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Comprehensive Analysis of Necroptosis-Related Genes as Prognostic Factors and Immunological Biomarkers in Breast Cancer

Breast cancer (BC) is a lethal malignancy with a poor prognosis. Necroptosis is critical in the progression of cancer. However, the expression of genes involved in necroptosis in BC and their association with prognosis remain unclear. We investigated the predictive potential of necroptosis-related g...

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Autores principales: Xu, Yingkun, Wu, Qiulin, Tang, Zhenrong, Tan, Zhaofu, Pu, Dongyao, Tan, Wenhao, Zhang, Wenjie, Liu, Shengchun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9863352/
https://www.ncbi.nlm.nih.gov/pubmed/36675706
http://dx.doi.org/10.3390/jpm13010044
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author Xu, Yingkun
Wu, Qiulin
Tang, Zhenrong
Tan, Zhaofu
Pu, Dongyao
Tan, Wenhao
Zhang, Wenjie
Liu, Shengchun
author_facet Xu, Yingkun
Wu, Qiulin
Tang, Zhenrong
Tan, Zhaofu
Pu, Dongyao
Tan, Wenhao
Zhang, Wenjie
Liu, Shengchun
author_sort Xu, Yingkun
collection PubMed
description Breast cancer (BC) is a lethal malignancy with a poor prognosis. Necroptosis is critical in the progression of cancer. However, the expression of genes involved in necroptosis in BC and their association with prognosis remain unclear. We investigated the predictive potential of necroptosis-related genes in BC samples from the TCGA dataset. We used LASSO regression to build a risk model consisting of twelve necroptosis-related genes in BC. Using the necroptosis-related risk model, we were able to successfully classify BC patients into high- and low-risk groups with significant prognostic differences (p = 4.872 × 10 (−7)). Additionally, we developed a matched nomogram predicting 5, 7, and 10-year overall survival in BC patients based on this necroptosis-related risk model. Our next step was to perform multiple GSEA analyses to explore the biological pathways through which these necroptosis-related risk genes influence cancer progression. For these twelve risk model genes, we analyzed CNV, SNV, OS, methylation, immune cell infiltration, and drug sensitivity in pan-cancer. In addition, immunohistochemical data from the THPA database were used to validate the protein expression of these risk model genes in BC. Taken together, we believe that necroptosis-related genes are considered potential therapeutic targets in BC and should be further investigated.
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spelling pubmed-98633522023-01-22 Comprehensive Analysis of Necroptosis-Related Genes as Prognostic Factors and Immunological Biomarkers in Breast Cancer Xu, Yingkun Wu, Qiulin Tang, Zhenrong Tan, Zhaofu Pu, Dongyao Tan, Wenhao Zhang, Wenjie Liu, Shengchun J Pers Med Article Breast cancer (BC) is a lethal malignancy with a poor prognosis. Necroptosis is critical in the progression of cancer. However, the expression of genes involved in necroptosis in BC and their association with prognosis remain unclear. We investigated the predictive potential of necroptosis-related genes in BC samples from the TCGA dataset. We used LASSO regression to build a risk model consisting of twelve necroptosis-related genes in BC. Using the necroptosis-related risk model, we were able to successfully classify BC patients into high- and low-risk groups with significant prognostic differences (p = 4.872 × 10 (−7)). Additionally, we developed a matched nomogram predicting 5, 7, and 10-year overall survival in BC patients based on this necroptosis-related risk model. Our next step was to perform multiple GSEA analyses to explore the biological pathways through which these necroptosis-related risk genes influence cancer progression. For these twelve risk model genes, we analyzed CNV, SNV, OS, methylation, immune cell infiltration, and drug sensitivity in pan-cancer. In addition, immunohistochemical data from the THPA database were used to validate the protein expression of these risk model genes in BC. Taken together, we believe that necroptosis-related genes are considered potential therapeutic targets in BC and should be further investigated. MDPI 2022-12-26 /pmc/articles/PMC9863352/ /pubmed/36675706 http://dx.doi.org/10.3390/jpm13010044 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Xu, Yingkun
Wu, Qiulin
Tang, Zhenrong
Tan, Zhaofu
Pu, Dongyao
Tan, Wenhao
Zhang, Wenjie
Liu, Shengchun
Comprehensive Analysis of Necroptosis-Related Genes as Prognostic Factors and Immunological Biomarkers in Breast Cancer
title Comprehensive Analysis of Necroptosis-Related Genes as Prognostic Factors and Immunological Biomarkers in Breast Cancer
title_full Comprehensive Analysis of Necroptosis-Related Genes as Prognostic Factors and Immunological Biomarkers in Breast Cancer
title_fullStr Comprehensive Analysis of Necroptosis-Related Genes as Prognostic Factors and Immunological Biomarkers in Breast Cancer
title_full_unstemmed Comprehensive Analysis of Necroptosis-Related Genes as Prognostic Factors and Immunological Biomarkers in Breast Cancer
title_short Comprehensive Analysis of Necroptosis-Related Genes as Prognostic Factors and Immunological Biomarkers in Breast Cancer
title_sort comprehensive analysis of necroptosis-related genes as prognostic factors and immunological biomarkers in breast cancer
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9863352/
https://www.ncbi.nlm.nih.gov/pubmed/36675706
http://dx.doi.org/10.3390/jpm13010044
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