Q-Cell Glioblastoma Resource: Proteomics Analysis Reveals Unique Cell-States Are Maintained in 3D Culture
Q-Cell Glioblastoma Resource: Proteomics Analysis Reveals Unique Cell-States Are Maintained in 3D Culture
复制标题
DOI：
10.3390/cells9020267
复制
发表时间：
2020-02-01
期刊：
影响因子：
6
通讯作者：
Day, Bryan W.
中科院分区：
文献类型：
--
作者：
D'Souza, Rochelle C. J.;Offenhauser, Carolin;Day, Bryan W.
胶质母细胞瘤（GBM）是一种难以治疗的中枢神经系统（CNS）肿瘤，迫切需要更好的治疗方法来治疗这种侵袭性疾病。代表真实疾病状态的原发性GBM模型对于更好地理解疾病生物学和准确的临床前治疗评估至关重要。我们之前提出了一组（n = 12）原发性GBM模型（Q-Cell）的综合转录组特征。我们现在已经在3D培养中生成了Q-Cell模型的系统、定量和深度蛋白质组丰度图谱，代表了6167种人类蛋白质。最近的一项研究强调了单个GBM肿瘤中共存的功能异质性程度，描述了四种细胞状态（mes样、npc样、opc样和ac样）。我们进行了比较蛋白质组学分析，证实了13种模型中四种细胞状态的良好代表。京都基因和基因组百科全书（KEGG）途径分析发现了一些gbm相关的癌症途径蛋白的上调。生物信息学分析，使用OncoKB数据库，确定了许多功能性可操作的目标，这些目标要么是唯一的，要么是在整个面板中普遍表达的。这项研究为GBM Q-Cell资源提供了深入的蛋白质组学分析，这将为未来的生物学和临床前研究提供有价值的功能数据集。
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.