| Autor: |
Rochelle C. J. D’Souza, Carolin Offenhäuser, Jasmin Straube, Ulrich Baumgartner, Anja Kordowski, Yuchen Li, Brett W. Stringer, Hamish Alexander, Zarnie Lwin, Po-Ling Inglis, Rosalind L. Jeffree, Terrance G. Johns, Andrew W. Boyd, Bryan W. Day |
| Jazyk: |
angličtina |
| Rok vydání: |
2020 |
| Předmět: |
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| Zdroj: |
Cells, Vol 9, Iss 2, p 267 (2020) |
| Druh dokumentu: |
article |
| ISSN: |
2073-4409 |
| DOI: |
10.3390/cells9020267 |
| Popis: |
Glioblastoma (GBM) is a treatment-refractory central nervous system (CNS) tumour, and better therapies to treat this aggressive disease are urgently needed. Primary GBM models that represent the true disease state are essential to better understand disease biology and for accurate preclinical therapy assessment. We have previously presented a comprehensive transcriptome characterisation of a panel (n = 12) of primary GBM models (Q-Cell). We have now generated a systematic, quantitative, and deep proteome abundance atlas of the Q-Cell models grown in 3D culture, representing 6167 human proteins. A recent study has highlighted the degree of functional heterogeneity that coexists within individual GBM tumours, describing four cellular states (MES-like, NPC-like, OPC-like and AC-like). We performed comparative proteomic analysis, confirming a good representation of each of the four cell-states across the 13 models examined. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis identified upregulation of a number of GBM-associated cancer pathway proteins. Bioinformatics analysis, using the OncoKB database, identified a number of functional actionable targets that were either uniquely or ubiquitously expressed across the panel. This study provides an in-depth proteomic analysis of the GBM Q-Cell resource, which should prove a valuable functional dataset for future biological and preclinical investigations. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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