Zou Yong, Hu Chuan
Department of Oncology, The People's Hosipital of Hanchuan City, Hanchuan, Hubei, China.
PeerJ. 2020 Oct 29;8:e10183. doi: 10.7717/peerj.10183. eCollection 2020.
Kidney renal clear cell carcinoma (KIRC) is the leading cause of kidney cancer-related deaths. Currently, there are no studies in tumor immunology investigating the use of signatures as a predictor of overall survival in KIRC patients. Our study attempts to establish an immune-related gene risk signature to predict clinical outcomes in KIRC. A total of 528 patients from The Cancer Genome Atlas (TCGA) database were included in our analysis and randomly divided into training ( = 315) and testing sets ( = 213). We collected 1,534 immune-related genes from the Immunology Database and Analysis Portal as candidates to construct our signature. LASSO-COX was used to find gene models with the highest predictive ability. We used survival and Cox analysis to test the model's independent prognostic ability. Univariate analysis identified 650 immune-related genes with prognostic abilities. After 1,000 iterations, we choose 14 of the most frequent and stable immune-related genes as our signature. We found that the signature was associated with M stage, T stage, and pathological staging. More importantly, the signature can independently predict clinical prognosis in KIRC patients. Gene Set Enrichment Analysis (GSEA) showed an association between our signature and critical metabolism pathways. Our research established a model based upon 14 immune-related genes that predicted the prognosis of KIRC patients based on tumor immune microenvironments.
肾透明细胞癌(KIRC)是肾癌相关死亡的主要原因。目前,肿瘤免疫学领域尚无研究探讨将特征作为KIRC患者总生存期预测指标的应用。我们的研究试图建立一种免疫相关基因风险特征,以预测KIRC患者的临床结局。我们的分析纳入了来自癌症基因组图谱(TCGA)数据库的528例患者,并将其随机分为训练集(n = 315)和测试集(n = 213)。我们从免疫学数据库和分析门户收集了1534个免疫相关基因作为构建特征的候选基因。使用LASSO-COX方法寻找具有最高预测能力的基因模型。我们使用生存分析和Cox分析来检验该模型的独立预后能力。单因素分析确定了650个具有预后能力的免疫相关基因。经过1000次迭代后,我们选择了14个最常见且稳定的免疫相关基因作为我们的特征。我们发现该特征与M分期、T分期和病理分期相关。更重要的是,该特征能够独立预测KIRC患者的临床预后。基因集富集分析(GSEA)表明我们的特征与关键代谢途径之间存在关联。我们的研究基于14个免疫相关基因建立了一个模型,该模型可根据肿瘤免疫微环境预测KIRC患者的预后。