Abstract

Background Cancer stem cells (CSCs) have an key role in the beginning, progression and treatment of bladder cancer . In the current study, our target was to identify CSCS-related genes in bladder cancer. Methods Bladder cancer (BLCA) transcriptome data were acquired from The Cancer Genome Atlas (TCGA) database. WGCNA was used to screen genes connected with the mRNA expression-based stemness index (mRNAsi).Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were used to analyze the biological function of mRNAsi-related genes. Univariate Cox regression and LASSO Cox regression algorithms were applied to build a risk score model. Additionally, a ceRNA regulatory netwok based on key mRNAsi-related genes was established via TargetScan, miRDB, miRTarBas and miRcode database,and lncRNA SNHG12 was selected for further in vitro and invivo functional assays. Results Between BLCA and normal samples were identified 1560 differentially expressed genes (DEGs).845 DEGs were most significantly associated with mRNAsi according to WGCNA analysis, which were mainly enriched in GO terms and KEGG pathways related to cell proliferation . Univariate Cox regression and LASSO Cox regression algorithms screened 25 mRNAsi-related genes to construct the risk score model with the significant ability to estimate prognosis of BLCA patients . A ceRNA network, including 8 lncRNA, 11 miRNA and 9 mRNAsi-related mRNA, was constructed.We found that lncRNAs ADAMTS9-AS1 and SNHG12 were observably related to the survival of BLCA patients. To verify this finding, we selected SNHG12 for further study. RT-PCR experiments revealed that SNHG12 was high expression in both bladder cancer tissues and cells.SNHG12 promoted proliferation, invasion, migration, apoptosis and stemness of bladder cancer cells in vitro and tumour proliferation in vivo. Conclusion Our study identified 25 biomarkers associated with stemness indices in BLCA and established a ceRNA netwo