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Development of prognostic signature and nomogram for patients with breast cancer

To identify prognostic signature that could predict the survival of patients with breast cancer (BC). Breast cancer samples and normal breast tissues in the TCGA-BRCA and GSE7390 were included. Differentially expressed genes (DEGs) were identified using the “limma” method. Overall survival (OS) asso...

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Autores principales: Su, Jiao, Miao, Li-Feng, Ye, Xiang-Hua, Cui, Meng-Shen, He, Xiao-Feng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer Health 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6426514/
https://www.ncbi.nlm.nih.gov/pubmed/30882627
http://dx.doi.org/10.1097/MD.0000000000014617
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author Su, Jiao
Miao, Li-Feng
Ye, Xiang-Hua
Cui, Meng-Shen
He, Xiao-Feng
author_facet Su, Jiao
Miao, Li-Feng
Ye, Xiang-Hua
Cui, Meng-Shen
He, Xiao-Feng
author_sort Su, Jiao
collection PubMed
description To identify prognostic signature that could predict the survival of patients with breast cancer (BC). Breast cancer samples and normal breast tissues in the TCGA-BRCA and GSE7390 were included. Differentially expressed genes (DEGs) were identified using the “limma” method. Overall survival (OS) associated with DEGs were obtained using univariate and multivariable Cox proportional-hazards regression analysis, and the corresponding prognostic signature and nomogram were constructed. Calibration analysis and decision curve analysis (DCA) were performed. In all, 742 DEGs were identified, 19 of which were independently correlated with the OS of BC patients. The OS of patients in the 19-gene signature low-risk group was significantly better than that in high-risk group (hazard ratio [HR] 0.3506, 95% confidence interval [CI] 0.2488–0.4939), and the 19-gene based signature was demonstrated to be an independent prognostic factor in patient with BC in the TCGA-BRCA cohort (HR 1.501, 95% CI 1.374–1.640) and validation cohort GSE7392 ((HR 0.3557, 95% CI 0.2155–0.5871, P < .0001)). The primary and internally validated C-indexes for the 19-gene signature-based nomogram were 0.817 and 8.013, respectively. The results of calibration analysis and DCA analysis confirmed the robustness and the clinical usability of the nomogram. We constructed a prognostic signature and nomogram for patient with BC, which showed good application prospect.
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spelling pubmed-64265142019-04-15 Development of prognostic signature and nomogram for patients with breast cancer Su, Jiao Miao, Li-Feng Ye, Xiang-Hua Cui, Meng-Shen He, Xiao-Feng Medicine (Baltimore) Research Article To identify prognostic signature that could predict the survival of patients with breast cancer (BC). Breast cancer samples and normal breast tissues in the TCGA-BRCA and GSE7390 were included. Differentially expressed genes (DEGs) were identified using the “limma” method. Overall survival (OS) associated with DEGs were obtained using univariate and multivariable Cox proportional-hazards regression analysis, and the corresponding prognostic signature and nomogram were constructed. Calibration analysis and decision curve analysis (DCA) were performed. In all, 742 DEGs were identified, 19 of which were independently correlated with the OS of BC patients. The OS of patients in the 19-gene signature low-risk group was significantly better than that in high-risk group (hazard ratio [HR] 0.3506, 95% confidence interval [CI] 0.2488–0.4939), and the 19-gene based signature was demonstrated to be an independent prognostic factor in patient with BC in the TCGA-BRCA cohort (HR 1.501, 95% CI 1.374–1.640) and validation cohort GSE7392 ((HR 0.3557, 95% CI 0.2155–0.5871, P < .0001)). The primary and internally validated C-indexes for the 19-gene signature-based nomogram were 0.817 and 8.013, respectively. The results of calibration analysis and DCA analysis confirmed the robustness and the clinical usability of the nomogram. We constructed a prognostic signature and nomogram for patient with BC, which showed good application prospect. Wolters Kluwer Health 2019-03-15 /pmc/articles/PMC6426514/ /pubmed/30882627 http://dx.doi.org/10.1097/MD.0000000000014617 Text en Copyright © 2019 the Author(s). Published by Wolters Kluwer Health, Inc. http://creativecommons.org/licenses/by-nc/4.0 This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial License 4.0 (CCBY-NC), where it is permissible to download, share, remix, transform, and buildup the work provided it is properly cited. The work cannot be used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc/4.0
spellingShingle Research Article
Su, Jiao
Miao, Li-Feng
Ye, Xiang-Hua
Cui, Meng-Shen
He, Xiao-Feng
Development of prognostic signature and nomogram for patients with breast cancer
title Development of prognostic signature and nomogram for patients with breast cancer
title_full Development of prognostic signature and nomogram for patients with breast cancer
title_fullStr Development of prognostic signature and nomogram for patients with breast cancer
title_full_unstemmed Development of prognostic signature and nomogram for patients with breast cancer
title_short Development of prognostic signature and nomogram for patients with breast cancer
title_sort development of prognostic signature and nomogram for patients with breast cancer
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6426514/
https://www.ncbi.nlm.nih.gov/pubmed/30882627
http://dx.doi.org/10.1097/MD.0000000000014617
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