Dataset Information

Expression data from PDGF driven mouse tumors

ABSTRACT: Background Tumor heterogeneity is a major obstacle for finding effective treatment of Glioblastoma (GBM). Based on global expression analysis, GBM can be classified into distinct subtypes: Proneural, Neural, Classical and Mesenchymal. The signatures of these different tumor subtypes may reflect the phenotypes of cells giving rise to them. However, the experimental evidence connecting any specific subtype of GBM to particular cells of origin is lacking. In addition, it is unclear how different genetic alterations interact with cells of origin in determining tumor heterogeneity. This issue cannot be addressed by studying end-stage human tumors. Methodology/Principal Findings To address this issue, we used retroviruses to deliver transforming genetic lesions to glial progenitors in adult mouse brain. We compared the resulting tumors to human GBM. We found that different initiating genetic lesions gave rise to tumors with different growth rates. However all mouse tumors closely resembled the human Proneural GBM. Comparative analysis of these mouse tumors allowed us to identify a set of genes whose expression in humans with Proneural GBM correlates with survival. Conclusions/Significance This study offers insights into the relationship between adult glial progenitors and Proneural GBM, and allows us to identify molecular alterations that lead to more aggressive tumor growth. In addition, we present a new preclinical model that can be used to test treatments directed at a specific type of GBM in future studies.

ORGANISM(S): Mus musculus

PROVIDER: GSE29458 | GEO | 2011/05/23

SECONDARY ACCESSION(S): PRJNA141577

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:Glioblastoma (GBM), the most malignant primary brain tumor, is characterized by widespread heterogeneity, leading to poor and unpredictable clinical outcomes. Recent studies have provided evidences that the tumor microenvironment has a critical role in regulating tumor growth by establishing a complex network of interactions with tumor cells. Here we investigate how GBM cells modulate glial cells, and how this modulation can influence back on the malignant phenotype of GBM cells. Primary mouse glial cultures were established and cultured in serum-free media (unprimed) or exposed to secretome derived from GL261 GBM cells (primed). Conditioned media (CM) from each glial culture were collected and a proteomic analysis was conducted. Glial cells CM (unprimed and primed) were also used in GL261 GBM cells to evaluate its impact in critical hallmarks of GBM cells, including viability, migration, and activation of tumor-related intracellular signaling pathways. The proteomic analysis revealed that the pre-exposure of glial cells to CM from GBM cells led to the upregulation of several proteins related to inflammatory response, cell adhesion and extracellular structure organization within the secretome of primed glial cells, consistent with a pattern of reactive astrogliosis. At the functional levels, CM derived from unprimed glial cells favored an increase in cell migration capacity, while CM from primed glial cells was more efficient in promoting GBM cells viability. These effects on GBM cells were accompanied by activation of particular intracellular cancer-related pathways, mainly the MAPK/ERK pathway, which is a known regulator of cell proliferation. Together, our results demonstrate that glial cells can have a different impact on the progression of GBM tumors, suggesting that the secretome of GBM cells is able to modulate the secretome of neighboring glial cells, in a way that regulates the “go-or-grow” phenotypic switch of GBM cells. Together, our results suggest that glial cells can impact on the pathophysiology of GBM tumors, and that the secretome of GBM cells is able to modulate the secretome of neighboring glial cells, in a way that regulates the “go-or-grow” phenotypic switch of GBM cells.

Project description:Glioblastoma (GBM) is a common and deadly form of brain tumor in adults. Dysregulated metabolism in GBM offers an opportunity to deploy metabolic interventions as precise therapeutic strategies. To identify the molecular drivers and the modalities by which different molecular subgroups of GBM exploit metabolic rewiring to sustain tumor progression, we interrogated the transcriptome, the metabolome, and the glycoproteome of human subgroup-specific GBM sphere-forming cells (GSC). L-fucose abundance and core fucosylation activation were elevated in mesenchymal (MES) compared with proneural GSCs; this pattern was retained in subgroup-specific xenografts and in subgroup-affiliated human patient samples. Genetic and pharmacological inhibition of core fucosylation significantly reduced tumor growth in MES GBM preclinical models. Liquid chromatography-mass spectrometry (LC-MS)-based glycoproteomic screening indicated that most MES-restricted core-fucosylated proteins are involved in therapeutically relevant GBM pathological processes, such as extracellular matrix interaction, cell adhesion, and integrin-mediated signaling. Selective L-fucose accumulation in MES GBMs was observed using preclinical minimally invasive PET, implicating this metabolite as a potential subgroup-restricted biomarker.Overall, these findings indicate that L-fucose pathway activation in MES GBM is a subgroup-specific dependency that could provide diagnostic markers and actionable therapeutic targets.<h4>SIGNIFICANCE: Metabolic characterization of subgroup-specific glioblastoma (GBM) sphere-forming cells identifies the L-fucose pathway as a vulnerability restricted to mesenchymal GBM, disclosing a potential precision medicine strategy for targeting cancer metabolism.</h4> Stem cell and cell line assays are reported in the current study <a href='https://www.ebi.ac.uk/metabolights/MTBLS4708' rel='noopener noreferrer' target='_blank'>MTBLS4708</a>.Xenograft assays are reported in <a href='https://www.ebi.ac.uk/metabolights/MTBLS730' rel='noopener noreferrer' target='_blank'>MTBLS730</a>.

Dataset Information

Expression data from PDGF driven mouse tumors

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets