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Molecular features in young vs elderly breast cancer patients and the impacts on survival disparities by age at diagnosis

Young and elderly breast cancer patients are more likely to have a poorer outcome than middle‐aged patients. The intrinsic molecular features for this disparity are unclear. We obtained data from the Cancer Genome Atlas (TCGA) on May 15, 2017 to test the potential mediation effects of the molecular...

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Autores principales: Wang, Mei‐Xia, Ren, Jun‐Ting, Tang, Lu‐Ying, Ren, Ze‐Fang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6051220/
https://www.ncbi.nlm.nih.gov/pubmed/29761914
http://dx.doi.org/10.1002/cam4.1544
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author Wang, Mei‐Xia
Ren, Jun‐Ting
Tang, Lu‐Ying
Ren, Ze‐Fang
author_facet Wang, Mei‐Xia
Ren, Jun‐Ting
Tang, Lu‐Ying
Ren, Ze‐Fang
author_sort Wang, Mei‐Xia
collection PubMed
description Young and elderly breast cancer patients are more likely to have a poorer outcome than middle‐aged patients. The intrinsic molecular features for this disparity are unclear. We obtained data from the Cancer Genome Atlas (TCGA) on May 15, 2017 to test the potential mediation effects of the molecular features on the association between age and prognosis with a four‐step approach. The relative contributions of the molecular features (PAM50 subtype, risk stratification, DNAm age, and mutations in TP53,PIK3CA,MLL3,CDH1,GATA3, and MAP3K1) to age disparities in survival were estimated by Cox proportional hazard models with or without the features. Young patients were significantly more likely to have basal‐like subtype, GATA3 mutations, and younger DNA methylation (DNAm) age than middle‐aged patients (P < .05). Both the young and elderly patients had a significantly increased risk of breast cancer recurrence after adjusted by race, tumor size, and node status (Hazard ratio [HR] (95% confidence interval [CI]): 2.81 [1.44, 5.45], 2.37 [1.45, 3.89], respectively). This increased risk was weakened in the young patients after further adjustments in the molecular features, particularly basal‐like subtype, GATA3 mutations, and DNAm age (HR [95%CI]: 1.87 [0.81, 4.32]), resulting in 33.5% decreased risk of recurrence. Meanwhile, the adjustments of the molecular features did not alter the recurrence risk for the elderly patients. Compared with middle‐aged patients of breast cancer, poorer prognosis of elderly patients may be caused by aging, while poorer prognosis of young patients was probably mediated through intrinsic characteristics, such as basal‐like subtype, GATA3 mutations, and DNAm age of the cancerous tissues.
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spelling pubmed-60512202018-07-20 Molecular features in young vs elderly breast cancer patients and the impacts on survival disparities by age at diagnosis Wang, Mei‐Xia Ren, Jun‐Ting Tang, Lu‐Ying Ren, Ze‐Fang Cancer Med Cancer Biology Young and elderly breast cancer patients are more likely to have a poorer outcome than middle‐aged patients. The intrinsic molecular features for this disparity are unclear. We obtained data from the Cancer Genome Atlas (TCGA) on May 15, 2017 to test the potential mediation effects of the molecular features on the association between age and prognosis with a four‐step approach. The relative contributions of the molecular features (PAM50 subtype, risk stratification, DNAm age, and mutations in TP53,PIK3CA,MLL3,CDH1,GATA3, and MAP3K1) to age disparities in survival were estimated by Cox proportional hazard models with or without the features. Young patients were significantly more likely to have basal‐like subtype, GATA3 mutations, and younger DNA methylation (DNAm) age than middle‐aged patients (P < .05). Both the young and elderly patients had a significantly increased risk of breast cancer recurrence after adjusted by race, tumor size, and node status (Hazard ratio [HR] (95% confidence interval [CI]): 2.81 [1.44, 5.45], 2.37 [1.45, 3.89], respectively). This increased risk was weakened in the young patients after further adjustments in the molecular features, particularly basal‐like subtype, GATA3 mutations, and DNAm age (HR [95%CI]: 1.87 [0.81, 4.32]), resulting in 33.5% decreased risk of recurrence. Meanwhile, the adjustments of the molecular features did not alter the recurrence risk for the elderly patients. Compared with middle‐aged patients of breast cancer, poorer prognosis of elderly patients may be caused by aging, while poorer prognosis of young patients was probably mediated through intrinsic characteristics, such as basal‐like subtype, GATA3 mutations, and DNAm age of the cancerous tissues. John Wiley and Sons Inc. 2018-05-15 /pmc/articles/PMC6051220/ /pubmed/29761914 http://dx.doi.org/10.1002/cam4.1544 Text en © 2018 The Authors. Cancer Medicine published by John Wiley & Sons Ltd. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Cancer Biology
Wang, Mei‐Xia
Ren, Jun‐Ting
Tang, Lu‐Ying
Ren, Ze‐Fang
Molecular features in young vs elderly breast cancer patients and the impacts on survival disparities by age at diagnosis
title Molecular features in young vs elderly breast cancer patients and the impacts on survival disparities by age at diagnosis
title_full Molecular features in young vs elderly breast cancer patients and the impacts on survival disparities by age at diagnosis
title_fullStr Molecular features in young vs elderly breast cancer patients and the impacts on survival disparities by age at diagnosis
title_full_unstemmed Molecular features in young vs elderly breast cancer patients and the impacts on survival disparities by age at diagnosis
title_short Molecular features in young vs elderly breast cancer patients and the impacts on survival disparities by age at diagnosis
title_sort molecular features in young vs elderly breast cancer patients and the impacts on survival disparities by age at diagnosis
topic Cancer Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6051220/
https://www.ncbi.nlm.nih.gov/pubmed/29761914
http://dx.doi.org/10.1002/cam4.1544
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