Title:
Identification and validation of core genes as promising diagnostic signature in hepatocellular carcinoma based on integrated bioinformatics approach

dc.contributor.authorPradeep Kumar
dc.contributor.authorAmit Kumar Singh
dc.contributor.authorKavindra Nath Tiwari
dc.contributor.authorSunil Kumar Mishra
dc.contributor.authorVishnu D. Rajput
dc.contributor.authorTatiana Minkina
dc.contributor.authorSimona Cavalu
dc.contributor.authorOvidiu Pop
dc.date.accessioned2026-02-07T10:57:30Z
dc.date.issued2022
dc.description.abstractThe primary objective of this investigation was to determine the hub genes of hepatocellular carcinoma (HCC) through an in silico approach. In the current context of the increased incidence of liver cancers, this approach could be a useful prognostic biomarker and HCC prevention target. This study aimed to examine hub genes for immune cell infiltration and their good prognostic characteristics for HCC research. Human genes selected from databases (Gene Cards and DisGeNET) were used to identify the HCC markers. Further, classification of the hub genes from communicating genes was performed using data derived from the targets' protein–protein interaction (PPI) platform. The expression as well as survival studies of all these selected genes were validated by utilizing databases such as GEPIA2, HPA, and immune cell infiltration. Based on the studies, five hub genes (TP53, ESR1, AKT1, CASP3, and JUN) were identified, which have been linked to HCC. They may be an important prognostic biomarker and preventative target of HCC. In silico analysis revealed that out of five hub genes, the TP53 and ESR1 hub genes potentially act as key targets for HCC prevention and treatment. © 2022, The Author(s).
dc.identifier.doi10.1038/s41598-022-22059-6
dc.identifier.issn20452322
dc.identifier.urihttps://doi.org/10.1038/s41598-022-22059-6
dc.identifier.urihttps://dl.bhu.ac.in/bhuir/handle/123456789/40301
dc.publisherNature Research
dc.titleIdentification and validation of core genes as promising diagnostic signature in hepatocellular carcinoma based on integrated bioinformatics approach
dc.typePublication
dspace.entity.typeArticle

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