Large Scale Identification of Variant Proteins in Glioma Stem Cells

  • Ekaterina Mostovenko
  • , Ákos Végvári
  • , Melinda Rezeli
  • , Cheryl F. Lichti
  • , David Fenyö
  • , Qianghu Wang
  • , Frederick F. Lang
  • , Erik P. Sulman
  • , K. Barbara Sahlin
  • , György Marko-Varga
  • , Carol L. Nilsson

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

Abstract

Glioblastoma (GBM), the most malignant of primary brain tumors, is a devastating and deadly disease, with a median survival of 14 months from diagnosis, despite standard regimens of radical brain tumor surgery, maximal safe radiation, and concomitant chemotherapy. GBM tumors nearly always re-emerge after initial treatment and frequently display resistance to current treatments. One theory that may explain GBM re-emergence is the existence of glioma stemlike cells (GSCs). We sought to identify variant protein features expressed in low passage GSCs derived from patient tumors. To this end, we developed a proteomic database that reflected variant and nonvariant sequences in the human proteome, and applied a novel retrograde proteomic workflow, to identify and validate the expression of 126 protein variants in 33 glioma stem cell strains. These newly identified proteins may harbor a subset of novel protein targets for future development of GBM therapy.

Original languageEnglish
Pages (from-to)73-79
Number of pages7
JournalACS Chemical Neuroscience
Volume9
Issue number1
DOIs
StatePublished - Jan 17 2018

Keywords

  • GBM
  • Glioblastoma
  • bioinformatics
  • parallel reaction monitoring
  • precision medicine
  • protein quantification
  • protein single amino acid variants
  • proteomics
  • targeted mass spectrometry
  • transcriptomics

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