Identification of Selected Genes Associated With the Prediction of Prognosis in Bladder Cancer

Bladder cancer (BC) is one of the most common urological malignancies, ranking as the eleventh most common cause of cancer-related deaths worldwide. The lack of specific and sensitive prognostic biomarkers presents a significant challenge in the early diagnosis and treatment of BC.

This study utilizes the Gene Expression Omnibus (GEO) dataset GSE13507 and the Cancer Genome Atlas (TCGA) database to screen differentially expressed genes related to BC. By using Weighted Gene Co-expression Network Analysis (WGCNA), two modules associated with BC were investigated in GSE13507 and TCGA. Hub genes were identified through Protein- Protein Interaction (PPI) network analysis, and their functions were validated through multiple approaches, including Gene Expression Profiling Interactive Analysis (GEPIA), Western Blotting (WB) assay, Human Protein Atlas (HPA), Oncomine analysis, and quantitative Real-Time PCR (qRT-PCR) analysis. Additionally, miRNAs associated with hub gene expression were identified using various databases to predict the progression and prognosis of BC.

WGCNA and a differential gene expression analysis identified 171 common genes as target genes. Ten genes (MYH11, ACTA2, TPM2, ACTG2, CALD1, MYL9, TPM1, MYLK, SORBS1, and LMOD1) were identified using the PPI tool. The CALD1 and MYLK genes showed a significant prognostic value for overall survival and disease-free survival in patients with BC. CALD1 and MYLK expression levels were significantly lower in BC tissues than in normal tissues. Furthermore, miR-155 showed a significant positive correlation with MYLK.

This study established MYLK as a direct target gene of miR-155, functioning as an actionable survival-related gene correlated with BC development.