A two-tiered targeted proteomics approach to identify pre-diagnostic biomarkers of colorectal cancer risk

Abstract 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 r...

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Autores principales:	Sophia Harlid, Justin Harbs, Robin Myte, Carl Brunius, Marc J. Gunter, Richard Palmqvist, Xijia Liu, Bethany Van Guelpen
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/ecce1d3ceeb4472caa4b3a0b21c3609a
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spelling	oai:doaj.org-article:ecce1d3ceeb4472caa4b3a0b21c3609a2021-12-02T13:33:51ZA two-tiered targeted proteomics approach to identify pre-diagnostic biomarkers of colorectal cancer risk10.1038/s41598-021-83968-62045-2322https://doaj.org/article/ecce1d3ceeb4472caa4b3a0b21c3609a2021-03-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-83968-6https://doaj.org/toc/2045-2322Abstract 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.Sophia HarlidJustin HarbsRobin MyteCarl BruniusMarc J. GunterRichard PalmqvistXijia LiuBethany Van GuelpenNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Sophia Harlid Justin Harbs Robin Myte Carl Brunius Marc J. Gunter Richard Palmqvist Xijia Liu Bethany Van Guelpen A two-tiered targeted proteomics approach to identify pre-diagnostic biomarkers of colorectal cancer risk
description	Abstract 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	article
author	Sophia Harlid Justin Harbs Robin Myte Carl Brunius Marc J. Gunter Richard Palmqvist Xijia Liu Bethany Van Guelpen
author_facet	Sophia Harlid Justin Harbs Robin Myte Carl Brunius Marc J. Gunter Richard Palmqvist Xijia Liu Bethany Van Guelpen
author_sort	Sophia Harlid
title	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_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_sort	two-tiered targeted proteomics approach to identify pre-diagnostic biomarkers of colorectal cancer risk
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/ecce1d3ceeb4472caa4b3a0b21c3609a
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A two-tiered targeted proteomics approach to identify pre-diagnostic biomarkers of colorectal cancer risk

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