Distinguishing pancreatic cancer from chronic pancreatitis and healthy individuals by (1)H nuclear magnetic resonance-based metabonomic profiles.

To develop a noninvasive and accessible diagnostic method for pancreatic cancer (PC). We presented a metabolomic method, pattern recognition techniques applied to (1)H nuclear magnetic resonance ((1)H NMR) spectra, to investigate the plasma metabolites obtained from 19 patients with PC, 20 patients with chronic pancreatitis (CP) and 20 healthy individuals. Metabolic changes associated with PC included abnormal amino acid and lipid metabolism, and possible multiple metabolic syndrome. PC elevated plasma levels of N-acetyl glycoprotein (NAG), dimethylamine (DMA), very low density lipoprotein (VLDL), and acetone, and reduced levels of 3-hydroxybutyrate, lactate, high density lipoprotein (HDL), low density lipoprotein (LDL), citrate, alanine, glutamate, glutamine, histidine, isoleucine, lysine, and valine. These metabolites could be a biomarker group for PC that distinguishes between PC and CP patients and healthy individuals. NMR-based metabonomic strategy appears as a promising approach for distinguishing pancreatic cancer and identifying new strategies for prevention or therapy in the clinical practice.