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Household Income Is Associated with the p53 Mutation Frequency in Human Breast Tumors

BACKGROUND: A study from Scotland reported that the p53 mutation frequency in breast tumors is associated with socio-economic deprivation. METHODS: We analyzed the association of the tumor p53 mutational status with tumor characteristics, education, and self-reported annual household income (HI) amo...

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Autores principales: Starks, Adrienne M., Martin, Damali N., Dorsey, Tiffany H., Boersma, Brenda J., Wallace, Tiffany A., Ambs, Stefan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3585937/
https://www.ncbi.nlm.nih.gov/pubmed/23469190
http://dx.doi.org/10.1371/journal.pone.0057361
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author Starks, Adrienne M.
Martin, Damali N.
Dorsey, Tiffany H.
Boersma, Brenda J.
Wallace, Tiffany A.
Ambs, Stefan
author_facet Starks, Adrienne M.
Martin, Damali N.
Dorsey, Tiffany H.
Boersma, Brenda J.
Wallace, Tiffany A.
Ambs, Stefan
author_sort Starks, Adrienne M.
collection PubMed
description BACKGROUND: A study from Scotland reported that the p53 mutation frequency in breast tumors is associated with socio-economic deprivation. METHODS: We analyzed the association of the tumor p53 mutational status with tumor characteristics, education, and self-reported annual household income (HI) among 173 breast cancer patients from the greater Baltimore area, United States. RESULTS: p53 mutational frequency was significantly associated with HI. Patients with < $15,000 HI had the highest p53 mutation frequency (21%), followed by the income group between $15,000 and $60,000 (18%), while those above $60,000 HI had the fewest mutations (5%). When dichotomized at $60,000, 26 out of 135 patients in the low income category had acquired a p53 mutation, while only 2 out of 38 with a high income carried a mutation (P < 0.05). In the adjusted logistic regression analysis with 3 income categories (trend test), the association between HI and p53 mutational status was independent of tumor characteristics, age, race/ethnicity, tobacco smoking and body mass. Further analyses revealed that HI may impact the p53 mutational frequency preferentially in patients who develop an estrogen receptor (ER)-negative disease. Within this group, 42% of the low income patients (< $15,000 HI) carried a mutation, followed by the middle income group (21%), while those above $60,000 HI did not carry mutations (P (trend) < 0.05). CONCLUSIONS: HI is associated with the p53 mutational frequency in patients who develop an ER-negative disease. Furthermore, high income patients may acquire fewer p53 mutations than other patients, suggesting that lifetime exposures associated with socio-economic status may impact breast cancer biology.
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spelling pubmed-35859372013-03-06 Household Income Is Associated with the p53 Mutation Frequency in Human Breast Tumors Starks, Adrienne M. Martin, Damali N. Dorsey, Tiffany H. Boersma, Brenda J. Wallace, Tiffany A. Ambs, Stefan PLoS One Research Article BACKGROUND: A study from Scotland reported that the p53 mutation frequency in breast tumors is associated with socio-economic deprivation. METHODS: We analyzed the association of the tumor p53 mutational status with tumor characteristics, education, and self-reported annual household income (HI) among 173 breast cancer patients from the greater Baltimore area, United States. RESULTS: p53 mutational frequency was significantly associated with HI. Patients with < $15,000 HI had the highest p53 mutation frequency (21%), followed by the income group between $15,000 and $60,000 (18%), while those above $60,000 HI had the fewest mutations (5%). When dichotomized at $60,000, 26 out of 135 patients in the low income category had acquired a p53 mutation, while only 2 out of 38 with a high income carried a mutation (P < 0.05). In the adjusted logistic regression analysis with 3 income categories (trend test), the association between HI and p53 mutational status was independent of tumor characteristics, age, race/ethnicity, tobacco smoking and body mass. Further analyses revealed that HI may impact the p53 mutational frequency preferentially in patients who develop an estrogen receptor (ER)-negative disease. Within this group, 42% of the low income patients (< $15,000 HI) carried a mutation, followed by the middle income group (21%), while those above $60,000 HI did not carry mutations (P (trend) < 0.05). CONCLUSIONS: HI is associated with the p53 mutational frequency in patients who develop an ER-negative disease. Furthermore, high income patients may acquire fewer p53 mutations than other patients, suggesting that lifetime exposures associated with socio-economic status may impact breast cancer biology. Public Library of Science 2013-03-01 /pmc/articles/PMC3585937/ /pubmed/23469190 http://dx.doi.org/10.1371/journal.pone.0057361 Text en https://creativecommons.org/publicdomain/zero/1.0/ This is an open-access article distributed under the terms of the Creative Commons Public Domain declaration, which stipulates that, once placed in the public domain, this work may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose.
spellingShingle Research Article
Starks, Adrienne M.
Martin, Damali N.
Dorsey, Tiffany H.
Boersma, Brenda J.
Wallace, Tiffany A.
Ambs, Stefan
Household Income Is Associated with the p53 Mutation Frequency in Human Breast Tumors
title Household Income Is Associated with the p53 Mutation Frequency in Human Breast Tumors
title_full Household Income Is Associated with the p53 Mutation Frequency in Human Breast Tumors
title_fullStr Household Income Is Associated with the p53 Mutation Frequency in Human Breast Tumors
title_full_unstemmed Household Income Is Associated with the p53 Mutation Frequency in Human Breast Tumors
title_short Household Income Is Associated with the p53 Mutation Frequency in Human Breast Tumors
title_sort household income is associated with the p53 mutation frequency in human breast tumors
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3585937/
https://www.ncbi.nlm.nih.gov/pubmed/23469190
http://dx.doi.org/10.1371/journal.pone.0057361
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