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Comprehensive genomic signature of pyroptosis-related genes and relevant characterization in hepatocellular carcinoma

BACKGROUND: Currently, the most predominant type of liver cancer is hepatocellular carcinoma (HCC), which is also the fourth leading cause of cancer-related death in the global population. Pyroptosis is an emerging form of cell death that affects the prognosis of cancer patients by modulating tumor...

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Autores principales: Wang, Sheng, Gao, Songsen, Shan, Liang, Qian, Xueyi, Luan, Jiajie, Lv, Xiongwen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9840857/
https://www.ncbi.nlm.nih.gov/pubmed/36650832
http://dx.doi.org/10.7717/peerj.14691
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author Wang, Sheng
Gao, Songsen
Shan, Liang
Qian, Xueyi
Luan, Jiajie
Lv, Xiongwen
author_facet Wang, Sheng
Gao, Songsen
Shan, Liang
Qian, Xueyi
Luan, Jiajie
Lv, Xiongwen
author_sort Wang, Sheng
collection PubMed
description BACKGROUND: Currently, the most predominant type of liver cancer is hepatocellular carcinoma (HCC), which is also the fourth leading cause of cancer-related death in the global population. Pyroptosis is an emerging form of cell death that affects the prognosis of cancer patients by modulating tumor cell migration, proliferation and invasion. However, the evaluation of pyroptosis in the prognosis of HCC is still insufficient. METHODS: A total of 365 HCC patients from the TCGA-LIHC cohort were classified into two distinct subtypes using consensus clustering of pyroptosis-related genes (PRGs). Following univariate Cox analysis of differentially expressed genes between subtypes, we established a prognostic model (PRGs-score, PRGS) by LASSO Cox analysis. We further tested the predictive power of the prognostic model in the ICGC (LIRI-JP) and GEO (GSE14520) cohorts. The tumor microenvironment (TME) was studied using the CIBERSORT. The enrichment scores for immune cells and immune functions in low- and high-PRGS groups were assessed using ssGSEA. The IMvigor210 cohort was used to investigate the immunotherapy efficacy. Furthermore, we validated the expression of prognostic genes in PRGS by RT-qPCR in vitro. RESULTS: The subtyping of HCC based on PRGs exhibited distinct clinical characteristics. We developed a prognostic model PRGS by differentially expressed genes between different subtypes. The results showed that PRGS could well forecast the survival of HCC patients in different cohorts and was associated with the immune microenvironment. Moreover, PRGS was considered to be an independent prognostic risk factor and superior to other pyroptosis-related signatures. Low-PRGS implied greater immune cell infiltration and better overall survival with immunotherapy. The results of RT-qPCR also showed that prognostic genes were significantly dysregulated in HCC. CONCLUSIONS: PRGS has promising application in forecasting the prognosis of HCC patients, and its relationship with the immune microenvironment provides a basis for the subsequent treatment and research of HCC.
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spelling pubmed-98408572023-01-16 Comprehensive genomic signature of pyroptosis-related genes and relevant characterization in hepatocellular carcinoma Wang, Sheng Gao, Songsen Shan, Liang Qian, Xueyi Luan, Jiajie Lv, Xiongwen PeerJ Bioinformatics BACKGROUND: Currently, the most predominant type of liver cancer is hepatocellular carcinoma (HCC), which is also the fourth leading cause of cancer-related death in the global population. Pyroptosis is an emerging form of cell death that affects the prognosis of cancer patients by modulating tumor cell migration, proliferation and invasion. However, the evaluation of pyroptosis in the prognosis of HCC is still insufficient. METHODS: A total of 365 HCC patients from the TCGA-LIHC cohort were classified into two distinct subtypes using consensus clustering of pyroptosis-related genes (PRGs). Following univariate Cox analysis of differentially expressed genes between subtypes, we established a prognostic model (PRGs-score, PRGS) by LASSO Cox analysis. We further tested the predictive power of the prognostic model in the ICGC (LIRI-JP) and GEO (GSE14520) cohorts. The tumor microenvironment (TME) was studied using the CIBERSORT. The enrichment scores for immune cells and immune functions in low- and high-PRGS groups were assessed using ssGSEA. The IMvigor210 cohort was used to investigate the immunotherapy efficacy. Furthermore, we validated the expression of prognostic genes in PRGS by RT-qPCR in vitro. RESULTS: The subtyping of HCC based on PRGs exhibited distinct clinical characteristics. We developed a prognostic model PRGS by differentially expressed genes between different subtypes. The results showed that PRGS could well forecast the survival of HCC patients in different cohorts and was associated with the immune microenvironment. Moreover, PRGS was considered to be an independent prognostic risk factor and superior to other pyroptosis-related signatures. Low-PRGS implied greater immune cell infiltration and better overall survival with immunotherapy. The results of RT-qPCR also showed that prognostic genes were significantly dysregulated in HCC. CONCLUSIONS: PRGS has promising application in forecasting the prognosis of HCC patients, and its relationship with the immune microenvironment provides a basis for the subsequent treatment and research of HCC. PeerJ Inc. 2023-01-12 /pmc/articles/PMC9840857/ /pubmed/36650832 http://dx.doi.org/10.7717/peerj.14691 Text en © 2023 Wang et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Bioinformatics
Wang, Sheng
Gao, Songsen
Shan, Liang
Qian, Xueyi
Luan, Jiajie
Lv, Xiongwen
Comprehensive genomic signature of pyroptosis-related genes and relevant characterization in hepatocellular carcinoma
title Comprehensive genomic signature of pyroptosis-related genes and relevant characterization in hepatocellular carcinoma
title_full Comprehensive genomic signature of pyroptosis-related genes and relevant characterization in hepatocellular carcinoma
title_fullStr Comprehensive genomic signature of pyroptosis-related genes and relevant characterization in hepatocellular carcinoma
title_full_unstemmed Comprehensive genomic signature of pyroptosis-related genes and relevant characterization in hepatocellular carcinoma
title_short Comprehensive genomic signature of pyroptosis-related genes and relevant characterization in hepatocellular carcinoma
title_sort comprehensive genomic signature of pyroptosis-related genes and relevant characterization in hepatocellular carcinoma
topic Bioinformatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9840857/
https://www.ncbi.nlm.nih.gov/pubmed/36650832
http://dx.doi.org/10.7717/peerj.14691
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