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Chromatin Regulator-Related Gene Signature for Predicting Prognosis and Immunotherapy Efficacy in Breast Cancer
BACKGROUND: Many studies have found that chromatin regulators (CRs) are correlated with tumorigenesis and disease prognosis. Here, we attempted to build a new CR-related gene model to predict breast cancer (BC) survival status. METHODS: First, the CR-related differentially expressed genes (DEGs) wer...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9902130/ https://www.ncbi.nlm.nih.gov/pubmed/36755810 http://dx.doi.org/10.1155/2023/2736932 |
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author | Feng, Dongxu Li, Wenbing Wu, Wei Kahlert, Ulf Dietrich Gao, Pingfa Hu, Gangfeng Huang, Xia Shi, Wenjie Li, Huichao |
author_facet | Feng, Dongxu Li, Wenbing Wu, Wei Kahlert, Ulf Dietrich Gao, Pingfa Hu, Gangfeng Huang, Xia Shi, Wenjie Li, Huichao |
author_sort | Feng, Dongxu |
collection | PubMed |
description | BACKGROUND: Many studies have found that chromatin regulators (CRs) are correlated with tumorigenesis and disease prognosis. Here, we attempted to build a new CR-related gene model to predict breast cancer (BC) survival status. METHODS: First, the CR-related differentially expressed genes (DEGs) were screened in normal and tumor breast tissues, and the potential mechanism of CR-related DEGs was determined by function analysis. Based on the prognostic DEGs, the Cox regression model was applied to build a signature for BC. Then, survival and receiver operating characteristic (ROC) curves were performed to validate the signature's efficacy and identify its independent prognostic value. The CIBERSORT and tumor immune dysfunction and exclusion (TIDE) algorithms were used to assess the immune cells infiltration and immunotherapy efficacy for this signature, respectively. Additionally, a novel nomogram was also built for clinical decisions. RESULTS: We identified 98 CR-related DEGs in breast tissues and constructed a novel 6 CR-related gene signature (ARID5A, ASCL1, IKZF3, KDM4B, PRDM11, and TFF1) to predict the outcome of BC patients. The prognostic value of this CR-related gene signature was validated with outstanding predictive performance. The TIDE analysis revealed that the high-risk group patients had a better response to immune checkpoint blockade (ICB) therapy. CONCLUSION: A new CR-related gene signature was built, and this signature could provide the independent predictive capability of prognosis and immunotherapy efficacy for BC patients. |
format | Online Article Text |
id | pubmed-9902130 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-99021302023-02-07 Chromatin Regulator-Related Gene Signature for Predicting Prognosis and Immunotherapy Efficacy in Breast Cancer Feng, Dongxu Li, Wenbing Wu, Wei Kahlert, Ulf Dietrich Gao, Pingfa Hu, Gangfeng Huang, Xia Shi, Wenjie Li, Huichao J Oncol Research Article BACKGROUND: Many studies have found that chromatin regulators (CRs) are correlated with tumorigenesis and disease prognosis. Here, we attempted to build a new CR-related gene model to predict breast cancer (BC) survival status. METHODS: First, the CR-related differentially expressed genes (DEGs) were screened in normal and tumor breast tissues, and the potential mechanism of CR-related DEGs was determined by function analysis. Based on the prognostic DEGs, the Cox regression model was applied to build a signature for BC. Then, survival and receiver operating characteristic (ROC) curves were performed to validate the signature's efficacy and identify its independent prognostic value. The CIBERSORT and tumor immune dysfunction and exclusion (TIDE) algorithms were used to assess the immune cells infiltration and immunotherapy efficacy for this signature, respectively. Additionally, a novel nomogram was also built for clinical decisions. RESULTS: We identified 98 CR-related DEGs in breast tissues and constructed a novel 6 CR-related gene signature (ARID5A, ASCL1, IKZF3, KDM4B, PRDM11, and TFF1) to predict the outcome of BC patients. The prognostic value of this CR-related gene signature was validated with outstanding predictive performance. The TIDE analysis revealed that the high-risk group patients had a better response to immune checkpoint blockade (ICB) therapy. CONCLUSION: A new CR-related gene signature was built, and this signature could provide the independent predictive capability of prognosis and immunotherapy efficacy for BC patients. Hindawi 2023-01-30 /pmc/articles/PMC9902130/ /pubmed/36755810 http://dx.doi.org/10.1155/2023/2736932 Text en Copyright © 2023 Dongxu Feng et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Feng, Dongxu Li, Wenbing Wu, Wei Kahlert, Ulf Dietrich Gao, Pingfa Hu, Gangfeng Huang, Xia Shi, Wenjie Li, Huichao Chromatin Regulator-Related Gene Signature for Predicting Prognosis and Immunotherapy Efficacy in Breast Cancer |
title | Chromatin Regulator-Related Gene Signature for Predicting Prognosis and Immunotherapy Efficacy in Breast Cancer |
title_full | Chromatin Regulator-Related Gene Signature for Predicting Prognosis and Immunotherapy Efficacy in Breast Cancer |
title_fullStr | Chromatin Regulator-Related Gene Signature for Predicting Prognosis and Immunotherapy Efficacy in Breast Cancer |
title_full_unstemmed | Chromatin Regulator-Related Gene Signature for Predicting Prognosis and Immunotherapy Efficacy in Breast Cancer |
title_short | Chromatin Regulator-Related Gene Signature for Predicting Prognosis and Immunotherapy Efficacy in Breast Cancer |
title_sort | chromatin regulator-related gene signature for predicting prognosis and immunotherapy efficacy in breast cancer |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9902130/ https://www.ncbi.nlm.nih.gov/pubmed/36755810 http://dx.doi.org/10.1155/2023/2736932 |
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