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Effect of Pyroptosis-Related Genes on the Prognosis of Breast Cancer

BACKGROUNDS: Pyroptosis, a newly pattern of specific programmed cell death, has been reported to participate in several cancers. However, the value of pyroptosis in breast cancer (BRCA) is still not clear. METHODS: Herein, we analyzed the data of BRCA from both The Cancer Genome Atlas (TCGA) and GSE...

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Autores principales: Zhou, Ying, Zheng, Jianfeng, Bai, Mengru, Gao, Yuzhen, Lin, Nengming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9357945/
https://www.ncbi.nlm.nih.gov/pubmed/35957895
http://dx.doi.org/10.3389/fonc.2022.948169
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author Zhou, Ying
Zheng, Jianfeng
Bai, Mengru
Gao, Yuzhen
Lin, Nengming
author_facet Zhou, Ying
Zheng, Jianfeng
Bai, Mengru
Gao, Yuzhen
Lin, Nengming
author_sort Zhou, Ying
collection PubMed
description BACKGROUNDS: Pyroptosis, a newly pattern of specific programmed cell death, has been reported to participate in several cancers. However, the value of pyroptosis in breast cancer (BRCA) is still not clear. METHODS: Herein, we analyzed the data of BRCA from both The Cancer Genome Atlas (TCGA) and GSEA MSigDB database. Based on the obtained pyroptosis-related genes (PRGs), we searched the interactions by STRING. After that, we performed clustering analysis by ConsensusClusterPlus. The PRGs with significant prognostic value were then screened through univariate cox regression and further evaluate by constructing a risk model by least absolute shrinkage and selection operator (LASSO) Cox regression. The immune and sensitivity to drugs were also predicted by comprehensive algorithms. Finally, real-time quantitative PCR (qPCR) was performed on two of the screened signature PRGs. RESULTS: A total of 49 PRGs were obtained from public database and 35 of them were significantly differentially expressed genes (DEGs). Cluster analysis was then performed to explore the relationship between DEGs with overall survival. After that, 6 optimal PRGs (GSDMC, IL-18, CHMP3, TP63, GZMB and CHMP6) were screened out to construct a prognostic signature, which divide BRCA patients into two risk groups. Risk scores were then confirmed to be independent prognostic factors in BRCA. Functional enrichment analyses showed that the signature were obviously associated with tumor-related and immune-associated pathways. 79 microenvironmental cells and 11 immune checkpoint genes were found disparate in two groups. Besides, tumor immune dysfunction and exclusion (TIDE) scores revealed that patients with higher risk scores are more sensitive to immune checkpoint blockade treatment. Patients in the low-risk group were more sensitive to Cytarabine, Docetaxel, Gefitinib, Paclitaxel, and Vinblastine. Inversely, patients in the high-risk group were more sensitive to Lapatinib. Finally, we found that, CHMP3 were down-regulated in both BRCA tissues and cell lines, while IL-18 were up-regulated. CONCLUSION: PRGs play important roles in BRCA. Our study fills the gaps of 6 selected PRGs in BRCA, which were worthy for the further study as predict potential biomarkers and therapeutic targets.
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spelling pubmed-93579452022-08-10 Effect of Pyroptosis-Related Genes on the Prognosis of Breast Cancer Zhou, Ying Zheng, Jianfeng Bai, Mengru Gao, Yuzhen Lin, Nengming Front Oncol Oncology BACKGROUNDS: Pyroptosis, a newly pattern of specific programmed cell death, has been reported to participate in several cancers. However, the value of pyroptosis in breast cancer (BRCA) is still not clear. METHODS: Herein, we analyzed the data of BRCA from both The Cancer Genome Atlas (TCGA) and GSEA MSigDB database. Based on the obtained pyroptosis-related genes (PRGs), we searched the interactions by STRING. After that, we performed clustering analysis by ConsensusClusterPlus. The PRGs with significant prognostic value were then screened through univariate cox regression and further evaluate by constructing a risk model by least absolute shrinkage and selection operator (LASSO) Cox regression. The immune and sensitivity to drugs were also predicted by comprehensive algorithms. Finally, real-time quantitative PCR (qPCR) was performed on two of the screened signature PRGs. RESULTS: A total of 49 PRGs were obtained from public database and 35 of them were significantly differentially expressed genes (DEGs). Cluster analysis was then performed to explore the relationship between DEGs with overall survival. After that, 6 optimal PRGs (GSDMC, IL-18, CHMP3, TP63, GZMB and CHMP6) were screened out to construct a prognostic signature, which divide BRCA patients into two risk groups. Risk scores were then confirmed to be independent prognostic factors in BRCA. Functional enrichment analyses showed that the signature were obviously associated with tumor-related and immune-associated pathways. 79 microenvironmental cells and 11 immune checkpoint genes were found disparate in two groups. Besides, tumor immune dysfunction and exclusion (TIDE) scores revealed that patients with higher risk scores are more sensitive to immune checkpoint blockade treatment. Patients in the low-risk group were more sensitive to Cytarabine, Docetaxel, Gefitinib, Paclitaxel, and Vinblastine. Inversely, patients in the high-risk group were more sensitive to Lapatinib. Finally, we found that, CHMP3 were down-regulated in both BRCA tissues and cell lines, while IL-18 were up-regulated. CONCLUSION: PRGs play important roles in BRCA. Our study fills the gaps of 6 selected PRGs in BRCA, which were worthy for the further study as predict potential biomarkers and therapeutic targets. Frontiers Media S.A. 2022-07-25 /pmc/articles/PMC9357945/ /pubmed/35957895 http://dx.doi.org/10.3389/fonc.2022.948169 Text en Copyright © 2022 Zhou, Zheng, Bai, Gao and Lin 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
Zhou, Ying
Zheng, Jianfeng
Bai, Mengru
Gao, Yuzhen
Lin, Nengming
Effect of Pyroptosis-Related Genes on the Prognosis of Breast Cancer
title Effect of Pyroptosis-Related Genes on the Prognosis of Breast Cancer
title_full Effect of Pyroptosis-Related Genes on the Prognosis of Breast Cancer
title_fullStr Effect of Pyroptosis-Related Genes on the Prognosis of Breast Cancer
title_full_unstemmed Effect of Pyroptosis-Related Genes on the Prognosis of Breast Cancer
title_short Effect of Pyroptosis-Related Genes on the Prognosis of Breast Cancer
title_sort effect of pyroptosis-related genes on the prognosis of breast cancer
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9357945/
https://www.ncbi.nlm.nih.gov/pubmed/35957895
http://dx.doi.org/10.3389/fonc.2022.948169
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