| Literature DB >> 29254333 |
Ekaterina Mostovenko1, Ákos Végvári2, Melinda Rezeli2, Cheryl F Lichti1,3, David Fenyö4, Qianghu Wang, Frederick F Lang, Erik P Sulman, K Barbara Sahlin2, György Marko-Varga2, Carol L Nilsson5.
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.Entities:
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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Year: 2017 PMID: 29254333 PMCID: PMC6008157 DOI: 10.1021/acschemneuro.7b00362
Source DB: PubMed Journal: ACS Chem Neurosci ISSN: 1948-7193 Impact factor: 4.418