• Screening The Hub Genes and Their Functional Significance in Liver Cancer: Evidenced by Bioinformatic Tools
  • Mehdi Hashemi,1,* Roya Sinaei,2 Maryam Tahmasebi-Birgani,3
    1. Department of Medical Genetics, School of Medicine, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran.
    2. Department of Genetics, Faculty of Advanced Science and Technology, Tehran Medical Sciences, Islamic Azad University, Tehran, Iran.
    3. Department of Medical Genetics, School of Medicine, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran.


  • Introduction: Liver hepatocellular carcinoma (LIHC), the most common type of liver cancer, originates from hepatocytes and represents over 80% of liver cancer cases. It is projected to be the sixth most frequently diagnosed cancer and the fourth leading cause of cancer-related deaths globally. Unfortunately, LIHC is often detected at an advanced stage, where effective treatments to enhance survival rates are nearly nonexistent. Thus, identifying diagnostic biomarkers is crucial for early detection and personalized treatment options for LIHC. This study aims to discover new diagnostic and prognostic biomarkers in LIHC patients.
  • Methods: mRNA microarray datasets GSE84402, GSE101685, and GSE60502 were sourced from the Gene Expression Omnibus (GEO) and analyzed through bioinformatics to pinpoint hub genes involved in the development of LIHC. Differentially expressed genes (DEGs) were evaluated using the GEO2R tool. Gene ontology (GO) and KEGG analyses were conducted using the Enrichr platform. The STRING database and Cytoscape software facilitated the construction of a protein-protein interaction (PPI) network, allowing for the identification of key modules and hub genes. To confirm the expression variations of hub genes in liver hepatocellular carcinoma compared to normal tissues, Gene Expression Profiling Interactive Analysis (GEPIA) was employed, and the overall survival (OS) related to hub genes was analyzed using the Kaplan-Meier plotter.
  • Results: A total of 115 overlapping differentially expressed genes (DEGs) were identified, consisting of 86 upregulated and 29 downregulated genes. An integrated analysis highlighted five key hub genes: PRC, MELK, TTK, MKI67, and FANCI. These DEGs were primarily linked to processes such as complement and coagulation cascades, mineral absorption, glycolysis/gluconeogenesis, fatty acid degradation, the cell cycle, and the p53 signaling pathway. The protein-protein interaction (PPI) network comprised 112 nodes and 385 edges. Survival analysis indicated a significant association between these hub genes and the overall survival of LIHC patients.
  • Conclusion: This study successfully identified several key hub genes associated with liver hepatocellular carcinoma, revealing important insights into the disease's molecular landscape. The bioinformatics analysis provided valuable insights into the molecular mechanisms underlying this cancer type. These findings may facilitate the development of targeted therapies and improve patient outcomes. Overall, the research contributes to a better understanding of liver cancer and its underlying biological mechanisms.
  • Keywords: Liver hepatocellular carcinoma (LIHC), Hub Genes, GEO, In Silico