A Bioinformatics-Based Approach to Discover Novel Biomarkers in Hepatocellular Carcinoma

Amir  Shourideh; Reza  Maddah; Bahareh  Shateri Amiri; Zarrin  Basharat; Marzieh  Shadpirouz

doi:10.18502/ijph.v53i6.15907

Amir Shourideh Faculty of Pharmacy, Eastern Mediterranean University, Famagusta, Cyprus
Reza Maddah Department of Bioprocess Engineering, Institute of Industrial and Environmental Biotechnology, National Institute of Genetic En-gineering and Biotechnology, Tehran, Iran
Bahareh Shateri Amiri Department of Internal Medicine, School of Medicine Hazrat-e Rasool General Hospital Iran University of Medical Sciences, Teh-ran, Iran
Zarrin Basharat Alpha Genomics Private Limited, Islamabad 45710, Pakistan
Marzieh Shadpirouz Department of Applied Mathematics, Faculty of Mathematical Sciences, Shahrood University of Technology, Semnan, Iran

DOI: https://doi.org/10.18502/ijph.v53i6.15907

Keywords: Hepatocellular carcinoma; Genes; Molecular pathway; Systems biology

Abstract

Background: Liver hepatocellular carcinoma (LIHC) is a common cancer with a poor prognosis and high recurrence rate. We aimed to identify potential biomarkers for LIHC by investigating the involvement of hub genes, microRNAs (miRNAs), transcription factors (TFs), and protein kinases (PKs) in its occurrence.

Methods: we conducted a bioinformatics analysis using microarray datasets, the TCGA-LIHC dataset, and text mining to identify differentially expressed genes (DEGs) associated with LIHC. They then performed functional enrichment analysis and gene-disease association analysis. The protein-protein interaction network of the genes was established, and hub genes were identified. The expression levels and survival analysis of these hub genes were evaluated, and their association with miRNAs, TFs, and PKs was assessed.

Results: The analysis identified 122 common genes involved in LIHC pathogenesis. Ten hub genes were filtered out, including CDK1, CCNB1, CCNB2, CCNA2, ASPM, NCAPG, BIRC5, RRM2, KIF20A, and CENPF. The expression level of all hub genes was confirmed, and high expression levels of all hub genes were correlated with poor overall survival of LIHC patients.

Conclusion: Identifying potential biomarkers for LIHC can aid in the design of targeted treatments and improve the survival of LIHC patients. The findings of this study provide a basis for further research in the field of LIHC and contribute to the understanding of its molecular pathogenesis.