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Large Scale Identification of Variant Proteins in Glioma Stem Cells

Mostovenko, Ekaterina; Végvári, Ákos LU ; Rezeli, Melinda LU ; Lichti, Cheryl F.; Fenyö, David; Wang, Qianghu; Lang, Frederick F.; Sulman, Erik P.; Sahlin, K. Barbara LU and Marko-Varga, György LU , et al. (2018) In ACS Chemical Neuroscience 9(1). p.73-79
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... (More)

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.

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publication status
published
subject
keywords
bioinformatics, GBM, Glioblastoma, parallel reaction monitoring, precision medicine, protein quantification, protein single amino acid variants, proteomics, targeted mass spectrometry, transcriptomics
in
ACS Chemical Neuroscience
volume
9
issue
1
pages
7 pages
publisher
The American Chemical Society
external identifiers
  • scopus:85040656011
ISSN
1948-7193
DOI
10.1021/acschemneuro.7b00362
language
English
LU publication?
yes
id
0dc6eb8e-a269-414a-ba66-8ccadb59adcf
date added to LUP
2018-01-30 11:12:14
date last changed
2018-05-29 12:23:02
@article{0dc6eb8e-a269-414a-ba66-8ccadb59adcf,
  abstract     = {<p>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.</p>},
  author       = {Mostovenko, Ekaterina and Végvári, Ákos and Rezeli, Melinda and Lichti, Cheryl F. and Fenyö, David and Wang, Qianghu and Lang, Frederick F. and Sulman, Erik P. and Sahlin, K. Barbara and Marko-Varga, György and Nilsson, Carol L.},
  issn         = {1948-7193},
  keyword      = {bioinformatics,GBM,Glioblastoma,parallel reaction monitoring,precision medicine,protein quantification,protein single amino acid variants,proteomics,targeted mass spectrometry,transcriptomics},
  language     = {eng},
  month        = {01},
  number       = {1},
  pages        = {73--79},
  publisher    = {The American Chemical Society},
  series       = {ACS Chemical Neuroscience},
  title        = {Large Scale Identification of Variant Proteins in Glioma Stem Cells},
  url          = {http://dx.doi.org/10.1021/acschemneuro.7b00362},
  volume       = {9},
  year         = {2018},
}