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

The 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 a...

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Autores principales: Kumar, Pradeep, Singh, Amit Kumar, Tiwari, Kavindra Nath, Mishra, Sunil Kumar, Rajput, Vishnu D., Minkina, Tatiana, Cavalu, Simona, Pop, Ovidiu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9646875/
https://www.ncbi.nlm.nih.gov/pubmed/36351994
http://dx.doi.org/10.1038/s41598-022-22059-6
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author Kumar, Pradeep
Singh, Amit Kumar
Tiwari, Kavindra Nath
Mishra, Sunil Kumar
Rajput, Vishnu D.
Minkina, Tatiana
Cavalu, Simona
Pop, Ovidiu
author_facet Kumar, Pradeep
Singh, Amit Kumar
Tiwari, Kavindra Nath
Mishra, Sunil Kumar
Rajput, Vishnu D.
Minkina, Tatiana
Cavalu, Simona
Pop, Ovidiu
author_sort Kumar, Pradeep
collection PubMed
description The 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.
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spelling pubmed-96468752022-11-15 Identification and validation of core genes as promising diagnostic signature in hepatocellular carcinoma based on integrated bioinformatics approach Kumar, Pradeep Singh, Amit Kumar Tiwari, Kavindra Nath Mishra, Sunil Kumar Rajput, Vishnu D. Minkina, Tatiana Cavalu, Simona Pop, Ovidiu Sci Rep Article The 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. Nature Publishing Group UK 2022-11-09 /pmc/articles/PMC9646875/ /pubmed/36351994 http://dx.doi.org/10.1038/s41598-022-22059-6 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Kumar, Pradeep
Singh, Amit Kumar
Tiwari, Kavindra Nath
Mishra, Sunil Kumar
Rajput, Vishnu D.
Minkina, Tatiana
Cavalu, Simona
Pop, Ovidiu
Identification and validation of core genes as promising diagnostic signature in hepatocellular carcinoma based on integrated bioinformatics approach
title Identification and validation of core genes as promising diagnostic signature in hepatocellular carcinoma based on integrated bioinformatics approach
title_full Identification and validation of core genes as promising diagnostic signature in hepatocellular carcinoma based on integrated bioinformatics approach
title_fullStr Identification and validation of core genes as promising diagnostic signature in hepatocellular carcinoma based on integrated bioinformatics approach
title_full_unstemmed Identification and validation of core genes as promising diagnostic signature in hepatocellular carcinoma based on integrated bioinformatics approach
title_short Identification and validation of core genes as promising diagnostic signature in hepatocellular carcinoma based on integrated bioinformatics approach
title_sort identification and validation of core genes as promising diagnostic signature in hepatocellular carcinoma based on integrated bioinformatics approach
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9646875/
https://www.ncbi.nlm.nih.gov/pubmed/36351994
http://dx.doi.org/10.1038/s41598-022-22059-6
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