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...

Full description

Bibliographic Details
Published in:Scientific Reports
Main Authors: Harlid, Sophia, Harbs, Justin, Myte, Robin, Brunius, Carl, Gunter, Marc J., Palmqvist, Richard, Liu, Xijia, Van Guelpen, Bethany
Format: Text
Language:English
Published: Nature Publishing Group UK 2021
Subjects:
Online Access:http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7933352/
http://www.ncbi.nlm.nih.gov/pubmed/33664295
https://doi.org/10.1038/s41598-021-83968-6
id ftpubmed:oai:pubmedcentral.nih.gov:7933352
record_format openpolar
spelling ftpubmed:oai:pubmedcentral.nih.gov:7933352 2023-05-15T17:44:43+02:00 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 2021-03-04 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7933352/ http://www.ncbi.nlm.nih.gov/pubmed/33664295 https://doi.org/10.1038/s41598-021-83968-6 en eng Nature Publishing Group UK http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7933352/ http://www.ncbi.nlm.nih.gov/pubmed/33664295 http://dx.doi.org/10.1038/s41598-021-83968-6 © 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/. CC-BY Sci Rep Article Text 2021 ftpubmed https://doi.org/10.1038/s41598-021-83968-6 2021-03-14T01:52:01Z 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. Text Northern Sweden PubMed Central (PMC) Scientific Reports 11 1
institution Open Polar
collection PubMed Central (PMC)
op_collection_id ftpubmed
language English
topic Article
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
topic_facet Article
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 Text
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
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 Publishing Group UK
publishDate 2021
url http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7933352/
http://www.ncbi.nlm.nih.gov/pubmed/33664295
https://doi.org/10.1038/s41598-021-83968-6
genre Northern Sweden
genre_facet Northern Sweden
op_source Sci Rep
op_relation http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7933352/
http://www.ncbi.nlm.nih.gov/pubmed/33664295
http://dx.doi.org/10.1038/s41598-021-83968-6
op_rights © 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/.
op_rightsnorm CC-BY
op_doi https://doi.org/10.1038/s41598-021-83968-6
container_title Scientific Reports
container_volume 11
container_issue 1
_version_ 1766146997845229568