OBJECTIVES: To develop a noninvasive and accessible diagnostic method for pancreatic cancer (PC). DESIGN AND METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.
OBJECTIVES: To develop a noninvasive and accessible diagnostic method for pancreatic cancer (PC). DESIGN AND METHODS: 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. RESULTS: 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 CPpatients and healthy individuals. CONCLUSIONS: 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.
Authors: Vijayasarathy Ketavarapu; Vishnubhotla Ravikanth; Mitnala Sasikala; G V Rao; Ch Venkataramana Devi; Prabhakar Sripadi; Murali Satyanarayana Bethu; Ramars Amanchy; H V V Murthy; Stephen J Pandol; D Nageshwar Reddy Journal: BMC Cancer Date: 2022-07-19 Impact factor: 4.638
Authors: Alexander Benedikt Leichtle; Uta Ceglarek; Peter Weinert; Christos T Nakas; Jean-Marc Nuoffer; Julia Kase; Tim Conrad; Helmut Witzigmann; Joachim Thiery; Georg Martin Fiedler Journal: Metabolomics Date: 2012-11-06 Impact factor: 4.290
Authors: Jun Kou; Chunyang He; Lin Cui; Zhengping Zhang; Wei Wang; Li Tan; Da Liu; Wei Zheng; Wei Gu; Ning Xia Journal: Front Endocrinol (Lausanne) Date: 2022-04-19 Impact factor: 6.055