Grading of endometrial cancer using 1H HR-MAS NMR-based metabolomics

Sci Rep. 2021 Sep 13;11(1):18160. doi: 10.1038/s41598-021-97505-y.

Abstract

The tissue metabolomic characteristics associated with endometrial cancer (EC) at different grades were studied using high resolution (400 MHz) magic angle spinning (HR-MAS) proton spectroscopy. The metabolic profiles were obtained from 64 patients (14 with grade 1 (G1), 33 with grade 2 (G2) and 17 with grade 3 (G3) tumors) and compared with the profile acquired from 10 patients with the benign disorders. OPLS-DA revealed increased valine, isoleucine, leucine, hypotaurine, serine, lysine, ethanolamine, choline and decreased creatine, creatinine, glutathione, ascorbate, glutamate, phosphoethanolamine and scyllo-inositol in all EC grades in reference to the non-transformed tissue. The increased levels of taurine was additionally detected in the G1 and G2 tumors in comparison to the control tissue, while the elevated glycine, N-acetyl compound and lactate-in the G1 and G3 tumors. The metabolic features typical for the G1 tumors are the increased dimethyl sulfone, phosphocholine, and decreased glycerophosphocholine and glutamine levels, while the decreased myo-inositol level is characteristic for the G2 and G3 tumors. The elevated 3-hydroxybutyrate, alanine and betaine levels were observed in the G3 tumors. The differences between the grade G1 and G3 malignances were mainly related to the perturbations of phosphoethanolamine and phosphocholine biosynthesis, inositol, betaine, serine and glycine metabolism. The statistical significance of the OPLS-DA modeling was also verified by an univariate analysis. HR-MAS NMR based metabolomics provides an useful insight into the metabolic reprogramming in endometrial cancer.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Cluster Analysis
  • Discriminant Analysis
  • Endometrial Neoplasms / diagnostic imaging*
  • Endometrial Neoplasms / metabolism*
  • Endometrium / pathology
  • Female
  • Humans
  • Least-Squares Analysis
  • Magnetic Resonance Spectroscopy*
  • Metabolic Networks and Pathways
  • Metabolome
  • Metabolomics*
  • Middle Aged
  • Models, Biological
  • Multivariate Analysis
  • Neoplasm Grading
  • Neoplasm Staging
  • Principal Component Analysis