Correlations between the metabolic profile and 18F-FDG-Positron Emission Tomography-Computed Tomography parameters reveal the complexity of the metabolic reprogramming within lung cancer patients
Open Access
- 7 November 2019
- journal article
- research article
- Published by Springer Nature in Scientific Reports
- Vol. 9 (1) , 1-11
Abstract
Several studies have demonstrated that the metabolite composition of plasma may indicate the presence of lung cancer. The metabolism of cancer is characterized by an enhanced glucose uptake and glycolysis which is exploited by 18F-FDG positron emission tomography (PET) in the work-up and management of cancer. This study aims to explore relationships between 1H-NMR spectroscopy derived plasma metabolite concentrations and the uptake of labeled glucose (18F-FDG) in lung cancer tissue. PET parameters of interest are standard maximal uptake values (SUVmax), total body metabolic active tumor volumes (MATVWTB) and total body total lesion glycolysis (TLGWTB) values. Patients with high values of these parameters have higher plasma concentrations of N-acetylated glycoproteins which suggest an upregulation of the hexosamines biosynthesis. High MATVWTB and TLGWTB values are associated with higher concentrations of glucose, glycerol, N-acetylated glycoproteins, threonine, aspartate and valine and lower levels of sphingomyelins and phosphatidylcholines appearing at the surface of lipoproteins. These higher concentrations of glucose and non-carbohydrate glucose precursors such as amino acids and glycerol suggests involvement of the gluconeogenesis pathway. The lower plasma concentration of those phospholipids points to a higher need for membrane synthesis. Our results indicate that the metabolic reprogramming in cancer is more complex than the initially described Warburg effect.Keywords
This publication has 71 references indexed in Scilit:
- A Review of Applications of Metabolomics in CancerMetabolites, 2013
- 1H-NMR based metabonomic profiling of human esophageal cancer tissueMolecular Cancer, 2013
- Prognostic Significance of Volume-Based PET Parameters in Cancer PatientsKorean Journal of Radiology, 2013
- Applications of metabolomics in cancer researchJournal of Carcinogenesis, 2013
- Study on metabonomic characteristics of human lung cancer using high resolution magic‐angle spinning 1H NMR spectroscopy and multivariate data analysisMagnetic Resonance in Medicine, 2011
- Hallmarks of Cancer: The Next GenerationCell, 2011
- Enhancing metabolomic data analysis with Progressive Consensus Alignment of NMR Spectra (PCANS)BMC Bioinformatics, 2010
- Q's next: the diverse functions of glutamine in metabolism, cell biology and cancerOncogene, 2009
- 'Metabonomics': understanding the metabolic responses of living systems to pathophysiological stimuli via multivariate statistical analysis of biological NMR spectroscopic dataXenobiotica, 1999
- On the Origin of Cancer CellsScience, 1956