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Prediction of prognosis and immunotherapy response in breast cancer based on neutrophil extracellular traps-related classification
Neutrophil extracellular traps (NETs), a network of DNA histone complexes and proteins released by activated neutrophils, have been demonstrated to be associated with inflammation, infection related immune response and tumorigenesis in previous reports. However, the relationship between NETs related...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10250592/ https://www.ncbi.nlm.nih.gov/pubmed/37304069 http://dx.doi.org/10.3389/fmolb.2023.1165776 |
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author | Zhao, Jiajing Xie, Xiaojun |
author_facet | Zhao, Jiajing Xie, Xiaojun |
author_sort | Zhao, Jiajing |
collection | PubMed |
description | Neutrophil extracellular traps (NETs), a network of DNA histone complexes and proteins released by activated neutrophils, have been demonstrated to be associated with inflammation, infection related immune response and tumorigenesis in previous reports. However, the relationship between NETs related genes and breast cancer remains controversial. In the study, we retrieved transcriptome data and clinical information of BRCA patients from The Cancer Genome Atlas (TCGA) database and Gene Expression Omnibus (GEO) datasets. The expression matrix of neutrophil extracellular traps (NETs) related genes was generated and consensus clustering was performed by Partitioning Around Medoid (PAM) to classify BRCA patients into two subgroups (NETs high group and NETs low group). Subsequently, we focus on the differentially expressed genes (DEGs) between the two NETs-related subgroups and further explored NETs enrichment related signaling pathways by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. In addition, we constructed a risk signature model by LASSO Cox regression analysis to evaluate the association between riskscore and prognosis. Even more, we explored the landscape of the tumor immune microenvironment and the expression of immune checkpoints related genes as well as HLA genes between two NETs subtypes in breast cancer patients. Moreover, we found and validated the correlation of different immune cells with risk score, as well as the response to immunotherapy in different subgroups of patients was detected by Tumor Immune Dysfunction and Exclusion (TIDE) database. Ultimately, a nomogram prognostic prediction model was established to speculate on the prognosis of breast cancer patients. The results suggest that high riskscore is associated with poor immunotherapy response and adverse clinical outcomes in breast cancer patients. In conclusion, we established a NETs-related stratification system that is beneficial for guiding the clinical treatment and predicting prognosis of BRCA. |
format | Online Article Text |
id | pubmed-10250592 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-102505922023-06-10 Prediction of prognosis and immunotherapy response in breast cancer based on neutrophil extracellular traps-related classification Zhao, Jiajing Xie, Xiaojun Front Mol Biosci Molecular Biosciences Neutrophil extracellular traps (NETs), a network of DNA histone complexes and proteins released by activated neutrophils, have been demonstrated to be associated with inflammation, infection related immune response and tumorigenesis in previous reports. However, the relationship between NETs related genes and breast cancer remains controversial. In the study, we retrieved transcriptome data and clinical information of BRCA patients from The Cancer Genome Atlas (TCGA) database and Gene Expression Omnibus (GEO) datasets. The expression matrix of neutrophil extracellular traps (NETs) related genes was generated and consensus clustering was performed by Partitioning Around Medoid (PAM) to classify BRCA patients into two subgroups (NETs high group and NETs low group). Subsequently, we focus on the differentially expressed genes (DEGs) between the two NETs-related subgroups and further explored NETs enrichment related signaling pathways by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. In addition, we constructed a risk signature model by LASSO Cox regression analysis to evaluate the association between riskscore and prognosis. Even more, we explored the landscape of the tumor immune microenvironment and the expression of immune checkpoints related genes as well as HLA genes between two NETs subtypes in breast cancer patients. Moreover, we found and validated the correlation of different immune cells with risk score, as well as the response to immunotherapy in different subgroups of patients was detected by Tumor Immune Dysfunction and Exclusion (TIDE) database. Ultimately, a nomogram prognostic prediction model was established to speculate on the prognosis of breast cancer patients. The results suggest that high riskscore is associated with poor immunotherapy response and adverse clinical outcomes in breast cancer patients. In conclusion, we established a NETs-related stratification system that is beneficial for guiding the clinical treatment and predicting prognosis of BRCA. Frontiers Media S.A. 2023-05-26 /pmc/articles/PMC10250592/ /pubmed/37304069 http://dx.doi.org/10.3389/fmolb.2023.1165776 Text en Copyright © 2023 Zhao and Xie. 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 | Molecular Biosciences Zhao, Jiajing Xie, Xiaojun Prediction of prognosis and immunotherapy response in breast cancer based on neutrophil extracellular traps-related classification |
title | Prediction of prognosis and immunotherapy response in breast cancer based on neutrophil extracellular traps-related classification |
title_full | Prediction of prognosis and immunotherapy response in breast cancer based on neutrophil extracellular traps-related classification |
title_fullStr | Prediction of prognosis and immunotherapy response in breast cancer based on neutrophil extracellular traps-related classification |
title_full_unstemmed | Prediction of prognosis and immunotherapy response in breast cancer based on neutrophil extracellular traps-related classification |
title_short | Prediction of prognosis and immunotherapy response in breast cancer based on neutrophil extracellular traps-related classification |
title_sort | prediction of prognosis and immunotherapy response in breast cancer based on neutrophil extracellular traps-related classification |
topic | Molecular Biosciences |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10250592/ https://www.ncbi.nlm.nih.gov/pubmed/37304069 http://dx.doi.org/10.3389/fmolb.2023.1165776 |
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