November 12, 2014
Notes: Ledder, Oren D
Lemberg, Daniel A
Ooi, Chee Y
Day, Andrew S
J Pediatr Gastroenterol Nutr. 2013 Nov;57(5):583-6. doi: 10.1097/MPG.0b013e31829f16fc.
Author Address: *Department of Pediatric Gastroenterology, Shaare Zedek Medical Centre, Jerusalem, Israel daggerDepartment of Gastroenterology, Sydney Children’s Hospital, Sydney, Australia.
Reference Type: Journal Article
Record Number: 5237Author: Leichtle, A. B., Ceglarek, U., Weinert, P., Nakas, C. T., Nuoffer, J. M., Kase, J., Conrad, T., Witzigmann, H., Thiery, J. and Fiedler, G. M.
Title: Pancreatic carcinoma, pancreatitis, and healthy controls: metabolite models in a three-class diagnostic dilemma
Short Title: Pancreatic carcinoma, pancreatitis, and healthy controls: metabolite models in a three-class diagnostic dilemma
Alternate Journal: Metabolomics : Official journal of the Metabolomic Society
ISSN: 1573-3882 (Print)
Accession Number: 23678345
Abstract: 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.