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Identification of a prognosis-associated signature associated with energy metabolism in triple-negative breast cancer
At present, a large number of exciting results have been found regarding energy metabolism within the triple-negative breast cancer (TNBC) field. Apart from aerobic glycolysis, a number of other catabolic pathways have also been demonstrated to participate in energy generation. However, the prognost...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
D.A. Spandidos
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7388543/ https://www.ncbi.nlm.nih.gov/pubmed/32582991 http://dx.doi.org/10.3892/or.2020.7657 |
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author | Li, Chao Li, Xujun Li, Guangming Sun, Long Zhang, Wei Jiang, Jing Ge, Qidong |
author_facet | Li, Chao Li, Xujun Li, Guangming Sun, Long Zhang, Wei Jiang, Jing Ge, Qidong |
author_sort | Li, Chao |
collection | PubMed |
description | At present, a large number of exciting results have been found regarding energy metabolism within the triple-negative breast cancer (TNBC) field. Apart from aerobic glycolysis, a number of other catabolic pathways have also been demonstrated to participate in energy generation. However, the prognostic value of energy metabolism for TNBC currently remains unclear. In the present study, the association between gene expression profiles of energy metabolism and outcomes in patients with TNBC was examined using datasets obtained from the Gene Expression Omnibus and The Cancer Genome Atlas. In total, four robust TNBC subtypes were identified on the basis of negative matrix factorization clustering and gene expression patterns, which exhibited distinct immunological, molecular and prognostic (disease-free survival) features. The differentially expressed genes were subsequently identified from the subgroup that demonstrated the poorest prognosis compared with the remaining 3 subgroups, where their biological functions were assessed further by means of gene ontology enrichment analysis. Any signatures found to be associated with energy metabolism were then established using the Cox proportional hazards model to assess patient prognosis. According to results of Kaplan-Meier analysis, the constructed signature consisting of eight genes that were associated with energy metabolism distinguished patient outcomes into low- and high-risk groups. In addition, this signature, which was found to be markedly associated with the clinical characteristics of the patients, served as an independent factor in predicting TNBC patient prognosis. According to gene set enrichment analysis, the gene sets related to the high-risk group participated in the MAPK signal transduction pathway, focal adhesion and extracellular matrix receptor interaction, whilst those related to the low-risk group were revealed to be mainly associated with mismatch repair and propanoate metabolism. Findings from the present study shed new light on the role of energy metabolism within TNBC, where the eight-gene signature associated with energy metabolism constructed can be utilized as a new prognostic marker for predicting survival in patients with TNBC. |
format | Online Article Text |
id | pubmed-7388543 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | D.A. Spandidos |
record_format | MEDLINE/PubMed |
spelling | pubmed-73885432020-08-05 Identification of a prognosis-associated signature associated with energy metabolism in triple-negative breast cancer Li, Chao Li, Xujun Li, Guangming Sun, Long Zhang, Wei Jiang, Jing Ge, Qidong Oncol Rep Articles At present, a large number of exciting results have been found regarding energy metabolism within the triple-negative breast cancer (TNBC) field. Apart from aerobic glycolysis, a number of other catabolic pathways have also been demonstrated to participate in energy generation. However, the prognostic value of energy metabolism for TNBC currently remains unclear. In the present study, the association between gene expression profiles of energy metabolism and outcomes in patients with TNBC was examined using datasets obtained from the Gene Expression Omnibus and The Cancer Genome Atlas. In total, four robust TNBC subtypes were identified on the basis of negative matrix factorization clustering and gene expression patterns, which exhibited distinct immunological, molecular and prognostic (disease-free survival) features. The differentially expressed genes were subsequently identified from the subgroup that demonstrated the poorest prognosis compared with the remaining 3 subgroups, where their biological functions were assessed further by means of gene ontology enrichment analysis. Any signatures found to be associated with energy metabolism were then established using the Cox proportional hazards model to assess patient prognosis. According to results of Kaplan-Meier analysis, the constructed signature consisting of eight genes that were associated with energy metabolism distinguished patient outcomes into low- and high-risk groups. In addition, this signature, which was found to be markedly associated with the clinical characteristics of the patients, served as an independent factor in predicting TNBC patient prognosis. According to gene set enrichment analysis, the gene sets related to the high-risk group participated in the MAPK signal transduction pathway, focal adhesion and extracellular matrix receptor interaction, whilst those related to the low-risk group were revealed to be mainly associated with mismatch repair and propanoate metabolism. Findings from the present study shed new light on the role of energy metabolism within TNBC, where the eight-gene signature associated with energy metabolism constructed can be utilized as a new prognostic marker for predicting survival in patients with TNBC. D.A. Spandidos 2020-09 2020-06-23 /pmc/articles/PMC7388543/ /pubmed/32582991 http://dx.doi.org/10.3892/or.2020.7657 Text en Copyright: © Li et al. This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made. |
spellingShingle | Articles Li, Chao Li, Xujun Li, Guangming Sun, Long Zhang, Wei Jiang, Jing Ge, Qidong Identification of a prognosis-associated signature associated with energy metabolism in triple-negative breast cancer |
title | Identification of a prognosis-associated signature associated with energy metabolism in triple-negative breast cancer |
title_full | Identification of a prognosis-associated signature associated with energy metabolism in triple-negative breast cancer |
title_fullStr | Identification of a prognosis-associated signature associated with energy metabolism in triple-negative breast cancer |
title_full_unstemmed | Identification of a prognosis-associated signature associated with energy metabolism in triple-negative breast cancer |
title_short | Identification of a prognosis-associated signature associated with energy metabolism in triple-negative breast cancer |
title_sort | identification of a prognosis-associated signature associated with energy metabolism in triple-negative breast cancer |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7388543/ https://www.ncbi.nlm.nih.gov/pubmed/32582991 http://dx.doi.org/10.3892/or.2020.7657 |
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