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通过加权相关基因网络分析结合差异基因表达分析确定，LGALS1与透明细胞肾细胞癌的预后相关。

LGALS1 was related to the prognosis of clear cell renal cell carcinoma identified by weighted correlation gene network analysis combined with differential gene expression analysis.

作者信息

Fang Jiang, Wang Xinjun, Xie Jun, Zhang Xi, Xiao Yiming, Li JinKun, Luo Guangcheng

机构信息

Zhongshan Hospital Xiamen University, School of Medicine, Xiamen University, Xiamen, China.

Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, China.

出版信息

Front Genet. 2023 Jan 12;13:1046164. doi: 10.3389/fgene.2022.1046164. eCollection 2022.

DOI:10.3389/fgene.2022.1046164
PMID:36712844
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9878452/
Abstract

Understanding the molecular mechanism of clear cell renal cell carcinoma (ccRCC) is essential for predicting the prognosis and developing new targeted therapies. Our study is to identify hub genes related to ccRCC and to further analyze its prognostic significance. The ccRCC gene expression profiles of GSE46699 from the Gene Expression Omnibus (GEO) database and datasets from the Cancer Genome Atlas Database The Cancer Genome Atlas were used for the Weighted Gene Co-expression Network Analysis (WGCNA) and differential gene expression analysis. We screened out 397 overlapping genes from the four sets of results, and then performed Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genome (KEGG) pathways. In addition, the protein-protein interaction (PPI) network of 397 overlapping genes was mapped using the STRING database. We identified ten hub genes (KNG1, TIMP1, ALB, C3, GPC3, VCAN, P4HB, CHGB, LGALS1, EGF) using the CytoHubba plugin of Cytoscape based on the Maximal Clique Centrality (MCC) score. According to Kaplan-Meier survival analysis, higher expression of LGALS1 and TIMP1 was related to poorer overall survival (OS) in patients with ccRCC. Univariate and multivariate Cox proportional hazard analysis showed that the expression of LGALS1 was an independent risk factor for poor prognosis. Moreover, the higher the clinical grade and stage of ccRCC, the higher the expression of LGALS1. LGALS1 may play an important role in developing ccRCC and may be potential a biomarker for prognosis and treatment targets.

摘要

了解透明细胞肾细胞癌（ccRCC）的分子机制对于预测预后和开发新的靶向治疗至关重要。我们的研究旨在识别与ccRCC相关的枢纽基因，并进一步分析其预后意义。使用来自基因表达综合数据库（GEO）的GSE46699的ccRCC基因表达谱以及来自癌症基因组图谱数据库的数据集进行加权基因共表达网络分析（WGCNA）和差异基因表达分析。我们从四组结果中筛选出397个重叠基因，然后进行基因本体（GO）富集分析和京都基因与基因组百科全书（KEGG）通路分析。此外，使用STRING数据库绘制了397个重叠基因的蛋白质-蛋白质相互作用（PPI）网络。我们基于最大团中心性（MCC）评分，使用Cytoscape的CytoHubba插件鉴定了十个枢纽基因（KNG1、TIMP1、ALB、C3、GPC3、VCAN、P4HB、CHGB、LGALS1、EGF）。根据Kaplan-Meier生存分析，LGALS1和TIMP1的高表达与ccRCC患者较差的总生存期（OS）相关。单因素和多因素Cox比例风险分析表明，LGALS1的表达是预后不良的独立危险因素。此外，ccRCC的临床分级和分期越高，LGALS1的表达越高。LGALS1可能在ccRCC的发生发展中起重要作用，可能是潜在的预后生物标志物和治疗靶点。

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