A novel focal adhesion-related risk model predicts prognosis of bladder cancer —— a bioinformatic study based on TCGA and GEO database

作者：Jiyuan Hu, Linhui Wang, Luanfeng Li, Yutao Wang, Jianbin Bi · 发表于：BMC Cancer · 年份：2022 · DOI：10.1186/s12885-022-10264-5 · 被引用次数：16 · 研究领域：Ferroptosis and cancer prognosis、Bladder and Urothelial Cancer Treatments、Epigenetics and DNA Methylation

BACKGROUND: Bladder cancer (BLCA) is the ninth most common cancer globally, as well as the fourth most common cancer in men, with an incidence of 7%. However, few effective prognostic biomarkers or models of BLCA are available at present. METHODS: The prognostic genes of BLCA were screened from one cohort of The Cancer Genome Atlas (TCGA) database through univariate Cox regression analysis and functionally annotated by Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. The intersecting genes of the BLCA gene set and focal adhesion-related gene were obtained and subjected to the least absolute shrinkage and selection operator regression (LASSO) to construct a prognostic model. Gene set enrichment analysis (GSEA) of high- and low-risk patients was performed to explore further the biological process related to focal adhesion genes. Univariate and multivariate Cox analysis, receiver operating characteristic (ROC) curve analysis, and Kaplan-Meier survival analysis (KM) were used to evaluate the prognostic model. DNA methylation analysis was presented to explore the relationship between prognosis and gene methylation. Furthermore, immune cell infiltration was assessed by CIBERSORT, ESTIMATE, and TIMER. The model was verified in an external GSE32894 cohort of the Gene Expression Omnibus (GEO) database, and the Prognoscan database presented further validation of genes. The HPA database validated the related protein level, and functional experiments verified s...