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Blood DNA methylation profiles improve breast cancer prediction

Although blood DNA methylation (DNAm) profiles are reported to be associated with breast cancer incidence, they have not been widely used in breast cancer risk assessment. Among a breast cancer case–cohort of 2774 women (1551 cases) in the Sister Study, we used candidate CpGs and DNAm estimators of...

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Autores principales: Kresovich, Jacob K., Xu, Zongli, O’Brien, Katie M., Shi, Min, Weinberg, Clarice R., Sandler, Dale P., Taylor, Jack A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8732352/
https://www.ncbi.nlm.nih.gov/pubmed/34411412
http://dx.doi.org/10.1002/1878-0261.13087
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author Kresovich, Jacob K.
Xu, Zongli
O’Brien, Katie M.
Shi, Min
Weinberg, Clarice R.
Sandler, Dale P.
Taylor, Jack A.
author_facet Kresovich, Jacob K.
Xu, Zongli
O’Brien, Katie M.
Shi, Min
Weinberg, Clarice R.
Sandler, Dale P.
Taylor, Jack A.
author_sort Kresovich, Jacob K.
collection PubMed
description Although blood DNA methylation (DNAm) profiles are reported to be associated with breast cancer incidence, they have not been widely used in breast cancer risk assessment. Among a breast cancer case–cohort of 2774 women (1551 cases) in the Sister Study, we used candidate CpGs and DNAm estimators of physiologic characteristics to derive a methylation‐based breast cancer risk score, mBCRS. Overall, 19 CpGs and five DNAm estimators were selected using elastic net regularization to comprise mBCRS. In a test set, higher mBCRS was positively associated with breast cancer incidence, showing similar strength to the polygenic risk score (PRS) based on 313 single nucleotide polymorphisms (313 SNPs). Area under the curve for breast cancer prediction was 0.60 for self‐reported risk factors (RFs), 0.63 for PRS, and 0.63 for mBCRS. Adding mBCRS to PRS and RFs improved breast cancer prediction from 0.66 to 0.71. mBCRS findings were replicated in a nested case–control study within the EPIC‐Italy cohort. These results suggest that mBCRS, a risk score derived using blood DNAm, can be used to enhance breast cancer prediction.
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spelling pubmed-87323522022-01-11 Blood DNA methylation profiles improve breast cancer prediction Kresovich, Jacob K. Xu, Zongli O’Brien, Katie M. Shi, Min Weinberg, Clarice R. Sandler, Dale P. Taylor, Jack A. Mol Oncol Research Articles Although blood DNA methylation (DNAm) profiles are reported to be associated with breast cancer incidence, they have not been widely used in breast cancer risk assessment. Among a breast cancer case–cohort of 2774 women (1551 cases) in the Sister Study, we used candidate CpGs and DNAm estimators of physiologic characteristics to derive a methylation‐based breast cancer risk score, mBCRS. Overall, 19 CpGs and five DNAm estimators were selected using elastic net regularization to comprise mBCRS. In a test set, higher mBCRS was positively associated with breast cancer incidence, showing similar strength to the polygenic risk score (PRS) based on 313 single nucleotide polymorphisms (313 SNPs). Area under the curve for breast cancer prediction was 0.60 for self‐reported risk factors (RFs), 0.63 for PRS, and 0.63 for mBCRS. Adding mBCRS to PRS and RFs improved breast cancer prediction from 0.66 to 0.71. mBCRS findings were replicated in a nested case–control study within the EPIC‐Italy cohort. These results suggest that mBCRS, a risk score derived using blood DNAm, can be used to enhance breast cancer prediction. John Wiley and Sons Inc. 2021-11-09 2022-01 /pmc/articles/PMC8732352/ /pubmed/34411412 http://dx.doi.org/10.1002/1878-0261.13087 Text en Published 2021. This article is a U.S. Government work and is in the public domain in the USA. Molecular Oncology published by John Wiley & Sons Ltd on behalf of Federation of European Biochemical Societies https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Articles
Kresovich, Jacob K.
Xu, Zongli
O’Brien, Katie M.
Shi, Min
Weinberg, Clarice R.
Sandler, Dale P.
Taylor, Jack A.
Blood DNA methylation profiles improve breast cancer prediction
title Blood DNA methylation profiles improve breast cancer prediction
title_full Blood DNA methylation profiles improve breast cancer prediction
title_fullStr Blood DNA methylation profiles improve breast cancer prediction
title_full_unstemmed Blood DNA methylation profiles improve breast cancer prediction
title_short Blood DNA methylation profiles improve breast cancer prediction
title_sort blood dna methylation profiles improve breast cancer prediction
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8732352/
https://www.ncbi.nlm.nih.gov/pubmed/34411412
http://dx.doi.org/10.1002/1878-0261.13087
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