Untargeted metabolomics reveals major differences in the plasma metabolome between colorectal cancer and colorectal adenomas

Sporadic colorectal cancer is characterized by a multistep progression from normal epithelium to precancerous low-risk and high-risk adenomas to invasive cancer. Yet, the underlying molecular mechanisms of colorectal carcinogenesis are not completely understood. Within the “Metabolomic profiles thro...

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Main Authors: Gumpenberger, Tanja (Author) , Brezina, Stefanie (Author) , Keski-Rahkonen, Pekka (Author) , Baierl, Andreas (Author) , Robinot, Nivonirina (Author) , Leeb, Gernot (Author) , Habermann, Nina (Author) , Kok, Dieuwertje E. G. (Author) , Scalbert, Augustin (Author) , Ueland, Per-Magne (Author) , Ulrich, Cornelia M. (Author) , Gsur, Andrea (Author)
Format: Article (Journal)
Language:English
Published: 19 February 2021
In: Metabolites
Year: 2021, Volume: 11, Issue: 2, Pages: 1-13
ISSN:2218-1989
DOI:10.3390/metabo11020119
Online Access:Verlag, lizenzpflichtig, Volltext: https://doi.org/10.3390/metabo11020119
Verlag, lizenzpflichtig, Volltext: https://www.mdpi.com/2218-1989/11/2/119
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Author Notes:Tanja Gumpenberger, Stefanie Brezina, Pekka Keski-Rahkonen, Andreas Baierl, Nivonirina Robinot, Gernot Leeb, Nina Habermann, Dieuwertje E.G. Kok, Augustin Scalbert, Per-Magne Ueland, Cornelia M. Ulrich and Andrea Gsur

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520 |a Sporadic colorectal cancer is characterized by a multistep progression from normal epithelium to precancerous low-risk and high-risk adenomas to invasive cancer. Yet, the underlying molecular mechanisms of colorectal carcinogenesis are not completely understood. Within the “Metabolomic profiles throughout the continuum of colorectal cancer” (MetaboCCC) consortium we analyzed data generated by untargeted, mass spectrometry-based metabolomics using plasma from 88 colorectal cancer patients, 200 patients with high-risk adenomas and 200 patients with low-risk adenomas recruited within the “Colorectal Cancer Study of Austria” (CORSA). Univariate logistic regression models comparing colorectal cancer to adenomas resulted in 442 statistically significant molecular features. Metabolites discriminating colorectal cancer patients from those with adenomas in our dataset included acylcarnitines, caffeine, amino acids, glycerophospholipids, fatty acids, bilirubin, bile acids and bacterial metabolites of tryptophan. The data obtained discovers metabolite profiles reflecting metabolic differences between colorectal cancer and colorectal adenomas and delineates a potentially underlying biological interpretation. 
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