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A signature constructed with mitophagy-related genes to predict the prognosis and therapy response for breast cancer
Over the past decades, the incidence and mortality rates of breast cancer (BC) have increased rapidly; however, molecular biomarkers that can reliably detect BC are yet to be discovered. Our study aimed to identify a novel signature that can predict the prognosis of patients with BC. Data from the T...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Impact Journals
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9417220/ https://www.ncbi.nlm.nih.gov/pubmed/35939339 http://dx.doi.org/10.18632/aging.204209 |
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author | Zhao, Yingan Zhang, Yingjue Dai, Chen Hong, Kai Guo, Yangyang |
author_facet | Zhao, Yingan Zhang, Yingjue Dai, Chen Hong, Kai Guo, Yangyang |
author_sort | Zhao, Yingan |
collection | PubMed |
description | Over the past decades, the incidence and mortality rates of breast cancer (BC) have increased rapidly; however, molecular biomarkers that can reliably detect BC are yet to be discovered. Our study aimed to identify a novel signature that can predict the prognosis of patients with BC. Data from the TCGA-BRCA cohort were analyzed using univariate Cox regression analysis, and least absolute shrinkage and selection operator (LASSO) analysis was performed to build a stable prognostic model. Subsequently, Kaplan–Meier (K–M) and receiver operating characteristic (ROC) analyses were performed to demonstrate the predictive power of our gene signature. Each patient was assigned to either a low- or high-risk group. Patients with high-risk BC had poorer survival than those with low-risk BC. Cox regression analysis suggested that our signature was an independent prognostic factor. Additionally, decision curve analysis and calibration accurately predicted the capacity of our nomogram. Thus, based on the differentially expressed genes (DEGs) of mitophagy-related tumor classification, we established a 13-gene signature and robust nomogram for predicting BC prognosis, which can be beneficial for the diagnosis and treatment of BC. |
format | Online Article Text |
id | pubmed-9417220 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Impact Journals |
record_format | MEDLINE/PubMed |
spelling | pubmed-94172202022-08-29 A signature constructed with mitophagy-related genes to predict the prognosis and therapy response for breast cancer Zhao, Yingan Zhang, Yingjue Dai, Chen Hong, Kai Guo, Yangyang Aging (Albany NY) Research Paper Over the past decades, the incidence and mortality rates of breast cancer (BC) have increased rapidly; however, molecular biomarkers that can reliably detect BC are yet to be discovered. Our study aimed to identify a novel signature that can predict the prognosis of patients with BC. Data from the TCGA-BRCA cohort were analyzed using univariate Cox regression analysis, and least absolute shrinkage and selection operator (LASSO) analysis was performed to build a stable prognostic model. Subsequently, Kaplan–Meier (K–M) and receiver operating characteristic (ROC) analyses were performed to demonstrate the predictive power of our gene signature. Each patient was assigned to either a low- or high-risk group. Patients with high-risk BC had poorer survival than those with low-risk BC. Cox regression analysis suggested that our signature was an independent prognostic factor. Additionally, decision curve analysis and calibration accurately predicted the capacity of our nomogram. Thus, based on the differentially expressed genes (DEGs) of mitophagy-related tumor classification, we established a 13-gene signature and robust nomogram for predicting BC prognosis, which can be beneficial for the diagnosis and treatment of BC. Impact Journals 2022-08-05 /pmc/articles/PMC9417220/ /pubmed/35939339 http://dx.doi.org/10.18632/aging.204209 Text en Copyright: © 2022 Zhao et al. https://creativecommons.org/licenses/by/3.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/3.0/) (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Paper Zhao, Yingan Zhang, Yingjue Dai, Chen Hong, Kai Guo, Yangyang A signature constructed with mitophagy-related genes to predict the prognosis and therapy response for breast cancer |
title | A signature constructed with mitophagy-related genes to predict the prognosis and therapy response for breast cancer |
title_full | A signature constructed with mitophagy-related genes to predict the prognosis and therapy response for breast cancer |
title_fullStr | A signature constructed with mitophagy-related genes to predict the prognosis and therapy response for breast cancer |
title_full_unstemmed | A signature constructed with mitophagy-related genes to predict the prognosis and therapy response for breast cancer |
title_short | A signature constructed with mitophagy-related genes to predict the prognosis and therapy response for breast cancer |
title_sort | signature constructed with mitophagy-related genes to predict the prognosis and therapy response for breast cancer |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9417220/ https://www.ncbi.nlm.nih.gov/pubmed/35939339 http://dx.doi.org/10.18632/aging.204209 |
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