Identifying novel biomarkers in hepatocellular carcinoma by weighted gene co‐expression network analysis

Background: A better comprehension of the genetic basis of hepatocellular carcinoma (HCC) isrequired to forecast a patient's prognosis and create new targeted gene therapies. The goal of thisstudy is to find critical genes linked to HCC.Materials and Methods: WGCNA and DEG analysis were utilized to study the relationshipbetween gene sets and clinical characteristics, as well as the interactions underlying the coexpressionmodules. The Kyoto Encyclopedia of Genes and Genomes (KEGG) and GeneOntology (GO) were then utilized to investigate the biological functions of the discovereddysregulated genes. Finally, to validate the study's findings, an online database analysis wasperformed using XenaBrowser and GEIPA to analyses hub-gene expression and determines itsdiagnostic significance.Results: The pink module was found as the most significant module in the co-expressionnetwork linked with the progression of HCC (r = ۰.۸۴, p-Value = ۲e-۰۷) in the GSE۱۱۴۵۶۴dataset. This module was linked to the positive regulation of the non-canonical Wnt signalingpathway, the regulation of lipolysis in adipocytes, and the positive regulation of the Wntsignaling pathway, planar cell polarity pathway. According to the Venn diagram constructedbetween the pink module and DEGs, the top seven genes, including MND۱, FCN۲, CLEC۴G,CLEC۴M, PTH۱R, VIPR۱, and AKR۱B۱۰, were also associated with HCC patient progression.Among these shared hub-genes, MND۱ was found as a novel biomarker and validated by thementioned databases.Conclusion: The current study identified important modules and MND۱ as a hub-gene related toHCC, which could provide references to understand the genesis and could be considered as anovel candidate for HCC target-therapy

کلیدواژه ها:

hepatocellular carcinoma ، Molecular Pathogenicity ، Transcriptome Analysis