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A two-tiered targeted proteomics approach to identify pre-diagnostic biomarkers of colorectal cancer risk
Colorectal cancer prognosis is dependent on stage, and measures to improve early detection are urgently needed. Using prospectively collected plasma samples from the population-based Northern Sweden Health and Disease Study, we evaluated protein biomarkers in relation to colorectal cancer risk. Appl...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7933352/ https://www.ncbi.nlm.nih.gov/pubmed/33664295 http://dx.doi.org/10.1038/s41598-021-83968-6 |
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author | Harlid, Sophia Harbs, Justin Myte, Robin Brunius, Carl Gunter, Marc J. Palmqvist, Richard Liu, Xijia Van Guelpen, Bethany |
author_facet | Harlid, Sophia Harbs, Justin Myte, Robin Brunius, Carl Gunter, Marc J. Palmqvist, Richard Liu, Xijia Van Guelpen, Bethany |
author_sort | Harlid, Sophia |
collection | PubMed |
description | Colorectal cancer prognosis is dependent on stage, and measures to improve early detection are urgently needed. Using prospectively collected plasma samples from the population-based Northern Sweden Health and Disease Study, we evaluated protein biomarkers in relation to colorectal cancer risk. Applying a two-tiered approach, we analyzed 160 proteins in matched sequential samples from 58 incident colorectal cancer case–control pairs. Twenty-one proteins selected from both this discovery phase and the literature were then analyzed in a validation set of 450 case–control pairs. Odds ratios were estimated by conditional logistic regression. LASSO regression and ROC analysis were used for multi-marker analyses. In the main validation analysis, no proteins retained statistical significance. However, exploratory subgroup analyses showed associations between FGF-21 and colon cancer risk (multivariable OR per 1 SD: 1.23 95% CI 1.03–1.47) as well as between PPY and rectal cancer risk (multivariable OR per 1 SD: 1.47 95% CI 1.12–1.92). Adding protein markers to basic risk predictive models increased performance modestly. Our results highlight the challenge of developing biomarkers that are effective in the asymptomatic, prediagnostic window of opportunity for early detection of colorectal cancer. Distinguishing between cancer subtypes may improve prediction accuracy. However, single biomarkers or small panels may not be sufficient for effective precision screening. |
format | Online Article Text |
id | pubmed-7933352 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-79333522021-03-08 A two-tiered targeted proteomics approach to identify pre-diagnostic biomarkers of colorectal cancer risk Harlid, Sophia Harbs, Justin Myte, Robin Brunius, Carl Gunter, Marc J. Palmqvist, Richard Liu, Xijia Van Guelpen, Bethany Sci Rep Article Colorectal cancer prognosis is dependent on stage, and measures to improve early detection are urgently needed. Using prospectively collected plasma samples from the population-based Northern Sweden Health and Disease Study, we evaluated protein biomarkers in relation to colorectal cancer risk. Applying a two-tiered approach, we analyzed 160 proteins in matched sequential samples from 58 incident colorectal cancer case–control pairs. Twenty-one proteins selected from both this discovery phase and the literature were then analyzed in a validation set of 450 case–control pairs. Odds ratios were estimated by conditional logistic regression. LASSO regression and ROC analysis were used for multi-marker analyses. In the main validation analysis, no proteins retained statistical significance. However, exploratory subgroup analyses showed associations between FGF-21 and colon cancer risk (multivariable OR per 1 SD: 1.23 95% CI 1.03–1.47) as well as between PPY and rectal cancer risk (multivariable OR per 1 SD: 1.47 95% CI 1.12–1.92). Adding protein markers to basic risk predictive models increased performance modestly. Our results highlight the challenge of developing biomarkers that are effective in the asymptomatic, prediagnostic window of opportunity for early detection of colorectal cancer. Distinguishing between cancer subtypes may improve prediction accuracy. However, single biomarkers or small panels may not be sufficient for effective precision screening. Nature Publishing Group UK 2021-03-04 /pmc/articles/PMC7933352/ /pubmed/33664295 http://dx.doi.org/10.1038/s41598-021-83968-6 Text en © The Author(s) 2021 Open Access This 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/. |
spellingShingle | Article Harlid, Sophia Harbs, Justin Myte, Robin Brunius, Carl Gunter, Marc J. Palmqvist, Richard Liu, Xijia Van Guelpen, Bethany A two-tiered targeted proteomics approach to identify pre-diagnostic biomarkers of colorectal cancer risk |
title | A two-tiered targeted proteomics approach to identify pre-diagnostic biomarkers of colorectal cancer risk |
title_full | A two-tiered targeted proteomics approach to identify pre-diagnostic biomarkers of colorectal cancer risk |
title_fullStr | A two-tiered targeted proteomics approach to identify pre-diagnostic biomarkers of colorectal cancer risk |
title_full_unstemmed | A two-tiered targeted proteomics approach to identify pre-diagnostic biomarkers of colorectal cancer risk |
title_short | A two-tiered targeted proteomics approach to identify pre-diagnostic biomarkers of colorectal cancer risk |
title_sort | two-tiered targeted proteomics approach to identify pre-diagnostic biomarkers of colorectal cancer risk |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7933352/ https://www.ncbi.nlm.nih.gov/pubmed/33664295 http://dx.doi.org/10.1038/s41598-021-83968-6 |
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