Purpose: Bladder cancer (BCa) is generally considered one of the most prevalent deadly diseases worldwide. Patients suffering from muscle-invasive bladder cancer (MIBC) possess dismal prognoses, while those with non-muscle-invasive bladder cancer (NMIBC) generally have a favorable outcome after local treatment. However, some NMIBCs relapse and progress to MIBC, with an unclarified mechanism. Hence, insight into the genetic drivers of BCa progression has tremendous potential benefits for precision therapeutics, risk stratification, and molecular diagnosis.
Methods: In this study, three cohorts profile datasets (GSE13507, GSE32584, and GSE89) consisting of NMIBC and MIBC samples were integrated to address the differently expressed genes (DEGs). Subsequently, the protein-protein interaction (PPI) network and pathway enrichment analysis of DGEs were performed.
Results: Six collagen members (COL1A1, COL1A2, COL5A2, COL6A1, COL6A2, and COL6A3) were up-regulated and gathered in the ECM-receptor interaction signal pathway identified by KEGG pathway analysis and GSEA. Evidence derived from the Oncomine and TCGA databases indicated that the 6 collagen genes promote the progression of BCa and are negatively associated with patient prognosis. Moreover, taking COL1A1 as a further research object, the results showed that COL1A1 was up-regulated in MIBC and its knockdown significantly inhibited the proliferation, migration, and invasion of 5637 and T24 cells by inhibiting epithelial-mesenchymal transition (EMT) process and the TGF-β signaling pathway.
Conclusion: With integrated bioinformatic analysis and cell experiments, we showed that 6 collagen family members are high progression risk factors and that they can be used as independent effective diagnostic and prognostic biomarkers for BCa.
Keywords: genomic analysis, bladder cancer, invasion, diagnostic marker, prognostic markers