• Exploration of Key Genes and Molecular Pathways in Cervical Cancer: Insights from Bioinformatics Analysis
  • Ameneh Jafari,1 Ehsan Zafari,2 Abbas Ghasemzadeh,3 Saman Asadi,4 Masumeh Farahani,5,*
    1. Proteomics Research Center, Shahid Beheshti University of Medical Sciences
    2. Department of Virology, Faculty of Medical Sciences, Tarbiat Modares University
    3. Department of Molecular Biology, Pasteur Institute of Iran,
    4. Veterinary faculty, Islamic Azad University science and research branch
    5. Skin Research Center, Shahid Beheshti University of Medical Sciences


  • Introduction: Cervical cancer (CC) ranks as the fourth most prevalent cancer among women worldwide. The urgent need to identify novel biomarkers and unravel underlying molecular mechanisms has prompted this study. Our objectives were to identify key genes and pathways influencing the diagnosis of CC patients, and to shed light on new molecular mechanisms associated with cervical cancer through bioinformatics analysis.
  • Methods: Proteomics data from published sources were utilized to gather CC-related information. We constructed a protein-protein interaction (PPI) network involving differentially expressed proteins (DEPs) using STRING and Cytoscape technology. The Cytoscape plug-in CytoHubba was employed to identify hub genes.
  • Results: Network analysis revealed the top seven hub genes: FGA, ITIH2, APO B, A2M, KNG1, VTN, and FN1, which exhibited overexpression in cervical carcinoma cells compared to normal cervical cells. These identified genes may serve as crucial diagnostic biomarkers and potential targets for CC prevention.
  • Conclusion: Through bioinformatics analysis, this study successfully screened key genes and pathways closely linked to cervical cancer, thereby deepening our understanding of its molecular mechanisms underlying initiation and progression. These findings hold promise in identifying potential therapeutic targets for cervical cancer.
  • Keywords: Cervical cancer, differential expression proteins (DEPs), biomarker, bioinformatics