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A pyroptosis-related gene signature that predicts immune infiltration and prognosis in colon cancer

BACKGROUND: Colon cancer (CC) is a highly heterogeneous malignancy associated with high morbidity and mortality. Pyroptosis is a type of programmed cell death characterized by an inflammatory response that can affect the tumor immune microenvironment and has potential prognostic and therapeutic valu...

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Autores principales: Wu, Mingjian, Hao, Shuai, Wang, Xiaoxiang, Su, Shuguang, Du, Siyuan, Zhou, Sitong, Yang, Ronghua, Du, Hanpeng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10369052/
https://www.ncbi.nlm.nih.gov/pubmed/37503314
http://dx.doi.org/10.3389/fonc.2023.1173181
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author Wu, Mingjian
Hao, Shuai
Wang, Xiaoxiang
Su, Shuguang
Du, Siyuan
Zhou, Sitong
Yang, Ronghua
Du, Hanpeng
author_facet Wu, Mingjian
Hao, Shuai
Wang, Xiaoxiang
Su, Shuguang
Du, Siyuan
Zhou, Sitong
Yang, Ronghua
Du, Hanpeng
author_sort Wu, Mingjian
collection PubMed
description BACKGROUND: Colon cancer (CC) is a highly heterogeneous malignancy associated with high morbidity and mortality. Pyroptosis is a type of programmed cell death characterized by an inflammatory response that can affect the tumor immune microenvironment and has potential prognostic and therapeutic value. The aim of this study was to evaluate the association between pyroptosis-related gene (PRG) expression and CC. METHODS: Based on the expression profiles of PRGs, we classified CC samples from The Cancer Gene Atlas and Gene Expression Omnibus databases into different clusters by unsupervised clustering analysis. The best prognostic signature was screened and established using least absolute shrinkage and selection operator (LASSO) and multivariate COX regression analyses. Subsequently, a nomogram was established based on multivariate COX regression analysis. Next, gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) were performed to explore the potential molecular mechanisms between the high- and low-risk groups and to explore the differences in clinicopathological characteristics, gene mutation characteristics, abundance of infiltrating immune cells, and immune microenvironment between the two groups. We also evaluated the association between common immune checkpoints and drug sensitivity using risk scores. The immunohistochemistry staining was utilized to confirm the expression of the selected genes in the prognostic model in CC. RESULTS: The 1163 CC samples were divided into two clusters (clusters A and B) based on the expression profiles of the 33 PRGs. Genes with prognostic value were screened from the DEGs between the two clusters, and an eight PRGs prognostic model was constructed. GSEA and GSVA of the high- and low-risk groups revealed that they were mainly enriched in inflammatory response-related pathways. Compared to those in the low-risk group, patients in the high-risk group had worse overall survival, an immunosuppressive microenvironment, and worse sensitivity to immunotherapy and drug treatment. CONCLUSION: Our findings provide a foundation for future research targeting pyroptosis and new insights into prognosis and immunotherapy from the perspective of pyroptosis in CC.
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spelling pubmed-103690522023-07-27 A pyroptosis-related gene signature that predicts immune infiltration and prognosis in colon cancer Wu, Mingjian Hao, Shuai Wang, Xiaoxiang Su, Shuguang Du, Siyuan Zhou, Sitong Yang, Ronghua Du, Hanpeng Front Oncol Oncology BACKGROUND: Colon cancer (CC) is a highly heterogeneous malignancy associated with high morbidity and mortality. Pyroptosis is a type of programmed cell death characterized by an inflammatory response that can affect the tumor immune microenvironment and has potential prognostic and therapeutic value. The aim of this study was to evaluate the association between pyroptosis-related gene (PRG) expression and CC. METHODS: Based on the expression profiles of PRGs, we classified CC samples from The Cancer Gene Atlas and Gene Expression Omnibus databases into different clusters by unsupervised clustering analysis. The best prognostic signature was screened and established using least absolute shrinkage and selection operator (LASSO) and multivariate COX regression analyses. Subsequently, a nomogram was established based on multivariate COX regression analysis. Next, gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) were performed to explore the potential molecular mechanisms between the high- and low-risk groups and to explore the differences in clinicopathological characteristics, gene mutation characteristics, abundance of infiltrating immune cells, and immune microenvironment between the two groups. We also evaluated the association between common immune checkpoints and drug sensitivity using risk scores. The immunohistochemistry staining was utilized to confirm the expression of the selected genes in the prognostic model in CC. RESULTS: The 1163 CC samples were divided into two clusters (clusters A and B) based on the expression profiles of the 33 PRGs. Genes with prognostic value were screened from the DEGs between the two clusters, and an eight PRGs prognostic model was constructed. GSEA and GSVA of the high- and low-risk groups revealed that they were mainly enriched in inflammatory response-related pathways. Compared to those in the low-risk group, patients in the high-risk group had worse overall survival, an immunosuppressive microenvironment, and worse sensitivity to immunotherapy and drug treatment. CONCLUSION: Our findings provide a foundation for future research targeting pyroptosis and new insights into prognosis and immunotherapy from the perspective of pyroptosis in CC. Frontiers Media S.A. 2023-07-12 /pmc/articles/PMC10369052/ /pubmed/37503314 http://dx.doi.org/10.3389/fonc.2023.1173181 Text en Copyright © 2023 Wu, Hao, Wang, Su, Du, Zhou, Yang and Du 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
Wu, Mingjian
Hao, Shuai
Wang, Xiaoxiang
Su, Shuguang
Du, Siyuan
Zhou, Sitong
Yang, Ronghua
Du, Hanpeng
A pyroptosis-related gene signature that predicts immune infiltration and prognosis in colon cancer
title A pyroptosis-related gene signature that predicts immune infiltration and prognosis in colon cancer
title_full A pyroptosis-related gene signature that predicts immune infiltration and prognosis in colon cancer
title_fullStr A pyroptosis-related gene signature that predicts immune infiltration and prognosis in colon cancer
title_full_unstemmed A pyroptosis-related gene signature that predicts immune infiltration and prognosis in colon cancer
title_short A pyroptosis-related gene signature that predicts immune infiltration and prognosis in colon cancer
title_sort pyroptosis-related gene signature that predicts immune infiltration and prognosis in colon cancer
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10369052/
https://www.ncbi.nlm.nih.gov/pubmed/37503314
http://dx.doi.org/10.3389/fonc.2023.1173181
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