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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...

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Autores principales: Zhao, Yingan, Zhang, Yingjue, Dai, Chen, Hong, Kai, Guo, Yangyang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals 2022
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.
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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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