Dataset Information

Glioma proteome - Quantitative proteomics reveals fundamental regulatory differences in oncogenic HRAS and IDH1 driven astrocytoma

ABSTRACT: In the present study, we applied a quantitative MS-based strategy to characterize the proteome and phosphoproteome in HRAS- or IDH1-driven glioma cells. We describe the driving roles of the MEK and PI3K signaling pathways in RAS-NHA cells, and uncover oncogenic signaling in other pathways. We highlight the interplay between the signaling cascades and show that inhibition of MEK and PI3K reverses phosphorylation signaling patterns driven by oncogenic RAS overexpression. Applying a histone hybrid chemical labeling method and high-resolution MS, we identified significant histone methylation, acetylation, and butyrylation changes in IDH1mut-NHA cells. Our results suggest a global transcriptional repressive state, consistent with the down-regulation of the proteome, transcriptome, and the DNA hyper-methylated state in IDH1mut-NHA cells. We provide a unique resource of altered proteins, phosphosites, and histone PTMs in RAS and IDH1 mutant astrocytoma cell lines, providing insight into oncogenesis in glioma beyond the transcriptomic level.

INSTRUMENT(S): LTQ Orbitrap Velos, Orbitrap Fusion

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Cell Culture

SUBMITTER: Sophia Doll

LAB HEAD: Sophia Doll

PROVIDER: PXD004945 | Pride | 2016-12-23

REPOSITORIES: Pride

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Publications

Quantitative Proteomics Reveals Fundamental Regulatory Differences in Oncogenic HRAS and Isocitrate Dehydrogenase (IDH1) Driven Astrocytoma.

Doll Sophia S Urisman Anatoly A Oses-Prieto Juan A JA Arnott David D Burlingame Alma L AL

Molecular & cellular proteomics : MCP 20161110 1

Glioblastoma multiformes (GBMs) are high-grade astrocytomas and the most common brain malignancies. Primary GBMs are often associated with disturbed RAS signaling, and expression of oncogenic HRAS results in a malignant phenotype in glioma cell lines. Secondary GBMs arise from lower-grade astrocytomas, have slower progression than primary tumors, and contain IDH1 mutations in over 70% of cases. Despite significant amount of accumulating genomic and transcriptomic data, the fundamental mechanisti ...[more]

PMID: 27834733

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Project description:Background: Signaling by receptor tyrosine kinases (RTK) is frequently dysregulated in gliomas. Inter-individual variability in the causes for dysregulated RTK signaling may have hampered the efficacy of targeted therapies. Using gene expression modules around key regulators in the RAS-RAF-MEK-MAPK cascade and in the phosphatidylinositol 3-kinase-AKT pathways, we developed a âRMPAâ clustering scheme to distinguish gliomas with varying extents of RTK signaling. Results: We identified gene modules consistently co-expressed with NF1 (NF1-M), Sprouty (SPRY-M) and PTEN (PTEN-M) in gliomas. Their signatures enabled robust clustering of adult diffuse gliomas of WHO grades II-IV into RMPAhigh and RMPAlow phenotypes in a morphology-independent manner. In five independent data sets from three continents containing more than 1500 adult diffuse gliomas, RMPAhigh gliomas were associated with poor prognosis while RMPAlow gliomas were not. The RMPAhigh and RMPAlow glioma subtypes showed distinct levels of the activities of RAS-RAF-MEK-MAPK cascade and PI3K-AKT pathway and harbored unique sets of genomic alterations in the RTK signaling-related genes. The RMPAhigh gliomas contained large numbers of immature vessel cells and tumor associated macrophages and both cell types expressed high levels of pro-angiogenic RTKs including MET, VEGFR1, KDR, EPHB4 and NRP1. Conclusion: Inter-glioma variability in RTK signaling activities can be defined using the RMPA clustering scheme. The combined signatures of NF1-M, SPRY-M and PTEN-M reflect RTK signaling activity both in the glioma cells and in the glioma microenvironment. Our data show that RTK signaling in the glioma microenvironment may play a pivotal role in glioma progression. Transcriptome data from 22 fresh gliomas (2 astrocytoma II, 1 oligodendrocytoma II, 7 oligoastrocytoma II, 4 anaplastic oligoastrocytoma III and 8 GBM) were obtained using Affymetrix Human Gene 1.0 ST Array. Unsupervised hierarchical clustering of the expression data for the SPRY-M, NF1-M and PTEN-M was performed on these transcriptome data to identify samples with RMPAhigh or RMPAlow signature.

Dataset Information

Glioma proteome - Quantitative proteomics reveals fundamental regulatory differences in oncogenic HRAS and IDH1 driven astrocytoma

Publications

Quantitative Proteomics Reveals Fundamental Regulatory Differences in Oncogenic HRAS and Isocitrate Dehydrogenase (IDH1) Driven Astrocytoma.

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