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Integrated pharmaco-proteogenomics defines two subgroups in isocitrate dehydrogenase wild-type glioblastoma with prognostic and therapeutic opportunities

Authors
Oh, SejinYeom, JeonghunCho, Hee JinKim, Ju-HwaYoon, Seon-JinKim, HakhyunSa, Jason K.Ju, ShinyeongLee, HwanhoOh, Myung JoonLee, WonyeopKwon, YumiLi, HonglanChoi, SeunghyukHan, Jang HeeChang, Jong HeeChoi, EunsukKim, JayeonHer, Nam-GuKim, Se HoonKang, Seok-GuPaek, EunokNam, Do-HyunLee, CheoljuKim, Hyun Seok
Issue Date
3-Jul-2020
Publisher
NATURE PUBLISHING GROUP
Citation
NATURE COMMUNICATIONS, v.11, no.1
Indexed
SCIE
SCOPUS
Journal Title
NATURE COMMUNICATIONS
Volume
11
Number
1
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/54437
DOI
10.1038/s41467-020-17139-y
ISSN
2041-1723
Abstract
The prognostic and therapeutic relevance of molecular subtypes for the most aggressive isocitrate dehydrogenase 1/2 (IDH) wild-type glioblastoma (GBM) is currently limited due to high molecular heterogeneity of the tumors that impedes patient stratification. Here, we describe a distinct binary classification of IDH wild-type GBM tumors derived from a quantitative proteomic analysis of 39 IDH wild-type GBMs as well as IDH mutant and low-grade glioma controls. Specifically, GBM proteomic cluster 1 (GPC1) tumors exhibit Warburg-like features, neural stem-cell markers, immune checkpoint ligands, and a poor prognostic biomarker, FKBP prolyl isomerase 9 (FKBP9). Meanwhile, GPC2 tumors show elevated oxidative phosphorylation-related proteins, differentiated oligodendrocyte and astrocyte markers, and a favorable prognostic biomarker, phosphoglycerate dehydrogenase (PHGDH). Integrating these proteomic features with the pharmacological profiles of matched patient-derived cells (PDCs) reveals that the mTORC1/2 dual inhibitor AZD2014 is cytotoxic to the poor prognostic PDCs. Our analyses will guide GBM prognosis and precision treatment strategies. The heterogeneity of IDH1/2 wild-type glioblastoma limits its prognosis and therapy. Here, the authors show a binary stratification, based on quantitative proteomic analysis of samples from patients with glioblastoma, with different prognosis and therapeutic vulnerabilities.
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