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Differential Gene Expression Analysis and Molecular Docking to Identify Potential Biomarkers of Colorectal Cancer

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Author Affiliations

  • 1Department of Bioinformatics, Stella Maris College, Chennai, Tamilnadu, India
  • 2Department of Bioinformatics, Stella Maris College, Chennai, Tamilnadu, India

Res. J. Computer & IT Sci., Volume 13, Issue (1), Pages 1-11, June,20 (2025)

Abstract

Colorectal cancer is one of the leading cancer types worldwide in terms of incidence and mortality. This type of cancer originates from the large intestine, near the gastrointestinal tract which includes the colon and rectum. Colon familial colorectal cancer refers to a situation where the first degree relatives have a higher chance of developing the disease with a high mortality rate. Considering this, the current study integrated a Bioinformatics approach to elucidate the gene expression patterns and molecular interactions associated with colorectal cancer (CRC) progression. Gene expression profiling revealed differential expression of key genes (CXCL1, CXCL2, CXCL3, COL1A1, COL1A2) across different stages of colon adenocarcinoma. Notably, early-stage samples exhibited elevated expression of CXCL genes, while MMP1 and MMP3 were upregulated in advanced stages. Gene Ontology analysis highlighted enrichment in processes related to extracellular matrix organization and proteolysis. Prognostic biomarkers, neurotransmitters, neuropeptides, and intracellular signaling pathways were identified for the CRC survival prediction. Protein-protein interaction network analysis identified key modules, unveiling protein clusters for further investigation. Molecular docking analysis targeting CRC-associated proteins CXCL2 and CXCL3 identified potential therapeutic compounds with high affinity, including Isorhamnetin, Kaempferol, Jaranol, Curcumin, EGCG, Hesperidin, Resveratrol, Liquiritin, and Baicalin. This comprehensive analysis provides valuable insights into the molecular landscape of CRC, identifying potential therapeutic targets and biomarkers for precision medicine strategies in CRC management.

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