• Utilizing Bioinformatics Databases to Discover Key Genes Associated with Colorectal Cancer Development
  • Johann Ebadfardzadeh,1 Mandana Kazemi,2 Ali Aghazadeh,3 Monireh Rezaei,4 Milad Shirvaliloo,5 Roghayeh Sheervalilou,6,*
    1. Department of Biology, Faculty of Sciences, University of Guilan, Rasht, Iran
    2. Department of Biology, Faculty of Basic Sciences, Shahrekord, Iran
    3. Azad Tonekabon University of Medical Sciences, Tonekabon, Iran
    4. Department of Medical Genetics, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran
    5. Infectious and Tropical Diseases Research Center, Tabriz University of Medical Sciences, Tabriz, Iran
    6. Pharmacology Research Center, Zahedan University of Medical Sciences, Zahedan, Iran


  • Introduction: Colorectal cancer (CRC) is the third most common cause of cancer-related deaths worldwide, presenting a significant global health challenge that necessitates advancements in both diagnostics and treatment to enhance patient survival rates. Recently, the analysis of microarray data has emerged as a promising and effective approach for classifying cancers and evaluating prognosis. This study focuses on integrating microarray data analysis to identify genes associated with CRC by examining gene expression patterns from four microarray datasets found in the Gene Expression Omnibus (GEO).
  • Methods: We collected four gene expression datasets: GSE37182, GSE25070, GSE10950, and GSE113513, along with differentially expressed genes (DEGs). The analysis was conducted using R software, the DAVID database, protein-protein interaction (PPI) networks, the Cytoscape application, and receiver operating characteristic (ROC) curves.
  • Results: From the four datasets analyzed, we identified 10 hub genes: SLC26A3, CLCA1, GUCA2A, MS4A12, CLCA4, GUCA2B, KRT20, AQP8, MAOA, and ADH1A. These DEGs were found to be significantly involved in multiple pathways, such as nitrogen metabolism, mineral absorption, pancreatic secretions, and tyrosine metabolism, according to the Kyoto Encyclopedia of Genes and Genomes (KEGG) database.
  • Conclusion: Our bioinformatics analysis indicates that the DEGs highlighted in this study may serve as crucial markers in understanding the molecular mechanisms underlying CRC progression. The insights gained could aid researchers in developing innovative strategies for predicting CRC, facilitating early diagnosis, and improving treatment options for patients suffering from this disease.
  • Keywords: Colorectal cancer (CRC), Differentially expressed genes (DEGs), Hub genes