Pancreatic carcinoma, pancreatitis, and healthy controls: metabolite models in a three-class diagnostic dilemma

Leichtle, Alexander Benedikt; Ceglarek, U; Weinert, P; Nakas, C T; Nuoffer, Jean-Marc; Kase, J; Conrad, T; Witzigmann, H; Thiery, J; Fiedler, Martin (2013). Pancreatic carcinoma, pancreatitis, and healthy controls: metabolite models in a three-class diagnostic dilemma. Metabolomics, 9(3), pp. 677-687. New York, N.Y.: Springer US; 10.1007/s11306-012-0476-7

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Metabolomics as one of the most rapidly growing technologies in the "-omics" field denotes the comprehensive analysis of low molecular-weight compounds and their pathways. Cancer-specific alterations of the metabolome can be detected by high-throughput mass-spectrometric metabolite profiling and serve as a considerable source of new markers for the early differentiation of malignant diseases as well as their distinction from benign states. However, a comprehensive framework for the statistical evaluation of marker panels in a multi-class setting has not yet been established. We collected serum samples of 40 pancreatic carcinoma patients, 40 controls, and 23 pancreatitis patients according to standard protocols and generated amino acid profiles by routine mass-spectrometry. In an intrinsic three-class bioinformatic approach we compared these profiles, evaluated their selectivity and computed multi-marker panels combined with the conventional tumor marker CA 19-9. Additionally, we tested for non-inferiority and superiority to determine the diagnostic surplus value of our multi-metabolite marker panels. Compared to CA 19-9 alone, the combined amino acid-based metabolite panel had a superior selectivity for the discrimination of healthy controls, pancreatitis, and pancreatic carcinoma patients [Formula: see text] We combined highly standardized samples, a three-class study design, a high-throughput mass-spectrometric technique, and a comprehensive bioinformatic framework to identify metabolite panels selective for all three groups in a single approach. Our results suggest that metabolomic profiling necessitates appropriate evaluation strategies and-despite all its current limitations-can deliver marker panels with high selectivity even in multi-class settings.

Item Type:

Journal Article (Original Article)


04 Faculty of Medicine > Department of Haematology, Oncology, Infectious Diseases, Laboratory Medicine and Hospital Pharmacy (DOLS) > Institute of Clinical Chemistry
04 Faculty of Medicine > Department of Gynaecology, Paediatrics and Endocrinology (DFKE) > Clinic of Paediatric Medicine

UniBE Contributor:

Leichtle, Alexander Benedikt; Nuoffer, Jean-Marc and Fiedler, Martin


600 Technology > 610 Medicine & health




1573-3882 (Print)


Springer US;




Anette van Dorland

Date Deposited:

04 Oct 2013 14:41

Last Modified:

20 Jul 2022 10:02

Publisher DOI:


PubMed ID:


Web of Science ID:


Additional Information:

Leichtle, Alexander Benedikt;Ceglarek, Uta;Weinert, Peter;Nakas, Christos T;Nuoffer, Jean-Marc;Kase, Julia;Conrad, Tim;Witzigmann, Helmut;Thiery, Joachim;Fiedler, Georg Martin;Metabolomics. 2013 Jun;9(3):677-687. Epub 2012 Nov 6.



URI: (FactScience: 224213)

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