Identification of Differentially Expressed Genes Associated with the Prognosis and Diagnosis of Hepatocellular Carcinoma by Integrated Bioinformatics Analysis

Author:

Kakar Mohib Ullah12,Mehboob Muhammad Zubair34,Akram Muhammad5,Shah Muddaser67,Shakir Yasmeen8,Ijaz Hafza Wajeeha3,Aziz Ubair9,Ullah Zahid10,Ahmad Sajjad11,Ali Sikandar12,Yin Yongxiang13ORCID

Affiliation:

1. Beijing Key Laboratory for Separation and Analysis in Biomedicine and Pharmaceutical, School of life Sciences, Beijing Institute of Technology (BIT), Beijing 100081, China

2. Faculty of Marine Sciences, Lasbela University of Agriculture, Water and Marine Sciences (LUAWMS), Uthal, Balochistan, Pakistan

3. CAS Centre for Excellence in Biotic Interaction, College of Life Sciences, University of Chinese Academy of Science, Beijing 100049, China

4. Department of Biochemistry and Biotechnology, University of Gujrat, Gujrat 50700, Pakistan

5. School of Science, Department of Life sciences, University of Management and Technology, Johar Town, Lahore 54770, Pakistan

6. Department of Botany, Abdul Wali Khan University, Mardan 23200, Pakistan

7. Natural and Medical Sciences Research Center, University of Nizwa, Birkat Al-Mauz, P.O. Box 33, Nizwa 616, Oman

8. Department of Biochemistry, Hazara University, Mansehra, Pakistan

9. Research Centre of Molecular Simulation, National University of Science and Technology, Islamabad, Pakistan

10. School of Environmental Studies, China University of Geosciences, Wuhan 430074, China

11. Faculty of Veterinary and Animal Sciences, Lasbela University of Agriculture, Water and Marine Sciences, LUAWMS, Uthal, 90150 Balochistan, Pakistan

12. Dow Institute for Advanced Biological and Animal Research, Dow University of Health Sciences, Ojha Campus, Karachi, Pakistan

13. Department of Pathology, Wuxi Maternity and Child Health Hospital Affiliated to Nanjing Medical University, Wuxi, China

Abstract

Objective. The goal of this study was to understand the possible core genes associated with hepatocellular carcinoma (HCC) pathogenesis and prognosis. Methods. GEO contains datasets of gene expression, miRNA, and methylation patterns of diseased and healthy/control patients. The GSE62232 dataset was selected by employing the server Gene Expression Omnibus. A total of 91 samples were collected, including 81 HCC and 10 healthy samples as control. GSE62232 was analysed through GEO2R, and Functional Enrichment Analysis was performed to extract rational information from a set of DEGs. The Protein-Protein Relationship Networking search method has been used for extracting the interacting genes. MCC method was used to calculate the top 10 genes according to their importance. Hub genes in the network were analysed using GEPIA to estimate the effect of their differential expression on cancer progression. Results. We identified the top 10 hub genes through CytoHubba plugin. These included BUB1, BUB1B, CCNB1, CCNA2, CCNB2, CDC20, CDK1 and MAD2L1, NCAPG, and NDC80. NCAPG and NDC80 reported for the first time in this study while the remaining from a recently reported literature. The pathogenesis of HCC may be directly linked with the aforementioned genes. In this analysis, we found critical genes for HCC that showed recommendations for future prognostic and predictive biomarkers studies that could promote selective molecular therapy for HCC.

Funder

High-Level Talent Training Project of Wuxi Taihu Talent Plan

Publisher

Hindawi Limited

Subject

General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Medicine

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