Yanovich-Arad Gali, Ofek Paula, Yeini Eilam, Mardamshina Mariya, Danilevsky Artem, Shomron Noam, Grossman Rachel, Satchi-Fainaro Ronit, Geiger Tamar
Department of Human Molecular Genetics and Biochemistry, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.
Department of Physiology and Pharmacology, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.
Cell Rep. 2021 Mar 2;34(9):108787. doi: 10.1016/j.celrep.2021.108787.
Glioblastoma (GBM) is the most aggressive form of glioma, with poor prognosis exhibited by most patients, and a median survival time of less than 2 years. We assemble a cohort of 87 GBM patients whose survival ranges from less than 3 months and up to 10 years and perform both high-resolution mass spectrometry proteomics and RNA sequencing (RNA-seq). Integrative analysis of protein expression, RNA expression, and patient clinical information enables us to identify specific immune, metabolic, and developmental processes associated with survival as well as determine whether they are shared between expression layers or are layer specific. Our analyses reveal a stronger association between proteomic profiles and survival and identify unique protein-based classification, distinct from the established RNA-based classification. By integrating published single-cell RNA-seq data, we find a connection between subpopulations of GBM tumors and survival. Overall, our findings establish proteomic heterogeneity in GBM as a gateway to understanding poor survival.
胶质母细胞瘤（GBM）是最具侵袭性的胶质瘤形式，大多数患者预后较差，中位生存时间不到2年。我们收集了一组87例GBM患者，其生存期从不到3个月到10年不等，并进行了高分辨率质谱蛋白质组学和RNA测序（RNA-seq）。对蛋白质表达、RNA表达和患者临床信息的综合分析使我们能够识别与生存相关的特定免疫、代谢和发育过程，并确定它们是在表达层之间共享还是特定于某一层。我们的分析揭示了蛋白质组学图谱与生存之间更强的关联，并确定了独特的基于蛋白质的分类，这与已建立的基于RNA的分类不同。通过整合已发表的单细胞RNA-seq数据，我们发现GBM肿瘤亚群与生存之间存在联系。总体而言，我们的研究结果表明GBM中的蛋白质组异质性是理解生存不佳的一个切入点。
