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A novel association of pyroptosis-related gene signature with the prognosis of hepatocellular carcinoma

BACKGROUND: Hepatocellular carcinoma (HCC) is one of the global leading lethal tumors. Pyroptosis has recently been defined as an inflammatory programmed cell death, which is closely linked to cancer progression. However, the significance of pyroptosis-related genes (PRGs) in the prognosis of HCC re...

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Autores principales: Li, Yuyao, Li, Yue, Zhang, Xuemei, Duan, Xiangjuan, Feng, Hai, Yu, Zhuo, Gao, Yueqiu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9578146/
https://www.ncbi.nlm.nih.gov/pubmed/36267972
http://dx.doi.org/10.3389/fonc.2022.986827
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author Li, Yuyao
Li, Yue
Zhang, Xuemei
Duan, Xiangjuan
Feng, Hai
Yu, Zhuo
Gao, Yueqiu
author_facet Li, Yuyao
Li, Yue
Zhang, Xuemei
Duan, Xiangjuan
Feng, Hai
Yu, Zhuo
Gao, Yueqiu
author_sort Li, Yuyao
collection PubMed
description BACKGROUND: Hepatocellular carcinoma (HCC) is one of the global leading lethal tumors. Pyroptosis has recently been defined as an inflammatory programmed cell death, which is closely linked to cancer progression. However, the significance of pyroptosis-related genes (PRGs) in the prognosis of HCC remains elusive. METHODS: RNA sequencing (RNA-seq) data of HCC cases and their corresponding clinical information were collected from the Cancer Genome Atlas (TCGA) database, and differential PRGs were explored. The prognostic PRGs were analyzed with univariate COX regression and the least absolute shrinkage and selection operator (LASSO) Cox regression analysis to build a prognostic model in the TCGA training cohort. The predictive model was further validated in the TCGA test cohort and ICGC validation cohort. Differential gene function and associated pathway analysis were performed by Gene ontology (GO) and Kyoto Encyclopedia of Gene and Genomes (KEGG). Single-sample gene set enrichment analysis (ssGSEA) was used to identify distinct immune cell infiltration. The mRNA and protein expression of prognostic PRGs was examined by quantitative RT-qPCR and immunohistochemistry. RESULTS: We identified 46 PRGs that were differentially expressed between normal and HCC tissues in a TCGA cohort, and HCC patients could be well categorized into two clusters associated with distinct survival rates based on expression levels of the PRGs. A three-PRG prognostic model comprising CHMP4A, HMGB1 and PLK1 was constructed in the training cohort, and HCC patients could be classified into the high- and low-risk subgroups based on the median risk score. High-risk patients exhibited shorter overall survival (OS) than low-risk ones, which was validated in the test cohort and ICGC validation cohort. The risk score of this model was confirmed as an independent prognostic factor to predict OS of HCC patients. GO, KEGG and ssGSEA demonstrated the differential immune cell infiltrations were associated with the risk scores. The higher expression of CHMP4A, HMGB1 and PLK1 were validated in HCC compared to normal in vivo and in vitro. CONCLUSION: The three-PRG signature (CHMP4A, HMGB1, and PLK1) could act as an independent factor to predict the prognosis of HCC patients, which would shed light upon a potent therapeutic strategy for HCC treatment.
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spelling pubmed-95781462022-10-19 A novel association of pyroptosis-related gene signature with the prognosis of hepatocellular carcinoma Li, Yuyao Li, Yue Zhang, Xuemei Duan, Xiangjuan Feng, Hai Yu, Zhuo Gao, Yueqiu Front Oncol Oncology BACKGROUND: Hepatocellular carcinoma (HCC) is one of the global leading lethal tumors. Pyroptosis has recently been defined as an inflammatory programmed cell death, which is closely linked to cancer progression. However, the significance of pyroptosis-related genes (PRGs) in the prognosis of HCC remains elusive. METHODS: RNA sequencing (RNA-seq) data of HCC cases and their corresponding clinical information were collected from the Cancer Genome Atlas (TCGA) database, and differential PRGs were explored. The prognostic PRGs were analyzed with univariate COX regression and the least absolute shrinkage and selection operator (LASSO) Cox regression analysis to build a prognostic model in the TCGA training cohort. The predictive model was further validated in the TCGA test cohort and ICGC validation cohort. Differential gene function and associated pathway analysis were performed by Gene ontology (GO) and Kyoto Encyclopedia of Gene and Genomes (KEGG). Single-sample gene set enrichment analysis (ssGSEA) was used to identify distinct immune cell infiltration. The mRNA and protein expression of prognostic PRGs was examined by quantitative RT-qPCR and immunohistochemistry. RESULTS: We identified 46 PRGs that were differentially expressed between normal and HCC tissues in a TCGA cohort, and HCC patients could be well categorized into two clusters associated with distinct survival rates based on expression levels of the PRGs. A three-PRG prognostic model comprising CHMP4A, HMGB1 and PLK1 was constructed in the training cohort, and HCC patients could be classified into the high- and low-risk subgroups based on the median risk score. High-risk patients exhibited shorter overall survival (OS) than low-risk ones, which was validated in the test cohort and ICGC validation cohort. The risk score of this model was confirmed as an independent prognostic factor to predict OS of HCC patients. GO, KEGG and ssGSEA demonstrated the differential immune cell infiltrations were associated with the risk scores. The higher expression of CHMP4A, HMGB1 and PLK1 were validated in HCC compared to normal in vivo and in vitro. CONCLUSION: The three-PRG signature (CHMP4A, HMGB1, and PLK1) could act as an independent factor to predict the prognosis of HCC patients, which would shed light upon a potent therapeutic strategy for HCC treatment. Frontiers Media S.A. 2022-10-04 /pmc/articles/PMC9578146/ /pubmed/36267972 http://dx.doi.org/10.3389/fonc.2022.986827 Text en Copyright © 2022 Li, Li, Zhang, Duan, Feng, Yu and Gao 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, Yuyao
Li, Yue
Zhang, Xuemei
Duan, Xiangjuan
Feng, Hai
Yu, Zhuo
Gao, Yueqiu
A novel association of pyroptosis-related gene signature with the prognosis of hepatocellular carcinoma
title A novel association of pyroptosis-related gene signature with the prognosis of hepatocellular carcinoma
title_full A novel association of pyroptosis-related gene signature with the prognosis of hepatocellular carcinoma
title_fullStr A novel association of pyroptosis-related gene signature with the prognosis of hepatocellular carcinoma
title_full_unstemmed A novel association of pyroptosis-related gene signature with the prognosis of hepatocellular carcinoma
title_short A novel association of pyroptosis-related gene signature with the prognosis of hepatocellular carcinoma
title_sort novel association of pyroptosis-related gene signature with the prognosis of hepatocellular carcinoma
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9578146/
https://www.ncbi.nlm.nih.gov/pubmed/36267972
http://dx.doi.org/10.3389/fonc.2022.986827
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