Mass spectrometry, data re-analysis, and homology modelling predict posttranslational modifications of leucine-rich alpha-2-glycoprotein as a marker of myelodysplastic syndrome

Cancer Biomark. 2022;34(3):485-492. doi: 10.3233/CBM-210033.

Abstract

Background: Leucine-rich alpha-2-glycoprotein (LRG) has been repeatedly proposed as a potential plasma biomarker for myelodysplastic syndrome (MDS).

Objective: The goal of our work was to establish the total LRG plasma level and LRG posttranslational modifications (PTMs) as a suitable MDS biomarker.

Methods: The total plasma LRG concentration was determined with ELISA, whilst the LRG-specific PTMs and their locations, were established using mass spectrometry and public mass spectrometry data re-analysis. Homology modelling and sequence analysis were used to establish the potential impact of PTMs on LRG functions via their impact on the LRG structure.

Results: While the results showed that the total LRG plasma concentration is not a suitable MDS marker, alterations within two LRG sites correlated with MDS diagnosis (p= 0.0011). Sequence analysis and the homology model suggest the influence of PTMs within the two LRG sites on the function of this protein.

Conclusions: We report the presence of LRG proteoforms that correlate with diagnosis in the plasma of MDS patients. The combination of mass spectrometry, re-analysis of publicly available data, and homology modelling, represents an approach that can be used for any protein to predict clinically relevant protein sites for biomarker research despite the character of the PTMs being unknown.

Keywords: LRG; MDS; Myelodysplastic syndrome; leucine-rich alpha-2-glycoprotein; proteomics.

MeSH terms

  • Biomarkers
  • Glycoproteins* / genetics
  • Glycoproteins* / metabolism
  • Humans
  • Leucine / metabolism
  • Mass Spectrometry
  • Myelodysplastic Syndromes* / diagnosis
  • Protein Processing, Post-Translational

Substances

  • Biomarkers
  • Glycoproteins
  • Leucine