早期肺鳞状细胞癌中一种先天性免疫相关预后特征的鉴定
Identification of an Innate Immune-Related Prognostic Signature in Early-Stage Lung Squamous Cell Carcinoma.
作者信息
Li Liang, Yu Xue, Ma Guanqiang, Ji Zhiqi, Bao Shihao, He Xiaopeng, Song Liang, Yu Yang, Shi Mo, Liu Xiangyan
机构信息
Department of Thoracic Surgery, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, 250021, People's Republic of China.
Department of Pediatrics, Wuhan Children's Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 420100, People's Republic of China.
出版信息
Int J Gen Med. 2021 Nov 30;14:9007-9022. doi: 10.2147/IJGM.S341175. eCollection 2021.
BACKGROUND
Early-stage lung squamous cell carcinoma (LUSC) progression is accompanied by changes in immune microenvironments and the expression of immune-related genes (IRGs). Identifying innate IRGs associated with prognosis may improve treatment and reveal new immunotherapeutic targets.
METHODS
Gene expression profiles and clinical data of early-stage LUSC patients were obtained from the Gene Expression Omnibus and The Cancer Genome Atlas databases and IRGs from the InnateDB database. Univariate and multivariate Cox regression and LASSO regression analyses were performed to identify an innate IRG signature model prognostic in patients with early-stage LUSC. The predictive ability of this model was assessed by time-dependent receiver operator characteristic curve analysis, with the independence of the model-determined risk score assessed by univariate and multivariate Cox regression analyses. Overall survival (OS) in early-stage LUSC patients was assessed using a nomogram and decision curve analysis (DCA). Functional and biological pathways were determined by gene set enrichment analysis, and differences in biological functions and immune microenvironments between the high- and low-risk groups were assessed by ESTIMATE and the CIBERSORT algorithm.
RESULTS
A signature involving six IRGs (SREBF2, GP2, BMX, NR1H4, DDX41, and GOPC) was prognostic of OS. Samples were divided into high- and low-risk groups based on median risk scores. OS was significantly shorter in the high-risk than in the low-risk group in the training (P < 0.001), GEO validation (P = 0.00021) and TCGA validation (P = 0.034) cohorts. Multivariate Cox regression analysis showed that risk score was an independent risk factor for OS, with the combination of risk score and T stage being optimally predictive of clinical benefit. GSEA, ESTIMATE, and the CIBERSORT algorithm showed that immune cell infiltration was higher and immune-related pathways were more strongly expressed in the low-risk group.
CONCLUSION
A signature that includes these six innate IRGs may predict prognosis in patients with early-stage LUSC.
背景
早期肺鳞状细胞癌（LUSC）进展伴随着免疫微环境的变化以及免疫相关基因（IRG）的表达。识别与预后相关的固有IRG可能会改善治疗并揭示新的免疫治疗靶点。
方法
从基因表达综合数据库和癌症基因组图谱数据库中获取早期LUSC患者的基因表达谱和临床数据，并从InnateDB数据库中获取IRG。进行单变量和多变量Cox回归以及LASSO回归分析，以识别早期LUSC患者中具有预后价值的固有IRG特征模型。通过时间依赖性受试者工作特征曲线分析评估该模型的预测能力，并通过单变量和多变量Cox回归分析评估模型确定的风险评分的独立性。使用列线图和决策曲线分析（DCA）评估早期LUSC患者的总生存期（OS）。通过基因集富集分析确定功能和生物学途径，并通过ESTIMATE和CIBERSORT算法评估高风险组和低风险组之间生物学功能和免疫微环境的差异。
结果
一个包含六个IRG（SREBF2、GP2、BMX、NR1H4、DDX41和GOPC）的特征对OS具有预后价值。根据中位风险评分将样本分为高风险组和低风险组。在训练队列（P < 0.001）、GEO验证队列（P = 0.00021）和TCGA验证队列（P = 0.034）中，高风险组的OS明显短于低风险组。多变量Cox回归分析表明，风险评分是OS的独立危险因素，风险评分与T分期的组合对临床获益具有最佳预测性。GSEA、ESTIMATE和CIBERSORT算法表明，低风险组的免疫细胞浸润更高，免疫相关途径的表达更强。
结论
包含这六个固有IRG的特征可能预测早期LUSC患者的预后。
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