Single nucleotide polymorphism mutation related genes in bladder cancer for the treatment of patients: a study based on the TCGA database

Abstract

Bladder cancer (BLCA) is a common malignancy and has a poor prognosis. Single nucleotide polymorphisms (SNPs) in genes are closely associated with the tumorigenesis and tumor development and yet are not well illustrated in BLCA. In this study, we downloaded SNP‐related data and transcriptome profiling of BLCA from the Cancer Genome Atlas (TCGA) database and identified high frequency mutation genes using Maftools package and differentially expressed genes (DEGs) between BLCA and normal bladder tissues by the Limma package. Then, the overlapping genes between high frequency mutation genes and DEGs were obtained by the Venn diagram tool. These overlapping genes were analyzed by Gene Ontology (GO) and Kyoto Gene and Genome Encyclopedia (KEGG) pathway enrichment analysis, protein–protein interaction (PPI) network construction, survival analysis and drug–gene interaction analysis. As a result, 33 overlapping mutant genes were obtained, which were enriched in multiple KEGG pathways (e.g. cellular senescence) and GO items (e.g. muscle organ development, costamere and actin binding). A significant gene module was constructed by PPI network analysis and included 12 hub genes (SYNE1, DMD, ATM, EP300, ANK2, LAMA2, FAT1, SRRM2, MACF1, TSC1, VCAN and RXRA). Moreover, ATM, RXRA, TSC1, DMD, EP300, LAMA2 and VCAN were drug targets. These findings provide important bioinformatics and theoretical basis for understanding the pathogenesis of BLCA and exploring the detailed mechanisms of mutant genes in the disease.

Keywords

• tcga
• go
• kegg
• ppi
• bladder cancer
• single nucleotide polymorphisms