Identification and analysis of the molecular targets of statins in colorectal cancer

Ali Ahmadizad Firouzjaei1, Ali Mahmoudi2, Wael Almahmeed3

  • 1Student Research Committee, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran; Department of Medical Biotechnology, School of Advanced Technologies in Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

PubMed

Insights

Statins may help suppress colorectal cancer (CRC) by targeting specific genes. This bioinformatics study identified 35 overlapping genes between statin targets and CRC differentially expressed genes (DEGs), suggesting a potential therapeutic role for statins in CRC treatment.

Area of Science:

  • Oncology
  • Bioinformatics
  • Pharmacology

Background:

  • Colorectal cancer (CRC) is a major global health concern.
  • Statins, commonly used for cholesterol management, are being investigated for their potential role in CRC development and treatment.
  • Understanding the molecular interplay between statins and CRC is crucial for developing novel therapeutic strategies.

Purpose of the Study:

  • To investigate the relationship between statin targets and differentially expressed genes (DEGs) in colorectal cancer (CRC) using bioinformatics.
  • To identify potential molecular mechanisms by which statins may suppress CRC progression.
  • To discover key overlapping genes (hub genes) between statin targets and CRC DEGs.

Main Methods:

  • Utilized CRC gene expression datasets from the GEO database to identify DEGs.
  • Employed DGIdb and STITCH databases to identify statin gene targets.
  • Applied Venn diagrams to find overlapping genes between CRC DEGs and statin targets.
  • Conducted KEGG pathway and Gene Ontology (GO) enrichment analyses using Funrich and Enrichr databases.

Main Results:

  • Identified 1370 CRC DEGs and 345 statin targets, with 35 overlapping genes.
  • Enrichment analysis revealed statin targets in CRC are associated with receptor activity, metallopeptidase activity, signal transduction, and cell communication.
  • KEGG pathway analysis highlighted enrichment in IL-17, PPAR, and Toll-like receptor signaling pathways.
  • Identified hub genes including CCNB1, DNMT1, AURKB, RAC1, PPARGC1A, CDKN1A, CAV1, IL1B, and HSPD1.

Conclusions:

  • Bioinformatic analysis reveals a significant overlap between statin targets and DEGs in colorectal cancer.
  • Statin targets in CRC are implicated in key molecular functions and signaling pathways relevant to cancer progression.
  • The identified hub genes and enriched pathways suggest that statins possess therapeutic potential for CRC, warranting further investigation.