Identification of Biomarkers for Bladder Cancer Based on WGCNA and LASSO Analyses
10.11969/j.issn.1673-548X.2025.03.011
- VernacularTitle:基于WGCNA和LASSO分析的膀胱癌生物学标志物鉴定
- Author:
Shuheng WANG
1
;
Weiwei LIU
;
Jiuzhi LI
Author Information
1. 830002 乌鲁木齐,新疆维吾尔自治区人民医院泌尿科
- Publication Type:Journal Article
- Keywords:
Bladder cancer;
Bioinformatics;
Weighted gene coexpression network analysis;
Biomarker
- From:
Journal of Medical Research
2025;54(3):54-61,89
- CountryChina
- Language:Chinese
-
Abstract:
Objective Bladder cancer(BLCA)is a common disease,and the pathogenesis of which is not clear.This study aims to find the key genes of bladder cancer for future prevention and treatment.Methods The bladder cancer dataset GSE121711 was obtained from the Gene Expression Omnibus(GEO)database of NCBI.The weighted gene coexpression network analysis(WGCNA)was performed on GEO data to identify the gene modules highly associated with BLCA in the samples.The intersecting genes of differentially expressed genes(DEG)and genes in the module were extracted.The common genes were analyzed by Gene Ontology(GO)and Kyoto Encyclopedi-a of Genes and Genomes(KEGG),and the key genes with the highest degree were further screened through the Protein-protein interac-tion(PPI)network.The cluster analysis is carried out.Finally,the LASSO is used to establish the diagnostic model.The expression of hub genes in BLCA tissues and normal tissues was detected by using reverse transcription real-time quantitative polymerase chain reaction(RT-qPCR).Results WGCNA showed the most significant association between the black module and bladder cancer.There were 611 genes in the black module and intersected with DEG for 449 common genes.A diagnostic model consisting of RAC3,APOL4,FASN and CLASRP was constructed using LASSO,and analysis was conducted using receiver operating characteristic(ROC)curves at time points of 365 days(1 year),1095 days(3 years)and 1825 days(5 years).The Area Under Curve(AUC)of 365(1 year),1095(3 years)and 1825(5 years)were 80％,82％and 85％,respectively.The results were verified on the combined dataset of GSE101723 and GSE83586,which were found to be similar to those of bioinformatics.The relative expression levels of hub genes RAC3,APOL4,FASN and CLASRP mRNA in BLCA tissues were significantly higher than those in normal tissues(t=8.074,P＜0.0001;t=3.577,P＜0.001;t=12.241,P＜0.0001;t=8.846,P＜0.0001).Conclusion We constructed a BLCA diagnostic model and found that RAC3,APOL4,FASN and CLASRP were potential biomarkers that may provide new insights to improve the early diagnosis and treatment of blad-der cancer.
