Zou Weijie, Chen Li, Mao Wenwen, Hu Su, Liu Yuanqing, Hu Chunhong
Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, China.
Institute of Medical Imaging of Soochow University, Suzhou, China.
Front Bioeng Biotechnol. 2021 Nov 22;9:772206. doi: 10.3389/fbioe.2021.772206. eCollection 2021.
Lung adenocarcinoma (LUAD) is an exceedingly diverse disease, making prognostication difficult. Inflammatory responses in the tumor or the tumor microenvironment can alter prognosis in the process of the ongoing cross-talk between the host and the tumor. Nonetheless, Inflammatory response-related genes' prognostic significance in LUAD, on the other hand, has yet to be determined. The clinical data as well as the mRNA expression patterns of LUAD patients were obtained from a public dataset for this investigation. In the TCGA group, a multigene prognostic signature was built utilizing LASSO Cox analysis. Validation was executed on LUAD patients from the GEO cohort. The overall survival (OS) of low- and high-risk cohorts was compared utilizing the Kaplan-Meier analysis. The assessment of independent predictors of OS was carried out utilizing multivariate and univariate Cox analyses. The immune-associated pathway activity and immune cell infiltration score were computed utilizing single-sample gene set enrichment analysis. GO keywords and KEGG pathways were explored utilizing gene set enrichment analysis. LASSO Cox regression analysis was employed to create an inflammatory response-related gene signature model. The high-risk cohort patients exhibited a considerably shorter OS as opposed to those in the low-risk cohort. The prognostic gene signature's predictive ability was demonstrated using receiver operating characteristic curve analysis. The risk score was found to be an independent predictor of OS using multivariate Cox analysis. The functional analysis illustrated that the immune status and cancer-related pathways for the two-risk cohorts were clearly different. The tumor stage and kind of immune infiltrate were found to be substantially linked with the risk score. Furthermore, the cancer cells' susceptibility to anti-tumor medication was substantially associated with the prognostic genes expression levels. In LUAD, a new signature made up of 8 inflammatory response-related genes may be utilized to forecast prognosis and influence immunological state. Inhibition of these genes could also be used as a treatment option.
肺腺癌(LUAD)是一种极为多样化的疾病,这使得预后预测变得困难。肿瘤或肿瘤微环境中的炎症反应会在宿主与肿瘤之间持续的相互作用过程中改变预后。然而,炎症反应相关基因在LUAD中的预后意义尚未确定。本研究从一个公共数据集中获取了LUAD患者的临床数据以及mRNA表达模式。在TCGA组中,利用LASSO Cox分析构建了一个多基因预后特征。对来自GEO队列的LUAD患者进行了验证。利用Kaplan-Meier分析比较了低风险和高风险队列的总生存期(OS)。利用多变量和单变量Cox分析对OS的独立预测因子进行了评估。利用单样本基因集富集分析计算免疫相关通路活性和免疫细胞浸润评分。利用基因集富集分析探索了GO关键词和KEGG通路。采用LASSO Cox回归分析建立了炎症反应相关基因特征模型。与低风险队列的患者相比,高风险队列的患者OS明显更短。利用受试者工作特征曲线分析证明了预后基因特征的预测能力。通过多变量Cox分析发现风险评分是OS的独立预测因子。功能分析表明,两个风险队列的免疫状态和癌症相关通路明显不同。发现肿瘤分期和免疫浸润类型与风险评分密切相关。此外,癌细胞对抗肿瘤药物的敏感性与预后基因表达水平密切相关。在LUAD中,由8个炎症反应相关基因组成的新特征可用于预测预后并影响免疫状态。抑制这些基因也可作为一种治疗选择。