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Construction and validation of a prognostic model of pyroptosis related genes in hepatocellular carcinoma

Pyroptosis plays an important role in the occurrence and development of cancer. We are interested in determining the prognostic value of pyroptosis-related genes in hepatocellular carcinoma (HCC). In this study, we searched the original transcriptome data of The Cancer Genome Atlas (TCGA) and identi...

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Autores principales: Li, Guanqun, Zhang, Dongxin, Liang, Chaowei, Liang, Chaojie, Wu, Jixiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9633965/
https://www.ncbi.nlm.nih.gov/pubmed/36338707
http://dx.doi.org/10.3389/fonc.2022.1021775
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author Li, Guanqun
Zhang, Dongxin
Liang, Chaowei
Liang, Chaojie
Wu, Jixiang
author_facet Li, Guanqun
Zhang, Dongxin
Liang, Chaowei
Liang, Chaojie
Wu, Jixiang
author_sort Li, Guanqun
collection PubMed
description Pyroptosis plays an important role in the occurrence and development of cancer. We are interested in determining the prognostic value of pyroptosis-related genes in hepatocellular carcinoma (HCC). In this study, we searched the original transcriptome data of The Cancer Genome Atlas (TCGA) and identified the related expressed genes by co-expression analysis. Differentially expressed genes were identified by using univariate analysis, the least absolute shrinkage and selection operator (LASSO) and multivariate analysis to screen for genes related to prognosis of HCC. Ultimately, we established a prognostic model for five genes, namely GSDME, DHX9, TREM2, SQSTM1 and GLMN. Survival analysis showed that the overall survival rate of HCC patients with high risk score was significantly lower than that of HCC patients with low risk score, and this signal could be used as an independent prognostic indicator of HCC. Receiver operating characteristic curve analysis confirmed the accuracy of this prognostic signal, and was further verified in a Gene Expression Omnibus (GEO) dataset (GSE14520) and the International Cancer Genome Consortium (ICGC) databases. In addition, nomograms based on the five identified prognostic genes were established and verified internally in TCGA cohort. Additionally, we also analyzed the gene mutations of the model genes and the correlation between immune cells of the model genes. In summary, this study identified for the first time a 5-gene prognostic signature associated with pyroptosis, which can be used as a promising prognostic biomarker and provide some potentially useful therapeutic targets for HCC.
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spelling pubmed-96339652022-11-05 Construction and validation of a prognostic model of pyroptosis related genes in hepatocellular carcinoma Li, Guanqun Zhang, Dongxin Liang, Chaowei Liang, Chaojie Wu, Jixiang Front Oncol Oncology Pyroptosis plays an important role in the occurrence and development of cancer. We are interested in determining the prognostic value of pyroptosis-related genes in hepatocellular carcinoma (HCC). In this study, we searched the original transcriptome data of The Cancer Genome Atlas (TCGA) and identified the related expressed genes by co-expression analysis. Differentially expressed genes were identified by using univariate analysis, the least absolute shrinkage and selection operator (LASSO) and multivariate analysis to screen for genes related to prognosis of HCC. Ultimately, we established a prognostic model for five genes, namely GSDME, DHX9, TREM2, SQSTM1 and GLMN. Survival analysis showed that the overall survival rate of HCC patients with high risk score was significantly lower than that of HCC patients with low risk score, and this signal could be used as an independent prognostic indicator of HCC. Receiver operating characteristic curve analysis confirmed the accuracy of this prognostic signal, and was further verified in a Gene Expression Omnibus (GEO) dataset (GSE14520) and the International Cancer Genome Consortium (ICGC) databases. In addition, nomograms based on the five identified prognostic genes were established and verified internally in TCGA cohort. Additionally, we also analyzed the gene mutations of the model genes and the correlation between immune cells of the model genes. In summary, this study identified for the first time a 5-gene prognostic signature associated with pyroptosis, which can be used as a promising prognostic biomarker and provide some potentially useful therapeutic targets for HCC. Frontiers Media S.A. 2022-10-21 /pmc/articles/PMC9633965/ /pubmed/36338707 http://dx.doi.org/10.3389/fonc.2022.1021775 Text en Copyright © 2022 Li, Zhang, Liang, Liang and Wu 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 Oncology
Li, Guanqun
Zhang, Dongxin
Liang, Chaowei
Liang, Chaojie
Wu, Jixiang
Construction and validation of a prognostic model of pyroptosis related genes in hepatocellular carcinoma
title Construction and validation of a prognostic model of pyroptosis related genes in hepatocellular carcinoma
title_full Construction and validation of a prognostic model of pyroptosis related genes in hepatocellular carcinoma
title_fullStr Construction and validation of a prognostic model of pyroptosis related genes in hepatocellular carcinoma
title_full_unstemmed Construction and validation of a prognostic model of pyroptosis related genes in hepatocellular carcinoma
title_short Construction and validation of a prognostic model of pyroptosis related genes in hepatocellular carcinoma
title_sort construction and validation of a prognostic model of pyroptosis related genes in hepatocellular carcinoma
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9633965/
https://www.ncbi.nlm.nih.gov/pubmed/36338707
http://dx.doi.org/10.3389/fonc.2022.1021775
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