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Metabolomic profiles in breast cancer:a pilot case-control study in the breast cancer family registry
BACKGROUND: Metabolomics is emerging as an important tool for detecting differences between diseased and non-diseased individuals. However, prospective studies are limited. METHODS: We examined the detectability, reliability, and distribution of metabolites measured in pre-diagnostic plasma samples...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5935968/ https://www.ncbi.nlm.nih.gov/pubmed/29728083 http://dx.doi.org/10.1186/s12885-018-4437-z |
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author | Dougan, Marcelle M. Li, Yuqing Chu, Lisa W. Haile, Robert W. Whittemore, Alice S. Han, Summer S. Moore, Steven C. Sampson, Joshua N. Andrulis, Irene L. John, Esther M. Hsing, Ann W. |
author_facet | Dougan, Marcelle M. Li, Yuqing Chu, Lisa W. Haile, Robert W. Whittemore, Alice S. Han, Summer S. Moore, Steven C. Sampson, Joshua N. Andrulis, Irene L. John, Esther M. Hsing, Ann W. |
author_sort | Dougan, Marcelle M. |
collection | PubMed |
description | BACKGROUND: Metabolomics is emerging as an important tool for detecting differences between diseased and non-diseased individuals. However, prospective studies are limited. METHODS: We examined the detectability, reliability, and distribution of metabolites measured in pre-diagnostic plasma samples in a pilot study of women enrolled in the Northern California site of the Breast Cancer Family Registry. The study included 45 cases diagnosed with breast cancer at least one year after the blood draw, and 45 controls. Controls were matched on age (within 5 years), family status, BRCA status, and menopausal status. Duplicate samples were included for reliability assessment. We used a liquid chromatography/gas chromatography mass spectrometer platform to measure metabolites. We calculated intraclass correlations (ICCs) among duplicate samples, and coefficients of variation (CVs) across metabolites. RESULTS: Of the 661 named metabolites detected, 338 (51%) were found in all samples, and 490 (74%) in more than 80% of samples. The median ICC between duplicates was 0.96 (25th – 75th percentile: 0.82–0.99). We observed a greater than 20% case-control difference in 24 metabolites (p < 0.05), although these associations were not significant after adjusting for multiple comparisons. CONCLUSIONS: These data show that assays are reproducible for many metabolites, there is a minimal laboratory variation for the same sample, and a large between-person variation. Despite small sample size, differences between cases and controls in some metabolites suggest that a well-powered large-scale study is likely to detect biological meaningful differences to provide a better understanding of breast cancer etiology. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12885-018-4437-z) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5935968 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-59359682018-05-11 Metabolomic profiles in breast cancer:a pilot case-control study in the breast cancer family registry Dougan, Marcelle M. Li, Yuqing Chu, Lisa W. Haile, Robert W. Whittemore, Alice S. Han, Summer S. Moore, Steven C. Sampson, Joshua N. Andrulis, Irene L. John, Esther M. Hsing, Ann W. BMC Cancer Research Article BACKGROUND: Metabolomics is emerging as an important tool for detecting differences between diseased and non-diseased individuals. However, prospective studies are limited. METHODS: We examined the detectability, reliability, and distribution of metabolites measured in pre-diagnostic plasma samples in a pilot study of women enrolled in the Northern California site of the Breast Cancer Family Registry. The study included 45 cases diagnosed with breast cancer at least one year after the blood draw, and 45 controls. Controls were matched on age (within 5 years), family status, BRCA status, and menopausal status. Duplicate samples were included for reliability assessment. We used a liquid chromatography/gas chromatography mass spectrometer platform to measure metabolites. We calculated intraclass correlations (ICCs) among duplicate samples, and coefficients of variation (CVs) across metabolites. RESULTS: Of the 661 named metabolites detected, 338 (51%) were found in all samples, and 490 (74%) in more than 80% of samples. The median ICC between duplicates was 0.96 (25th – 75th percentile: 0.82–0.99). We observed a greater than 20% case-control difference in 24 metabolites (p < 0.05), although these associations were not significant after adjusting for multiple comparisons. CONCLUSIONS: These data show that assays are reproducible for many metabolites, there is a minimal laboratory variation for the same sample, and a large between-person variation. Despite small sample size, differences between cases and controls in some metabolites suggest that a well-powered large-scale study is likely to detect biological meaningful differences to provide a better understanding of breast cancer etiology. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12885-018-4437-z) contains supplementary material, which is available to authorized users. BioMed Central 2018-05-05 /pmc/articles/PMC5935968/ /pubmed/29728083 http://dx.doi.org/10.1186/s12885-018-4437-z Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Dougan, Marcelle M. Li, Yuqing Chu, Lisa W. Haile, Robert W. Whittemore, Alice S. Han, Summer S. Moore, Steven C. Sampson, Joshua N. Andrulis, Irene L. John, Esther M. Hsing, Ann W. Metabolomic profiles in breast cancer:a pilot case-control study in the breast cancer family registry |
title | Metabolomic profiles in breast cancer:a pilot case-control study in the breast cancer family registry |
title_full | Metabolomic profiles in breast cancer:a pilot case-control study in the breast cancer family registry |
title_fullStr | Metabolomic profiles in breast cancer:a pilot case-control study in the breast cancer family registry |
title_full_unstemmed | Metabolomic profiles in breast cancer:a pilot case-control study in the breast cancer family registry |
title_short | Metabolomic profiles in breast cancer:a pilot case-control study in the breast cancer family registry |
title_sort | metabolomic profiles in breast cancer:a pilot case-control study in the breast cancer family registry |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5935968/ https://www.ncbi.nlm.nih.gov/pubmed/29728083 http://dx.doi.org/10.1186/s12885-018-4437-z |
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