Search for Early Pancreatic Cancer Blood Biomarkers in Five European Prospective Population Biobanks Using Metabolomics

Author:

Fest Jesse12,Vijfhuizen Lisanne S3,Goeman Jelle J4,Veth Olga3ORCID,Joensuu Anni56ORCID,Perola Markus56,Männistö Satu5,Ness-Jensen Eivind7ORCID,Hveem Kristian7,Haller Toomas8ORCID,Tonisson Neeme89,Mikkel Kairit8,Metspalu Andres8ORCID,van Duijn Cornelia M2,Ikram Arfan2,Stricker Bruno H2,Ruiter Rikje2,van Eijck Casper H J1,van Ommen Gert-Jan B3ORCID,ʼt Hoen Peter A C310ORCID

Affiliation:

1. Department of Surgery, Erasmus Medical Center, Rotterdam, Netherlands

2. Department of Epidemiology, Erasmus Medical Center, Rotterdam, Netherlands

3. Department of Human Genetics, Leiden University Medical Center, Leiden, Netherlands

4. Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, Netherlands

5. Department of Public Health Solutions, National Institute for Health and Welfare, Helsinki, Finland

6. Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland

7. HUNT Research Center, Department of Public Health and Nursing, Norwegian University of Science and Technology, Levanger, Norway

8. Institute of Genomics, University of Tartu, Tartu, Estonia

9. Department of Clinical Genetics, Tartu University Hospital, Tartu, Estonia

10. Center for Molecular and Biomolecular Informatics, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Nijmegen, Netherlands

Abstract

Abstract Most patients with pancreatic cancer present with advanced disease and die within the first year after diagnosis. Predictive biomarkers that signal the presence of pancreatic cancer in an early stage are desperately needed. We aimed to identify new and validate previously found plasma metabolomic biomarkers associated with early stages of pancreatic cancer. Prediagnostic blood samples from individuals who were to receive a diagnosis of pancreatic cancer between 1 month and 17 years after sampling (N = 356) and age- and sex-matched controls (N = 887) were collected from five large population cohorts (HUNT2, HUNT3, FINRISK, Estonian Biobank, Rotterdam Study). We applied proton nuclear magnetic resonance–based metabolomics on the Nightingale platform. Logistic regression identified two interesting hits: glutamine (P = 0.011) and histidine (P = 0.012), with Westfall–Young family-wise error rate adjusted P values of 0.43 for both. Stratification in quintiles showed a 1.5-fold elevated risk for the lowest 20% of glutamine and a 2.2-fold increased risk for the lowest 20% of histidine. Stratification by time to diagnosis suggested glutamine to be involved in an earlier process (2 to 5 years before diagnosis), and histidine in a process closer to the actual onset (<2 years). Our data did not support the branched-chain amino acids identified earlier in several US cohorts as potential biomarkers for pancreatic cancer. Thus, although we identified glutamine and histidine as potential biomarkers of biological interest, our results imply that a study at this scale does not yield metabolomic biomarkers with sufficient predictive value to be clinically useful per se as prognostic biomarkers.

Funder

FP7 Research infrastructures

H2020 Research Infrastructures

Finnish Academy

Yrjö Jahnssonin Säätiö

Horizon 2020 Framework Programme

Estonian Government

European Regional Development Fund

National Institutes of Health

Publisher

The Endocrine Society

Subject

Endocrinology

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