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A Panel of E2F Target Gene Signature Predicting the Prognosis of Hepatocellular Carcinoma
Hepatocellular carcinoma is one of the most malignant tumors, and the therapeutic effects of traditional treatments are poor. It is urgent to explore and identify new biomarkers and therapeutic targets to develop novel treatments which are individualized and effective. Three hallmarks, including E2F...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9110819/ https://www.ncbi.nlm.nih.gov/pubmed/35591857 http://dx.doi.org/10.3389/fgene.2022.879299 |
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author | Hu, Wenmin Shi, Yongmei Han, Tongqin Liu, Caiyun Cao, Xipeng Shi, Guangjun Zhu, Wenjing |
author_facet | Hu, Wenmin Shi, Yongmei Han, Tongqin Liu, Caiyun Cao, Xipeng Shi, Guangjun Zhu, Wenjing |
author_sort | Hu, Wenmin |
collection | PubMed |
description | Hepatocellular carcinoma is one of the most malignant tumors, and the therapeutic effects of traditional treatments are poor. It is urgent to explore and identify new biomarkers and therapeutic targets to develop novel treatments which are individualized and effective. Three hallmarks, including E2F targets, G2M checkpoint and DNA repair, were collected by GSEA analysis. The panel of E2F-related gene signature consisted of five genes: HN1, KIF4A, CDCA3, CDCA8 and SSRP1. They had various mutation rates ranging from 0.8 to 5% in hepatocellular carcinoma, and patients with gene mutation had poorer prognosis. Among these genes, HN1 has the greatest mutation rate, and SSRP1 has the greatest impact on the model with a B (COX) value of 0.8842. Patients with higher expression of these genes had poorer prognosis. Kaplan-Meier curves in stratified survival analysis confirmed that patients with high risk scores had poor prognosis (p < 0.05). The results of univariate and multivariate COX survival analysis showed that risk score was closely related to the overall survival of patients with hepatocellular carcinoma. For clinical validation, we found that all the genes in the model were upregulated in hepatocellular carcinoma tissues compared to normal liver tissues, which was consistent with the previous results we obtained. Our study demonstrated that a panel of E2F target genes signature including five genes could predict the prognosis of hepatocellular carcinoma. This panel gene signature can facilitate the development of individualized and effective treatment for hepatocellular carcinoma. |
format | Online Article Text |
id | pubmed-9110819 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-91108192022-05-18 A Panel of E2F Target Gene Signature Predicting the Prognosis of Hepatocellular Carcinoma Hu, Wenmin Shi, Yongmei Han, Tongqin Liu, Caiyun Cao, Xipeng Shi, Guangjun Zhu, Wenjing Front Genet Genetics Hepatocellular carcinoma is one of the most malignant tumors, and the therapeutic effects of traditional treatments are poor. It is urgent to explore and identify new biomarkers and therapeutic targets to develop novel treatments which are individualized and effective. Three hallmarks, including E2F targets, G2M checkpoint and DNA repair, were collected by GSEA analysis. The panel of E2F-related gene signature consisted of five genes: HN1, KIF4A, CDCA3, CDCA8 and SSRP1. They had various mutation rates ranging from 0.8 to 5% in hepatocellular carcinoma, and patients with gene mutation had poorer prognosis. Among these genes, HN1 has the greatest mutation rate, and SSRP1 has the greatest impact on the model with a B (COX) value of 0.8842. Patients with higher expression of these genes had poorer prognosis. Kaplan-Meier curves in stratified survival analysis confirmed that patients with high risk scores had poor prognosis (p < 0.05). The results of univariate and multivariate COX survival analysis showed that risk score was closely related to the overall survival of patients with hepatocellular carcinoma. For clinical validation, we found that all the genes in the model were upregulated in hepatocellular carcinoma tissues compared to normal liver tissues, which was consistent with the previous results we obtained. Our study demonstrated that a panel of E2F target genes signature including five genes could predict the prognosis of hepatocellular carcinoma. This panel gene signature can facilitate the development of individualized and effective treatment for hepatocellular carcinoma. Frontiers Media S.A. 2022-05-03 /pmc/articles/PMC9110819/ /pubmed/35591857 http://dx.doi.org/10.3389/fgene.2022.879299 Text en Copyright © 2022 Hu, Shi, Han, Liu, Cao, Shi and Zhu. https://creativecommons.org/licenses/by/4.0/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) and the copyright owner(s) 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. |
spellingShingle | Genetics Hu, Wenmin Shi, Yongmei Han, Tongqin Liu, Caiyun Cao, Xipeng Shi, Guangjun Zhu, Wenjing A Panel of E2F Target Gene Signature Predicting the Prognosis of Hepatocellular Carcinoma |
title | A Panel of E2F Target Gene Signature Predicting the Prognosis of Hepatocellular Carcinoma |
title_full | A Panel of E2F Target Gene Signature Predicting the Prognosis of Hepatocellular Carcinoma |
title_fullStr | A Panel of E2F Target Gene Signature Predicting the Prognosis of Hepatocellular Carcinoma |
title_full_unstemmed | A Panel of E2F Target Gene Signature Predicting the Prognosis of Hepatocellular Carcinoma |
title_short | A Panel of E2F Target Gene Signature Predicting the Prognosis of Hepatocellular Carcinoma |
title_sort | panel of e2f target gene signature predicting the prognosis of hepatocellular carcinoma |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9110819/ https://www.ncbi.nlm.nih.gov/pubmed/35591857 http://dx.doi.org/10.3389/fgene.2022.879299 |
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