TY - JOUR A1 - Conrad, Tim A1 - Leichtle, Alexander Benedikt A1 - Ceglarek, Uta A1 - Weinert, P. A1 - Nakas, C.T. A1 - Nuoffer, Jean-Marc A1 - Kase, Julia A1 - Witzigmann, Helmut A1 - Thiery, Joachim A1 - Fiedler, Georg Martin T1 - Pancreatic carcinoma, pancreatitis, and healthy controls - metabolite models in a three-class diagnostic dilemma JF - Metabolomics N2 - Background: 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 massspectrometric 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. Methods: 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.  Results: 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 [Volume under ROC surface (VUS) = 0.891 (95\% CI 0.794 - 0.968)]. Conclusions: We combined highly standardized samples, a three-class study design, a highthroughput 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. Y1 - 2013 U6 - https://doi.org/10.1007/s11306-012-0476-7 VL - 9 IS - 3 SP - 677 EP - 687 ER - TY - JOUR A1 - Fiedler, Georg Martin A1 - Leichtle, Alexander Benedikt A1 - Kase, Julia A1 - Baumann, Sven A1 - Ceglarek, Uta A1 - Felix, Klaus A1 - Conrad, Tim A1 - Witzigmann, Helmut A1 - Weimann, Arved A1 - Schütte, Christof A1 - Hauss, Johann A1 - Büchler, Markus A1 - Thiery, Joachim T1 - Serum Peptidome Profiling Revealed Platelet Factor 4 as a Potential Discriminating Peptide Associated With Pancreatic Cancer JF - Clinical Cancer Research Y1 - 2009 UR - http://publications.imp.fu-berlin.de/155/ U6 - https://doi.org/10.1158/1078-0432.CCR-08-2701 VL - 15 IS - 11 SP - 3812 EP - 3819 PB - American Association for Cancer Research, ER -