Gene network profiling in muscle-invasive bladder cancer: A systematic review and meta-analysis.
Gene network profiling in muscle-invasive bladder cancer: A systematic review and meta-analysis.
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DOI：
10.1016/j.urolonc.2021.11.003
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发表时间：
2022-05
影响因子：
2.7
通讯作者：
Bukavina, Laura
中科院分区：
文献类型：
--
作者：
Isali, Ilaha;McClellan, Phillip;Calaway, Adam;Prunty, Megan;Abbosh, Phillip;Mishra, Kirtishri;Ponsky, Lee;Markt, Sarah;Psutka, Sarah P.;Bukavina, Laura
尚未研究通过基因表达综合数据集（GEO）确定肌层浸润性膀胱癌（MIBC）转录谱的荟萃分析。本研究旨在确定MIBC的基因表达谱，并确定潜在的候选基因和途径。通过公开可用的RNA测序（RNA-Seq）和微阵列数据审查和评估MIBC中的基因表达研究，以确定MIBC的潜在预后和治疗靶点。使用术语“基因”、“基因表达”和“膀胱癌”对奥维德MEDLINE、PubMed和Wiley科克伦对照试验中心登记数据库进行了系统性文献检索，检索时间为1990年1月1日至2021年3月，重点关注MIBC人群。在最后的分析中，纳入了全球环境展望数据集。Meta分析采用固定效应模型。使用ImaGEO和GeneMANIA软件对MIBC中差异表达的鉴定基因进行基因网络连接和基因集功能分析。沿着相关途径生成上调和下调基因的热图。在该分析中总共报告了9个基因。6个基因报告为上调（ProTα、SPINT 1、UBE 2 E1、RAB 25、KPNB 1、HDAC 1），3个基因报告为下调（NUP 188、IPO 13、NUP 124）。基因被发现参与“泛素介导的蛋白质水解”、“内质网中的蛋白质加工”、“癌症中的转录失调”和“RNA转运”途径。
Determining meta-analysis of transcriptional profiling of muscle-invasive bladder cancer (MIBC) through Gene Expression Omnibus (GEO) datasets has not been investigated. This study aims to define gene expression profiles in MIBC and to identify potential candidate genes and pathways. To review and evaluate gene expression studies in MIBC through publicly available RNA sequencing (RNA-Seq) and microarray data in order to identify potential prognostic and therapeutic targets for MIBC. A systematic literature search of the Ovid MEDLINE, PubMed, and Wiley Cochrane Central Register of Controlled Trials databases was performed using the terms “gene,” “gene expression,” and “bladder cancer” January 1, 1990 through March 2021 focused on populations with MIBC. In the final analysis, GEO datasets were included. Fixed effect model was employed in the meta-analysis. Gene networking connections and gene-set functional analyses of the identified genes as differentially expressed in MIBC were performed using ImaGEO and GeneMANIA software. A heatmap for the upregulated and downregulated genes was generated along with the correlated pathways. A total of 9 genes were reported in this analysis. Six genes were reported as upregulated (ProTα, SPINT1, UBE2E1, RAB25, KPNB1, HDAC1) and 3 genes as downregulated (NUP188, IPO13, NUP124). Genes were found to be involved in “ubiquitin mediated proteolysis,” “protein processing in endoplasmic reticulum,” “transcriptional misregulation in cancer,” and “RNA transport” pathways.
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