Journal Article

DKFZ-2020-01563

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Metabolic perturbations prior to hepatocellular carcinoma diagnosis - Findings from a prospective observational cohort study.

Stepien, M. ; Keski-Rahkonen, P. ; Kiss, A. ; Robinot, N. ; Duarte-Salles, T. ; Murphy, N. ; Perlemuter, G. ; Viallon, V. ; Tjønneland, A. ; Rostgaard-Hansen, A. L. ; Dahm, C. C. ; Overvad, K. ; Boutron-Ruault, M.-C. ; Mancini, F. R. ; Mahamat-Saleh, Y. ; Aleksandrova, K. ; Kaaks, R.DKFZ* ; Kühn, T.DKFZ* ; Trichopoulou, A. ; Karakatsani, A. ; Panico, S. ; Tumino, R. ; Palli, D. ; Tagliabue, G. ; Naccarati, A. ; Vermeulen, R. C. H. ; Bueno-de-Mesquita, H. B. ; Weiderpass, E. ; Skeie, G. ; Ramón Quirós, J. ; Ardanaz, E. ; Mokoroa, O. ; Sala, N. ; Sánchez, M.-J. ; Huerta, J. M. ; Winkvist, A. ; Harlid, S. ; Ohlsson, B. ; Sjöberg, K. ; Schmidt, J. A. ; Wareham, N. ; Khaw, K.-T. ; Ferrari, P. ; Rothwell, J. A. ; Gunter, M. ; Riboli, E. ; Scalbert, A. ; Jenab, M.

2020
Wiley-Liss Bognor Regis

This record in other databases:  

Please use a persistent id in citations: doi:10.1002/ijc.33236

Abstract: Hepatocellular carcinoma (HCC) development entails changes in liver metabolism. Current knowledge on metabolic perturbations in HCC is derived mostly from case-control designs, with sparse information from prospective cohorts. Our objective was to apply comprehensive metabolite profiling to detect metabolites whose serum concentrations are associated with HCC development, using biological samples from within the prospective EPIC cohort (>520 000 participants,), where we identified 129 HCC cases matched 1:1 to controls. We conducted high resolution untargeted liquid chromatography-mass spectrometry based metabolomics on serum samples collected at recruitment prior to cancer diagnosis. Multivariable conditional logistic regression was applied controlling for dietary habits, alcohol consumption, smoking, body size, hepatitis infection and liver dysfunction. Corrections for multiple comparisons were applied. Of 9206 molecular features detected, 220 discriminated HCC cases from controls. Detailed feature annotation revealed 92 metabolites associated with HCC risk; 14 of which were unambiguously identified using pure reference standards. Positive HCC risk associations were observed for N1-acetylspermidine, isatin, p-hydroxyphenyllactic acid, tyrosine, sphingosine, L,L-cyclo(leucylprolyl), glycochenodeoxycholic acid, glycocholic acid, and 7-methylguanine. Inverse risk associations were observed for retinol, dehydroepiandrosterone sulfate, glycerophosphocholine, γ-carboxyethyl hydroxychroman, and creatine. Discernible differences for these metabolites were observed between cases and controls up to 10 years prior to diagnosis. Our observations highlight the diversity of metabolic perturbations involved in HCC development and replicate previous observations (metabolism of bile acids, amino acids, phospholipids) made in Asian and Scandinavian populations. These findings emphasize the role of metabolic pathways associated with steroid metabolism and immunity and specific dietary and environmental exposures in HCC development. This article is protected by copyright. All rights reserved.

Note: 2021 Feb 1;148(3):609-625

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Contributing Institute(s):

1. C020 Epidemiologie von Krebs (C020)

Research Program(s):

1. 313 - Cancer risk factors and prevention (POF3-313) (POF3-313)

Appears in the scientific report 2020

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Database coverage:
; BIOSIS Previews ; Biological Abstracts ; Clarivate Analytics Master Journal List ; Current Contents - Life Sciences ; DEAL Wiley ; Essential Science Indicators ; IF < 5 ; JCR ; NCBI Molecular Biology Database ; Nationallizenz ; SCOPUS ; Science Citation Index ; Science Citation Index Expanded ; Web of Science Core Collection

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