作者: Huier Zhu , Hui Chen , Jizhong Wang , Ling Zhou , Shaoyan Liu
DOI: 10.2147/OTT.S194568
关键词:
摘要: Purpose: Bladder cancer (BCa) is generally considered one of the most prevalent deadly diseases worldwide. Patients suffering from muscle-invasive bladder (MIBC) possess dismal prognoses, while those with non-muscle-invasive (NMIBC) have a favorable outcome after local treatment. However, some NMIBCs relapse and progress to MIBC, an unclarified mechanism. Hence, insight into genetic drivers BCa progression has tremendous potential benefits for precision therapeutics, risk stratification, molecular diagnosis. Methods: In this study, three cohorts profile datasets (GSE13507, GSE32584, GSE89) consisting NMIBC MIBC samples were integrated address differently expressed genes (DEGs). Subsequently, protein-protein interaction (PPI) network pathway enrichment analysis DGEs performed. Results: Six collagen members (COL1A1, COL1A2, COL5A2, COL6A1, COL6A2, COL6A3) up-regulated gathered in ECM-receptor signal identified by KEGG GSEA. Evidence derived Oncomine TCGA databases indicated that 6 promote are negatively associated patient prognosis. Moreover, taking COL1A1 as further research object, results showed was its knockdown significantly inhibited proliferation, migration, invasion 5637 T24 cells inhibiting epithelial-mesenchymal transition (EMT) process TGF-β signaling pathway. Conclusion: With bioinformatic cell experiments, we family high factors they can be used independent effective diagnostic prognostic biomarkers BCa.