Metabolomics for early pancreatic cancer detection in plasma samples from a Swedish prospective population-based biobank
Background: Pancreatic ductal adenocarcinoma (pancreatic cancer) is often detected at late stages resulting in poor overall survival. To improve survival, more patients need to be diagnosed early when curative surgery is feasible. We aimed to identify circulating metabolites that could be used as ea...
Published in: | Journal of Gastrointestinal Oncology |
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Högskolan i Skövde, Institutionen för biovetenskap
2024
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Online Access: | http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-23791 https://doi.org/10.21037/jgo-23-930 |
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ftskoevdehoeg:oai:DiVA.org:his-23791 2024-06-02T08:12:14+00:00 Metabolomics for early pancreatic cancer detection in plasma samples from a Swedish prospective population-based biobank Borgmästars, Emmy Jacobson, Sara Simm, Maja Johansson, Mattias Billing, Ola Lundin, Christina Nyström, Hanna Öhlund, Daniel Lubovac-Pilav, Zelmina Jonsson, Pär Franklin, Oskar Sund, Malin 2024 application/pdf http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-23791 https://doi.org/10.21037/jgo-23-930 eng eng Högskolan i Skövde, Institutionen för biovetenskap Högskolan i Skövde, Forskningsmiljön Systembiologi Department of Surgical and Perioperative Sciences/Surgery, UmeÃ¥ University, Sweden Department of Clinical Sciences/Obstetrics and Gynecology, UmeaÌŠ University, Sweden Genomic Epidemiology Branch, International Agency for Research on Cancer, Lyon, France Wallenberg Centre for Molecular Medicine, UmeaÌŠ University, Sweden Department of Radiation Sciences/Oncology, UmeaÌŠ University, Sweden Department of Chemistry, UmeaÌŠ University, Sweden Division of Surgical Oncology, Department of Surgery, University of Colorado School of Medicine, Aurora, CO, USA Department of Surgery, University of Helsinki and Helsinki University Hospital, Finland AME Publishing Company Journal of Gastrointestinal Oncology, 2078-6891, 2024, 15:2, s. 755-767 orcid:0000-0001-6427-0315 http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-23791 doi:10.21037/jgo-23-930 info:eu-repo/semantics/openAccess Cancer and Oncology Cancer och onkologi Article in journal info:eu-repo/semantics/article text 2024 ftskoevdehoeg https://doi.org/10.21037/jgo-23-930 2024-05-07T23:38:21Z Background: Pancreatic ductal adenocarcinoma (pancreatic cancer) is often detected at late stages resulting in poor overall survival. To improve survival, more patients need to be diagnosed early when curative surgery is feasible. We aimed to identify circulating metabolites that could be used as early pancreatic cancer biomarkers. Methods: We performed metabolomics by liquid and gas chromatography-mass spectrometry in plasma samples from 82 future pancreatic cancer patients and 82 matched healthy controls within the Northern Sweden Health and Disease Study (NSHDS). Logistic regression was used to assess univariate associations between metabolites and pancreatic cancer risk. Least absolute shrinkage and selection operator (LASSO) logistic regression was used to design a metabolite-based risk score. We used receiver operating characteristic (ROC) analyses to assess the discriminative performance of the metabolite-based risk score. Results: Among twelve risk-associated metabolites with a nominal P value <0.05, we defined a risk score of three metabolites [indoleacetate, 3-hydroxydecanoate (10:0-OH), and retention index (RI): 2,745.4] using LASSO. A logistic regression model containing these three metabolites, age, sex, body mass index (BMI), smoking status, sample date, fasting status, and carbohydrate antigen 19-9 (CA 19-9) yielded an internal area under curve (AUC) of 0.784 [95% confidence interval (CI): 0.714–0.854] compared to 0.681 (95% CI: 0.597–0.764) for a model without these metabolites (P value =0.007). Seventeen metabolites were significantly associated with pancreatic cancer survival [false discovery rate (FDR) <0.1]. Conclusions: Indoleacetate, 3-hydroxydecanoate (10:0-OH), and RI: 2,745.4 were identified as the top candidate biomarkers for early detection. However, continued efforts are warranted to determine the usefulness of these metabolites as early pancreatic cancer biomarkers. CC BY-NC-ND 4.0 DEED Correspondence to: Emmy Borgmästars, PhD. Department of Surgical and Perioperative ... Article in Journal/Newspaper Northern Sweden University of Skövde: Publications (DiVA) Journal of Gastrointestinal Oncology 15 2 755 767 |
institution |
Open Polar |
