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The Construction of a Prognostic Model Based on a Peptidyl Prolyl Cis–Trans Isomerase Gene Signature in Hepatocellular Carcinoma

Objective: The aim of the present study was to construct a prognostic model based on the peptidyl prolyl cis–trans isomerase gene signature and explore the prognostic value of this model in patients with hepatocellular carcinoma. Methods: The transcriptome and clinical data of hepatocellular carcino...

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Autores principales: Shi, Huadi, Zhong, Fulan, Yi, Xiaoqiong, Shi, Zhenyi, Ou, Feiyan, Zuo, Yufang, Xu, Zumin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8650315/
https://www.ncbi.nlm.nih.gov/pubmed/34887898
http://dx.doi.org/10.3389/fgene.2021.730141
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author Shi, Huadi
Zhong, Fulan
Yi, Xiaoqiong
Shi, Zhenyi
Ou, Feiyan
Zuo, Yufang
Xu, Zumin
author_facet Shi, Huadi
Zhong, Fulan
Yi, Xiaoqiong
Shi, Zhenyi
Ou, Feiyan
Zuo, Yufang
Xu, Zumin
author_sort Shi, Huadi
collection PubMed
description Objective: The aim of the present study was to construct a prognostic model based on the peptidyl prolyl cis–trans isomerase gene signature and explore the prognostic value of this model in patients with hepatocellular carcinoma. Methods: The transcriptome and clinical data of hepatocellular carcinoma patients were downloaded from The Cancer Genome Atlas and the International Cancer Genome Consortium database as the training set and validation set, respectively. Peptidyl prolyl cis–trans isomerase gene sets were obtained from the Molecular Signatures Database. The differential expression of peptidyl prolyl cis–trans isomerase genes was analyzed by R software. A prognostic model based on the peptidyl prolyl cis–trans isomerase signature was established by Cox, Lasso, and stepwise regression methods. Kaplan–Meier survival analysis was used to evaluate the prognostic value of the model and validate it with an independent external data. Finally, nomogram and calibration curves were developed in combination with clinical staging and risk score. Results: Differential gene expression analysis of hepatocellular carcinoma and adjacent tissues showed that there were 16 upregulated genes. A prognostic model of hepatocellular carcinoma was constructed based on three gene signatures by Cox, Lasso, and stepwise regression analysis. The Kaplan–Meier curve showed that hepatocellular carcinoma patients in high-risk score group had a worse prognosis (p < 0.05). The receiver operating characteristic curve revealed that the area under curve values of predicting the survival rate at 1, 2, 3, 4, and 5 years were 0.725, 0.680, 0.644, 0.630, and 0.639, respectively. In addition, the evaluation results of the model by the validation set were basically consistent with those of the training set. A nomogram incorporating clinical stage and risk score was established, and the calibration curve matched well with the diagonal. Conclusion: A prognostic model based on 3 peptidyl prolyl cis–trans isomerase gene signatures is expected to provide reference for prognostic risk stratification in patients with hepatocellular carcinoma.
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spelling pubmed-86503152021-12-08 The Construction of a Prognostic Model Based on a Peptidyl Prolyl Cis–Trans Isomerase Gene Signature in Hepatocellular Carcinoma Shi, Huadi Zhong, Fulan Yi, Xiaoqiong Shi, Zhenyi Ou, Feiyan Zuo, Yufang Xu, Zumin Front Genet Genetics Objective: The aim of the present study was to construct a prognostic model based on the peptidyl prolyl cis–trans isomerase gene signature and explore the prognostic value of this model in patients with hepatocellular carcinoma. Methods: The transcriptome and clinical data of hepatocellular carcinoma patients were downloaded from The Cancer Genome Atlas and the International Cancer Genome Consortium database as the training set and validation set, respectively. Peptidyl prolyl cis–trans isomerase gene sets were obtained from the Molecular Signatures Database. The differential expression of peptidyl prolyl cis–trans isomerase genes was analyzed by R software. A prognostic model based on the peptidyl prolyl cis–trans isomerase signature was established by Cox, Lasso, and stepwise regression methods. Kaplan–Meier survival analysis was used to evaluate the prognostic value of the model and validate it with an independent external data. Finally, nomogram and calibration curves were developed in combination with clinical staging and risk score. Results: Differential gene expression analysis of hepatocellular carcinoma and adjacent tissues showed that there were 16 upregulated genes. A prognostic model of hepatocellular carcinoma was constructed based on three gene signatures by Cox, Lasso, and stepwise regression analysis. The Kaplan–Meier curve showed that hepatocellular carcinoma patients in high-risk score group had a worse prognosis (p < 0.05). The receiver operating characteristic curve revealed that the area under curve values of predicting the survival rate at 1, 2, 3, 4, and 5 years were 0.725, 0.680, 0.644, 0.630, and 0.639, respectively. In addition, the evaluation results of the model by the validation set were basically consistent with those of the training set. A nomogram incorporating clinical stage and risk score was established, and the calibration curve matched well with the diagonal. Conclusion: A prognostic model based on 3 peptidyl prolyl cis–trans isomerase gene signatures is expected to provide reference for prognostic risk stratification in patients with hepatocellular carcinoma. Frontiers Media S.A. 2021-11-23 /pmc/articles/PMC8650315/ /pubmed/34887898 http://dx.doi.org/10.3389/fgene.2021.730141 Text en Copyright © 2021 Shi, Zhong, Yi, Shi, Ou, Zuo and Xu. 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
Shi, Huadi
Zhong, Fulan
Yi, Xiaoqiong
Shi, Zhenyi
Ou, Feiyan
Zuo, Yufang
Xu, Zumin
The Construction of a Prognostic Model Based on a Peptidyl Prolyl Cis–Trans Isomerase Gene Signature in Hepatocellular Carcinoma
title The Construction of a Prognostic Model Based on a Peptidyl Prolyl Cis–Trans Isomerase Gene Signature in Hepatocellular Carcinoma
title_full The Construction of a Prognostic Model Based on a Peptidyl Prolyl Cis–Trans Isomerase Gene Signature in Hepatocellular Carcinoma
title_fullStr The Construction of a Prognostic Model Based on a Peptidyl Prolyl Cis–Trans Isomerase Gene Signature in Hepatocellular Carcinoma
title_full_unstemmed The Construction of a Prognostic Model Based on a Peptidyl Prolyl Cis–Trans Isomerase Gene Signature in Hepatocellular Carcinoma
title_short The Construction of a Prognostic Model Based on a Peptidyl Prolyl Cis–Trans Isomerase Gene Signature in Hepatocellular Carcinoma
title_sort construction of a prognostic model based on a peptidyl prolyl cis–trans isomerase gene signature in hepatocellular carcinoma
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8650315/
https://www.ncbi.nlm.nih.gov/pubmed/34887898
http://dx.doi.org/10.3389/fgene.2021.730141
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