Mou Zezhong, Yang Chen, Zhang Zheyu, Wu Siqi, Xu Chenyang, Cheng Zhang, Dai Xiyu, Chen Xinan, Ou Yuxi, Jiang Haowen
Department of Urology, Huashan Hospital, Fudan University, Shanghai, China.
Fudan Institute of Urology, Huashan Hospital, Fudan University, Shanghai, China.
Front Genet. 2020 Dec 23;11:566918. doi: 10.3389/fgene.2020.566918. eCollection 2020.
Bladder carcinoma (BC) is one of the most prevalent and malignant tumors. Multiple gene signatures based on BC metabolism, especially regarding glycolysis, remain unclear. Thus, we developed a glycolysis-related gene signature to be used for BC prognosis prediction.
Transcriptomic and clinical data were divided into a training set and a validation set after they were downloaded and analyzed from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Gene-set enrichment analysis (GSEA) and differential analysis were used to screen differentially expressed genes (DEGs), while univariate Cox regression and lasso-penalized Cox regression were employed for signature establishment. To evaluate the prognostic power of the signature, receiver operating characteristic (ROC) curve and Kaplan-Meier (KM) survival analysis were also used. Additionally, we developed a nomogram to predict patients' survival chances using the identified prognostic gene signature. Further, gene mutation and protein expression, as well as the independence of signature genes, were also analyzed. Finally, we also performed qPCR and western blot to detect the expression and potential pathways of signature genes in BC samples.
Ten genes were selected for signature construction among 71 DEGs, including nine risk genes and one protection gene. KM survival analysis revealed that the high-risk group had poor survival and the low-risk group had increased survival. ROC curve analysis and the nomogram validated the accurate prediction of survival using a gene signature composed of 10 glycolysis-related genes. Western blot and qPCR analysis demonstrated that the expression trend of signature genes was basically consistent with previous results. These 10 glycolysis-related genes were independent and suitable for a signature.
Our current study indicated that we successfully built and validated a novel 10-gene glycolysis-related signature for BC prognosis.
膀胱癌（BC）是最常见的恶性肿瘤之一。基于BC代谢，尤其是糖酵解的多个基因特征仍不清楚。因此，我们开发了一种与糖酵解相关的基因特征用于BC预后预测。
从癌症基因组图谱（TCGA）和基因表达综合数据库（GEO）下载并分析转录组学和临床数据，将其分为训练集和验证集。基因集富集分析（GSEA）和差异分析用于筛选差异表达基因（DEG），而单变量Cox回归和套索惩罚Cox回归用于建立特征。为了评估该特征的预后能力，还使用了受试者工作特征（ROC）曲线和Kaplan-Meier（KM）生存分析。此外，我们开发了一种列线图，使用确定的预后基因特征来预测患者存活几率。进一步分析了基因突变和蛋白质表达以及特征基因的独立性。最后，我们还进行了qPCR和蛋白质印迹，以检测BC样本中特征基因的表达和潜在途径。
在71个DEG中选择了10个基因用于构建特征，包括9个风险基因和1个保护基因。KM生存分析显示，高危组生存率低，低危组生存率增加。ROC曲线分析和列线图验证了使用由10个与糖酵解相关的基因组成的基因特征对生存的准确预测。蛋白质印迹和qPCR分析表明，特征基因的表达趋势与先前结果基本一致。这10个与糖酵解相关的基因是独立的，适合作为一个特征。
我们目前的研究表明，我们成功构建并验证了一种用于BC预后的新型10基因糖酵解相关特征。
