• Key Genes in Bladder Cancer Metastasis: An In Silico Analysis
  • Fatemeh khara,1,* Shaqayeq naderlou,2 Javad Yaghmoorian Khojini,3 Arezu Heydari,4
    1. Department of Molecular Medicine, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, Iran
    2. Department of Molecular Medicine, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, Iran
    3. Department of Medical Biotechnology, School of Advance Science in Medicine, Tehran University of Medical Sciences, Tehran, Iran
    4. Department of Molecular Medicine, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, Iran


  • Introduction: Bladder cancer is one of the most common types of urinary tract cancers, originating from the cells lining the inner surface of the bladder. In this disease, cancerous cells grow uncontrollably and can invade surrounding tissues or even metastasize to other parts of the body. While the exact causes of bladder cancer remain elusive, several risk factors have been identified, including: smoking, exposure to chemicals, age, gender, family history, chronic bladder infections and bladder stones. Biomarkers can serve as biological indicators, assisting clinicians in the early and accurate detection of bladder cancer. These markers can be found in bodily fluids such as blood or urine, and changes in their levels may indicate the presence of cancerous cells. By utilizing biomarkers, less invasive and more precise diagnostic methods can be developed. In this study, we aim to identify the key genes that involved in bladder cancer metastasis.
  • Methods: In the current study, two microarray dataset (GSE37317, GSE31684) were downloaded from the Gene Expression Omnibus database (GEO). The fold change (FC) values of individual gene levels were calculated; differentially expressed genes (DEGs) with |FC| > 1 and P-value < 0.05 were considered to be significant. The Venn diagram was carried out for the overlapped part via Funrich software.
  • Results: A total of 3 overlapped upregulated genes and 7 downregulated genes were identified. Analysis showed that up-regulated genes involve in the translation regulator activity, cell adhesion molecule activity and catalytic activity. Down-regulated genes mainly associate with cytoskeletal protein binding, oxidoreductase activity and auxiliary transport protein activity.
  • Conclusion: These in silico predictions will provide useful information in selecting the target genes that are likely to have functional impact on the bladder cancer metastasis and may serve as potential diagnostic biomarkers in bladder cancer patients.
  • Keywords: bladder cancer, in silico, metastasis biomarkers