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ORIGINAL RESEARCH article

Front. Bioinform.

Sec. Integrative Bioinformatics

Volume 5 - 2025 | doi: 10.3389/fbinf.2025.1567748

Identification and therapeutic investigation of biomarker genes underpinning hepatocellular carcinoma: An in-silico study utilising molecular docking and dynamics simulation

Provisionally accepted
Jishnu  GhoshJishnu Ghosh1Dr Abdullah  AlshahraniDr Abdullah Alshahrani2*Aritra  PalodhiAritra Palodhi3Debarghya  BhattacharyyaDebarghya Bhattacharyya3Subhadip  DasSubhadip Das3Sunil Kanti  MondalSunil Kanti Mondal1Abul  KalamAbul Kalam4*S Rehan  AhmadS Rehan Ahmad5Dr. Chittabrata  MalDr. Chittabrata Mal3*
  • 1University of Burdwan, Bardhaman, West Bengal, India
  • 2King Khalid University, Abha, Saudi Arabia
  • 3Maulana Abul Kalam Azad University of Technology, Kolkata, India
  • 4Bidhannagar College, Kolkata, West Bengal, India
  • 5Hiralal Mazumdar Memorial College for Women, Kolkata, West Bengal, India

The final, formatted version of the article will be published soon.

Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related mortality globally, and ranks fifth in terms of incidence. It primarily affects males and has a high prevalence in Asia. Risk factors include hepatitis B and C, liver cirrhosis, nonalcoholic fatty liver disease (NAFLD), and alcohol consumption. Late-stage diagnosis results in a poor survival rate of approximately 20%, underscoring the need for early detection methods to improve the survival rates. This study aimed to identify prognostic biomarkers for HCC through bioinformatic analysis of microarray datasets, providing insights into potential therapeutic targets.We analyzed five microarray datasets, comprising 402 HCC samples and 121 control samples.To identify relevant biological pathways, we conducted differential gene expression, Gene Ontology (GO), and KEGG pathway enrichment analyses. We identified hub genes and quantitatively assessed transcription factors and microRNAs targeting these genes.Additionally, molecular docking and dynamic simulations (100ns) were used to identify potential drug candidates capable of inhibiting the activity of differentially expressed hub genes.Our bioinformatic approach identified several promising HCC biomarkers. Among these, CDK1/CKS2 was identified as a key therapeutic target, with a regulatory role in HCC pathogenesis, suggesting its potential for further investigation. Digoxin (DB00390) has been highlighted as a potential repurposed drug candidate because of its favorable drug-likeness and stability, as confirmed by virtual screening, ADMET analysis, molecular docking study and dynamic simulations.This study enhances our understanding of HCC biology and offers new insights into drug interactions. It presents several promising biomarkers for the early diagnosis, prognosis, and therapy. Further investigation into CDK1/CKS2 as a therapeutic target and the role of the identified biomarkers could contribute to improved diagnostic and therapeutic strategies for HCC.

Keywords: Differential gene identification, PPI Network, biomarkers, Docking, molecular Biochemical and Biophysical Research Communications, 623, 111-119

Received: 28 Jan 2025; Accepted: 15 Aug 2025.

Copyright: © 2025 Ghosh, Alshahrani, Palodhi, Bhattacharyya, Das, Mondal, Kalam, Ahmad and Mal. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence:
Dr Abdullah Alshahrani, King Khalid University, Abha, 61431, Saudi Arabia
Abul Kalam, Bidhannagar College, Kolkata, 700064, West Bengal, India
Dr. Chittabrata Mal, Maulana Abul Kalam Azad University of Technology, Kolkata, India

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