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Predicting breast cancer metastasis from whole-blood transcriptomic measurements
OBJECTIVE: In this exploratory work we investigate whether blood gene expression measurements predict breast cancer metastasis. Early detection of increased metastatic risk could potentially be life-saving. Our data comes from the Norwegian Women and Cancer epidemiological cohort study. The women wh...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7238609/ https://www.ncbi.nlm.nih.gov/pubmed/32434554 http://dx.doi.org/10.1186/s13104-020-05088-0 |
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author | Holsbø, Einar Perduca, Vittorio Bongo, Lars Ailo Lund, Eiliv Birmelé, Etienne |
author_facet | Holsbø, Einar Perduca, Vittorio Bongo, Lars Ailo Lund, Eiliv Birmelé, Etienne |
author_sort | Holsbø, Einar |
collection | PubMed |
description | OBJECTIVE: In this exploratory work we investigate whether blood gene expression measurements predict breast cancer metastasis. Early detection of increased metastatic risk could potentially be life-saving. Our data comes from the Norwegian Women and Cancer epidemiological cohort study. The women who contributed to these data provided a blood sample up to a year before receiving a breast cancer diagnosis. We estimate a penalized maximum likelihood logistic regression. We evaluate this in terms of calibration, concordance probability, and stability, all of which we estimate by the bootstrap. RESULTS: We identify a set of 108 candidate predictor genes that exhibit a fold change in average metastasized observation where there is none for the average non-metastasized observation. |
format | Online Article Text |
id | pubmed-7238609 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-72386092020-05-29 Predicting breast cancer metastasis from whole-blood transcriptomic measurements Holsbø, Einar Perduca, Vittorio Bongo, Lars Ailo Lund, Eiliv Birmelé, Etienne BMC Res Notes Research Note OBJECTIVE: In this exploratory work we investigate whether blood gene expression measurements predict breast cancer metastasis. Early detection of increased metastatic risk could potentially be life-saving. Our data comes from the Norwegian Women and Cancer epidemiological cohort study. The women who contributed to these data provided a blood sample up to a year before receiving a breast cancer diagnosis. We estimate a penalized maximum likelihood logistic regression. We evaluate this in terms of calibration, concordance probability, and stability, all of which we estimate by the bootstrap. RESULTS: We identify a set of 108 candidate predictor genes that exhibit a fold change in average metastasized observation where there is none for the average non-metastasized observation. BioMed Central 2020-05-20 /pmc/articles/PMC7238609/ /pubmed/32434554 http://dx.doi.org/10.1186/s13104-020-05088-0 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. 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 in a credit line to the data. |
spellingShingle | Research Note Holsbø, Einar Perduca, Vittorio Bongo, Lars Ailo Lund, Eiliv Birmelé, Etienne Predicting breast cancer metastasis from whole-blood transcriptomic measurements |
title | Predicting breast cancer metastasis from whole-blood transcriptomic measurements |
title_full | Predicting breast cancer metastasis from whole-blood transcriptomic measurements |
title_fullStr | Predicting breast cancer metastasis from whole-blood transcriptomic measurements |
title_full_unstemmed | Predicting breast cancer metastasis from whole-blood transcriptomic measurements |
title_short | Predicting breast cancer metastasis from whole-blood transcriptomic measurements |
title_sort | predicting breast cancer metastasis from whole-blood transcriptomic measurements |
topic | Research Note |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7238609/ https://www.ncbi.nlm.nih.gov/pubmed/32434554 http://dx.doi.org/10.1186/s13104-020-05088-0 |
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