collection |
University of Skövde: Publications (DiVA) |
op_collection_id |
ftskoevdehoeg |
language |
English |
topic |
Cancer and Oncology Cancer och onkologi |
spellingShingle |
Cancer and Oncology Cancer och onkologi Borgmästars, Emmy Jacobson, Sara Simm, Maja Johansson, Mattias Billing, Ola Lundin, Christina Nyström, Hanna Öhlund, Daniel Lubovac-Pilav, Zelmina Jonsson, Pär Franklin, Oskar Sund, Malin Metabolomics for early pancreatic cancer detection in plasma samples from a Swedish prospective population-based biobank |
topic_facet |
Cancer and Oncology Cancer och onkologi |
description |
Background: Pancreatic ductal adenocarcinoma (pancreatic cancer) is often detected at late stages resulting in poor overall survival. To improve survival, more patients need to be diagnosed early when curative surgery is feasible. We aimed to identify circulating metabolites that could be used as early pancreatic cancer biomarkers. Methods: We performed metabolomics by liquid and gas chromatography-mass spectrometry in plasma samples from 82 future pancreatic cancer patients and 82 matched healthy controls within the Northern Sweden Health and Disease Study (NSHDS). Logistic regression was used to assess univariate associations between metabolites and pancreatic cancer risk. Least absolute shrinkage and selection operator (LASSO) logistic regression was used to design a metabolite-based risk score. We used receiver operating characteristic (ROC) analyses to assess the discriminative performance of the metabolite-based risk score. Results: Among twelve risk-associated metabolites with a nominal P value <0.05, we defined a risk score of three metabolites [indoleacetate, 3-hydroxydecanoate (10:0-OH), and retention index (RI): 2,745.4] using LASSO. A logistic regression model containing these three metabolites, age, sex, body mass index (BMI), smoking status, sample date, fasting status, and carbohydrate antigen 19-9 (CA 19-9) yielded an internal area under curve (AUC) of 0.784 [95% confidence interval (CI): 0.714–0.854] compared to 0.681 (95% CI: 0.597–0.764) for a model without these metabolites (P value =0.007). Seventeen metabolites were significantly associated with pancreatic cancer survival [false discovery rate (FDR) <0.1]. Conclusions: Indoleacetate, 3-hydroxydecanoate (10:0-OH), and RI: 2,745.4 were identified as the top candidate biomarkers for early detection. However, continued efforts are warranted to determine the usefulness of these metabolites as early pancreatic cancer biomarkers. CC BY-NC-ND 4.0 DEED Correspondence to: Emmy Borgmästars, PhD. Department of Surgical and Perioperative ... |
format |
Article in Journal/Newspaper |
author |
Borgmästars, Emmy Jacobson, Sara Simm, Maja Johansson, Mattias Billing, Ola Lundin, Christina Nyström, Hanna Öhlund, Daniel Lubovac-Pilav, Zelmina Jonsson, Pär Franklin, Oskar Sund, Malin |
author_facet |
Borgmästars, Emmy Jacobson, Sara Simm, Maja Johansson, Mattias Billing, Ola Lundin, Christina Nyström, Hanna Öhlund, Daniel Lubovac-Pilav, Zelmina Jonsson, Pär Franklin, Oskar Sund, Malin |
author_sort |
Borgmästars, Emmy |
title |
Metabolomics for early pancreatic cancer detection in plasma samples from a Swedish prospective population-based biobank |
title_short |
Metabolomics for early pancreatic cancer detection in plasma samples from a Swedish prospective population-based biobank |
title_full |
Metabolomics for early pancreatic cancer detection in plasma samples from a Swedish prospective population-based biobank |
title_fullStr |
Metabolomics for early pancreatic cancer detection in plasma samples from a Swedish prospective population-based biobank |
title_full_unstemmed |
Metabolomics for early pancreatic cancer detection in plasma samples from a Swedish prospective population-based biobank |
title_sort |
metabolomics for early pancreatic cancer detection in plasma samples from a swedish prospective population-based biobank |
publisher |
Högskolan i Skövde, Institutionen för biovetenskap |
publishDate |
2024 |
url |
http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-23791 https://doi.org/10.21037/jgo-23-930 |
genre |
Northern Sweden |
genre_facet |
Northern Sweden |
op_relation |
Journal of Gastrointestinal Oncology, 2078-6891, 2024, 15:2, s. 755-767 orcid:0000-0001-6427-0315 http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-23791 doi:10.21037/jgo-23-930 |
op_rights |
info:eu-repo/semantics/openAccess |
op_doi |
https://doi.org/10.21037/jgo-23-930 |
container_title |
Journal of Gastrointestinal Oncology |
container_volume |
15 |
container_issue |
2 |
container_start_page |
755 |
op_container_end_page |
767 |
_version_ |
1800758614006169600 |