Cargando…

A Seven-Gene Signature to Predict Prognosis of Patients With Hepatocellular Carcinoma

Purpose: Hepatocellular carcinoma (HCC) is one of the most prevalent malignant diseases worldwide and has a poor prognosis. Gene-based prognostic models have been reported to predict the overall survival of patients with HCC. Unfortunately, most of the genes used in earlier prognostic models lack pr...

Descripción completa

Detalles Bibliográficos
Autores principales: Wang, Junli, Zhang, Qi, Shi, Fukang, Yadav, Dipesh Kumar, Hong, Zhengtao, Wang, Jianing, Liang, Tingbo, Bai, Xueli
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8481951/
https://www.ncbi.nlm.nih.gov/pubmed/34603388
http://dx.doi.org/10.3389/fgene.2021.728476
_version_ 1784576797625548800
author Wang, Junli
Zhang, Qi
Shi, Fukang
Yadav, Dipesh Kumar
Hong, Zhengtao
Wang, Jianing
Liang, Tingbo
Bai, Xueli
author_facet Wang, Junli
Zhang, Qi
Shi, Fukang
Yadav, Dipesh Kumar
Hong, Zhengtao
Wang, Jianing
Liang, Tingbo
Bai, Xueli
author_sort Wang, Junli
collection PubMed
description Purpose: Hepatocellular carcinoma (HCC) is one of the most prevalent malignant diseases worldwide and has a poor prognosis. Gene-based prognostic models have been reported to predict the overall survival of patients with HCC. Unfortunately, most of the genes used in earlier prognostic models lack prospective validation and, thus, cannot be used in clinical practice. Methods: Candidate genes were selected from GEPIA (Gene Expression Profiling Interactive Analysis), and their associations with patients’ survival were confirmed by RT-PCR using cDNA tissue microarrays established from patients with HCC after radical resection. A multivariate Cox proportion model was used to calculate the coefficient of corresponding gene. The expression of seven genes of interest (MKI67, AR, PLG, DNASE1L3, PTTG1, PPP1R1A, and TTR) with two reference genes was defined to calculate a risk score which determined groups of different risks. Results: Our risk scoring efficiently classified patients (n = 129) with HCC into a low-, intermediate-, and high-risk group. The three groups showed meaningful distinction of 3-year overall survival rate, i.e., 88.9, 74.5, and 20.6% for the low-, intermediate-, and high-risk group, respectively. The prognostic prediction model of risk scores was subsequently verified using an independent prospective cohort (n = 77) and showed high accuracy. Conclusion: Our seven-gene signature model performed excellent long-term prediction power and provided crucially guiding therapy for patients who are not a candidate for surgery.
format Online
Article
Text
id pubmed-8481951
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-84819512021-10-01 A Seven-Gene Signature to Predict Prognosis of Patients With Hepatocellular Carcinoma Wang, Junli Zhang, Qi Shi, Fukang Yadav, Dipesh Kumar Hong, Zhengtao Wang, Jianing Liang, Tingbo Bai, Xueli Front Genet Genetics Purpose: Hepatocellular carcinoma (HCC) is one of the most prevalent malignant diseases worldwide and has a poor prognosis. Gene-based prognostic models have been reported to predict the overall survival of patients with HCC. Unfortunately, most of the genes used in earlier prognostic models lack prospective validation and, thus, cannot be used in clinical practice. Methods: Candidate genes were selected from GEPIA (Gene Expression Profiling Interactive Analysis), and their associations with patients’ survival were confirmed by RT-PCR using cDNA tissue microarrays established from patients with HCC after radical resection. A multivariate Cox proportion model was used to calculate the coefficient of corresponding gene. The expression of seven genes of interest (MKI67, AR, PLG, DNASE1L3, PTTG1, PPP1R1A, and TTR) with two reference genes was defined to calculate a risk score which determined groups of different risks. Results: Our risk scoring efficiently classified patients (n = 129) with HCC into a low-, intermediate-, and high-risk group. The three groups showed meaningful distinction of 3-year overall survival rate, i.e., 88.9, 74.5, and 20.6% for the low-, intermediate-, and high-risk group, respectively. The prognostic prediction model of risk scores was subsequently verified using an independent prospective cohort (n = 77) and showed high accuracy. Conclusion: Our seven-gene signature model performed excellent long-term prediction power and provided crucially guiding therapy for patients who are not a candidate for surgery. Frontiers Media S.A. 2021-09-16 /pmc/articles/PMC8481951/ /pubmed/34603388 http://dx.doi.org/10.3389/fgene.2021.728476 Text en Copyright © 2021 Wang, Zhang, Shi, Yadav, Hong, Wang, Liang and Bai. 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
Wang, Junli
Zhang, Qi
Shi, Fukang
Yadav, Dipesh Kumar
Hong, Zhengtao
Wang, Jianing
Liang, Tingbo
Bai, Xueli
A Seven-Gene Signature to Predict Prognosis of Patients With Hepatocellular Carcinoma
title A Seven-Gene Signature to Predict Prognosis of Patients With Hepatocellular Carcinoma
title_full A Seven-Gene Signature to Predict Prognosis of Patients With Hepatocellular Carcinoma
title_fullStr A Seven-Gene Signature to Predict Prognosis of Patients With Hepatocellular Carcinoma
title_full_unstemmed A Seven-Gene Signature to Predict Prognosis of Patients With Hepatocellular Carcinoma
title_short A Seven-Gene Signature to Predict Prognosis of Patients With Hepatocellular Carcinoma
title_sort seven-gene signature to predict prognosis of patients with hepatocellular carcinoma
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8481951/
https://www.ncbi.nlm.nih.gov/pubmed/34603388
http://dx.doi.org/10.3389/fgene.2021.728476
work_keys_str_mv AT wangjunli asevengenesignaturetopredictprognosisofpatientswithhepatocellularcarcinoma
AT zhangqi asevengenesignaturetopredictprognosisofpatientswithhepatocellularcarcinoma
AT shifukang asevengenesignaturetopredictprognosisofpatientswithhepatocellularcarcinoma
AT yadavdipeshkumar asevengenesignaturetopredictprognosisofpatientswithhepatocellularcarcinoma
AT hongzhengtao asevengenesignaturetopredictprognosisofpatientswithhepatocellularcarcinoma
AT wangjianing asevengenesignaturetopredictprognosisofpatientswithhepatocellularcarcinoma
AT liangtingbo asevengenesignaturetopredictprognosisofpatientswithhepatocellularcarcinoma
AT baixueli asevengenesignaturetopredictprognosisofpatientswithhepatocellularcarcinoma
AT wangjunli sevengenesignaturetopredictprognosisofpatientswithhepatocellularcarcinoma
AT zhangqi sevengenesignaturetopredictprognosisofpatientswithhepatocellularcarcinoma
AT shifukang sevengenesignaturetopredictprognosisofpatientswithhepatocellularcarcinoma
AT yadavdipeshkumar sevengenesignaturetopredictprognosisofpatientswithhepatocellularcarcinoma
AT hongzhengtao sevengenesignaturetopredictprognosisofpatientswithhepatocellularcarcinoma
AT wangjianing sevengenesignaturetopredictprognosisofpatientswithhepatocellularcarcinoma
AT liangtingbo sevengenesignaturetopredictprognosisofpatientswithhepatocellularcarcinoma
AT baixueli sevengenesignaturetopredictprognosisofpatientswithhepatocellularcarcinoma