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六个生存相关基因在膀胱癌中的预后价值。

The prognostic value of six survival-related genes in bladder cancer.

作者信息

Cheng Shuting, Jiang Zhou, Xiao Jing, Guo Huiling, Wang Zhengrong, Wang Yuhui

机构信息

Health Ministry Key Laboratory of Chronobiology, West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Chengdu, P.R. China.

出版信息

Cell Death Discov. 2020 Jul 13;6:58. doi: 10.1038/s41420-020-00295-x. eCollection 2020.

Abstract

This study was conducted to identify genes that are differentially expressed in paracancerous tissue and to determine the potential predictive value of selected gene panel. Gene transcriptome data of bladder tissue was downloaded from UCSC Xena browser and NCBI GEO repository, including GTEx (the Genotype-Tissue Expression project) data, TCGA (The Cancer Genome Atlas) data, and GEO (Gene Expression Omnibus) data. Differentially Expressed Genes (DEGs) analysis was performed to identify tumor-DEGs candidate genes, using the intersection of tumor-paracancerous DEGs genes and paracancerous-normal DEGs genes. The survival-related genes were screened by Kaplan-Meier (KM) survival analysis and univariable Cox regression with the cutoff criteria of KM < 0.05 and cox -value < 0.05. The risk model was developed using Lasso regression. The clinical data were analyzed by univariate and multivariate Cox regression analysis. Gene Ontology (GO) and KEGG enrichment analysis were performed in the DEGs genes between the high-risk and low-risk subgroups. We identified six survival-related genes, EMP1, TPM1, NRP2, FGFR1, CAVIN1, and LATS2, found in the DEG analyses of both, tumor-paracancerous and paracancerous-normal differentially expressed data sets. Then, the patients were classified into two clusters, which can be distinguished by specific clinical characteristics. A three-gene risk prediction model (EMP1, FGFR1, and CAVIN1) was constructed in patients within cluster 1. The model was applied to categorize cluster 1 patients into high-risk and low-risk subgroups. The prognostic risk score was considered as an independent prognostic factor. The six identified survival-related genes can be used in molecular characterization of a specific subtype of bladder cancer. This subtype had distinct clinical features of T (topography), N (lymph node), stage, grade, and survival status, compared to the other subtype of bladder cancer. Among the six identified survival-related genes, three-genes, EMP1, FGFR1, and CAVIN1, were identified as potential independent prognostic markers for the specific bladder cancer subtype with clinical features described.

摘要

本研究旨在鉴定在癌旁组织中差异表达的基因,并确定所选基因panel的潜在预测价值。膀胱组织的基因转录组数据从UCSC Xena浏览器和NCBI GEO数据库下载,包括GTEx(基因型-组织表达项目)数据、TCGA(癌症基因组图谱)数据和GEO(基因表达综合数据库)数据。通过使用肿瘤-癌旁差异表达基因和癌旁-正常差异表达基因的交集进行差异表达基因(DEGs)分析,以鉴定肿瘤DEGs候选基因。通过Kaplan-Meier(KM)生存分析和单变量Cox回归筛选生存相关基因,截断标准为KM<0.05和cox值<0.05。使用Lasso回归建立风险模型。通过单变量和多变量Cox回归分析临床数据。对高风险和低风险亚组之间的DEGs基因进行基因本体(GO)和KEGG富集分析。我们在肿瘤-癌旁和癌旁-正常差异表达数据集的DEG分析中发现了六个生存相关基因,即EMP1、TPM1、NRP2、FGFR1、CAVIN1和LATS2。然后,将患者分为两个簇,这两个簇可通过特定临床特征区分。在簇1患者中构建了一个三基因风险预测模型(EMP1、FGFR1和CAVIN1)。该模型用于将簇1患者分为高风险和低风险亚组。预后风险评分被视为独立的预后因素。所鉴定的六个生存相关基因可用于膀胱癌特定亚型的分子特征分析。与膀胱癌的其他亚型相比,该亚型在T(部位)、N(淋巴结)、分期、分级和生存状态方面具有独特的临床特征。在鉴定出的六个生存相关基因中,三个基因EMP1、FGFR1和CAVIN1被确定为具有所述临床特征的特定膀胱癌亚型的潜在独立预后标志物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9fe5/7359373/d07928c0886f/41420_2020_295_Fig1_HTML.jpg

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