的耐药性。相应的表达特征,在具有 ICB 治疗抗性的黑色素瘤患者中也得到印证。文章还检查了基因组和表观组的数据,发现这些患者呈现出较低的染色体突变负担和独特的甲基化模式。由此,作者还建立了一个在线网站,整合了用到的数据及分析方法,供研究人员使用多组学数据分析来研究 ICB 耐药性的潜在关联。从分析方法看,这篇文章的套路应该是比较常见的,算不上有什么创新性,不过在单病种上整合数据,并以在线网站的形式来使分析过程能够泛化并提供他人使用,也算是一类可行的生信“原创”工作吧。
IF:10.400Q1 Genome medicine, 2022-07-08. DOI: 10.1186/s13073-022-01079-x PMID: 35799269
Identification of a cytokine-dominated immunosuppressive class in squamous cell lung carcinoma with implications for immunotherapy resistance
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Abstract:
BACKGROUND: Immune checkpoint blockade (ICB) therapy has revolutionized the treatment of lung squamous cell carcinoma (LUSC). However, a significant proportion of patients with high tumour PD-L1 expression remain resistant to immune checkpoint inhibitors. To understand the underlying resistance mechanisms, characterization of the immunosuppressive tumour microenvironment and identification of biomarkers to predict resistance in patients are urgently needed.METHODS: Our study retrospectively analysed RNA sequencing data of 624 LUSC samples. We analysed gene expression patterns from tumour microenvironment by unsupervised clustering. We correlated the expression patterns with a set of T cell exhaustion signatures, immunosuppressive cells, clinical characteristics, and immunotherapeutic responses. Internal and external testing datasets were used to validate the presence of exhausted immune status.RESULTS: Approximately 28 to 36% of LUSC patients were found to exhibit significant enrichments of T cell exhaustion signatures, high fraction of immunosuppressive cells (M2 macrophage and CD4 Treg), co-upregulation of 9 inhibitory checkpoints (CTLA4, PDCD1, LAG3, BTLA, TIGIT, HAVCR2, IDO1, SIGLEC7, and VISTA), and enhanced expression of anti-inflammatory cytokines (e.g. TGFβ and CCL18). We defined this immunosuppressive group of patients as exhausted immune class (EIC). Although EIC showed a high density of tumour-infiltrating lymphocytes, these were associated with poor prognosis. EIC had relatively elevated PD-L1 expression, but showed potential resistance to ICB therapy. The signature of 167 genes for EIC prediction was significantly enriched in melanoma patients with ICB therapy resistance. EIC was characterized by a lower chromosomal alteration burden and a unique methylation pattern. We developed a web application ( http://lilab2.sysu.edu.cn/tex & http://liwzlab.cn/tex ) for researchers to further investigate potential association of ICB resistance based on our multi-omics analysis data.CONCLUSIONS: We introduced a novel LUSC immunosuppressive class which expressed high PD-L1 but showed potential resistance to ICB therapy. This comprehensive characterization of immunosuppressive tumour microenvironment in LUSC provided new insights for further exploration of resistance mechanisms and optimization of immunotherapy strategies.
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