The tumor microenvironment strongly impacts master transcriptional regulators and gene expression class of glioblastoma.
ABSTRACT: The Cancer Genome Atlas (TCGA) project has generated gene expression data that divides glioblastoma (GBM) into four transcriptional classes: proneural, neural, classical, and mesenchymal. Because transcriptional class is only partially explained by underlying genomic alterations, we hypothesize that the tumor microenvironment may also have an impact. In this study, we focused on necrosis and angiogenesis because their presence is both prognostically and biologically significant. These features were quantified in digitized histological images of TCGA GBM frozen section slides that were immediately adjacent to samples used for molecular analysis. Correlating these features with transcriptional data, we found that the mesenchymal transcriptional class was significantly enriched with GBM samples that contained a high degree of necrosis. Furthermore, among 2422 genes that correlated with the degree of necrosis in GBMs, transcription factors known to drive the mesenchymal expression class were most closely related, including C/EBP-?, C/EBP-?, STAT3, FOSL2, bHLHE40, and RUNX1. Non-mesenchymal GBMs in the TCGA data set were found to become more transcriptionally similar to the mesenchymal class with increasing levels of necrosis. In addition, high expression levels of the master mesenchymal factors C/EBP-?, C/EBP-?, and STAT3 were associated with a poor prognosis. Strong, specific expression of C/EBP-? and C/EBP-? by hypoxic, perinecrotic cells in GBM likely account for their tight association with necrosis and may be related to their poor prognosis.
Project description:Glioblastomas (GBMs), the most aggressive primary brain tumors, exhibit increased invasiveness and resistance to anti-tumor treatments. We explored the role of RTVP-1, a glioma-associated protein that promotes glioma cell migration, in the mesenchymal transformation of GBM. Analysis of The Cancer Genome Atlas (TCGA) demonstrated that RTVP-1 expression was higher in mesenchymal GBM and predicted tumor recurrence and poor clinical outcome. ChiP analysis revealed that the RTVP-1 promoter binds STAT3 and C/EBP?, two master transcription factors that regulate mesenchymal transformation of GBM. In addition, IL-6 induced RTVP-1 expression in a STAT3-dependent manner. RTVP-1 increased the migration and mesenchymal transformation of glioma cells. Similarly, overexpression of RTVP-1 in human neural stem cells induced mesenchymal differentiation, whereas silencing of RTVP-1 in glioma stem cells (GSCs) decreased the mesenchymal transformation and stemness of these cells. Silencing of RTVP-1 also increased the survival of mice bearing GSC-derived xenografts. Using gene array analysis of RTVP-1 silenced glioma cells we identified IL-6 as a mediator of RTVP-1 effects on the mesenchymal transformation and migration of GSCs, therefore acting in a positive feedback loop by upregulating RTVP-1 expression via the STAT3 pathway. Collectively, these results implicate RTVP-1 as a novel prognostic marker and therapeutic target in GBM.
Project description:Glioblastoma (GBM), the most malignant of the brain tumors is classified on the basis of molecular signature genes using TCGA data into four subtypes- classical, mesenchymal, proneural and neural. The mesenchymal phenotype is associated with greater aggressiveness and low survival in contrast to GBMs enriched with proneural genes. The proinflammatory cytokines secreted in the microenvironment of gliomas play a key role in tumor progression. The study focused on the role of Oncostatin-M (OSM), an IL-6 family cytokine in inducing mesenchymal properties in GBM. Analysis of TCGA and REMBRANDT data revealed that expression of OSMR but not IL-6R or LIFR is upregulated in GBM and has negative correlation with survival. Amongst the GBM subtypes, OSMR level was in the order of mesenchymal > classical > neural > proneural. TCGA data and RT-PCR analysis in primary cultures of low and high grade gliomas showed a positive correlation between OSMR and mesenchymal signature genes-YKL40/CHI3L1, fibronectin and vimentin and a negative correlation with proneural signature genes-DLL3, Olig2 and BCAN. OSM enhanced transcript and protein level of fibronectin and YKL-40 and reduced the expression of Olig2 and DLL3 in GBM cells. OSM-regulated mesenchymal phenotype was associated with enhanced MMP-9 activity, increased cell migration and invasion. Importantly, OSM induced mesenchymal markers and reduced proneural genes even in primary cultures of grade-III glioma cells. We conclude that OSM-mediated signaling contributes to aggressive nature associated with mesenchymal features via STAT3 signaling in glioma cells. The data suggest that OSMR can be explored as potential target for therapeutic intervention.
Project description:Glioblastomas (GBMs) are characterized by four subtypes, proneural (PN), neural, classical, and mesenchymal (MES) GBMs, and they all have distinct activated signaling pathways. Among the subtypes, PN and MES GBMs show mutually exclusive genetic signatures, and the MES phenotype is, in general, believed to be associated with more aggressive features of GBM: tumor recurrence and drug resistance. Therefore, targeting MES GBMs would improve the overall prognosis of patients with fatal tumors. In this study, we propose peroxisome proliferator-activated receptor gamma (PPAR?) as a potential diagnostic and prognostic biomarker as well as therapeutic target for MES GBM; we used multiple approaches to assess PPAR?, including biostatistics analysis and assessment of preclinical studies. First, we found that PPAR? was exclusively expressed in MES glioblastoma stem cells (GSCs), and ligand activation of endogenous PPAR? suppressed cell growth and stemness in MES GSCs. Further in vivo studies involving orthotopic and heterotopic xenograft mouse models confirmed the therapeutic efficacy of targeting PPAR?; compared to control mice, those that received ligand treatment exhibited longer survival as well as decreased tumor burden. Mechanistically, PPAR? activation suppressed proneural-mesenchymal transition (PMT) by inhibiting the STAT3 signaling pathway. Biostatistical analysis using The Cancer Genomics Atlas (TCGA, n?=?206) and REMBRANDT (n?=?329) revealed that PPAR? upregulation is linked to poor overall survival and disease-free survival of GBM patients. Analysis was performed on prospective (n?=?2) and retrospective (n?=?6) GBM patient tissues, and we finally confirmed that PPAR? expression was distinctly upregulated in MES GBM. Collectively, this study provides insight into PPAR? as a potential therapeutic target for patients with MES GBM.
Project description:In glioblastoma (GBM), brain tumor stem cells (BTSCs) encompass heterogenous populations of multipotent, self-renewing, and tumorigenic cells, which have been proposed to be at the root of therapeutic resistance and recurrence. While the functional significance of BTSC heterogeneity remains to be fully determined, we previously distinguished relatively quiescent stem-like precursor state from the more aggressive progenitor-like precursor state. In the present study, we hypothesized that progenitor-like BTSCs arise from stem-like precursors through a mesenchymal transition and drive post-treatment recurrence. We first demonstrate that progenitor-like BTSCs display a more mesenchymal transcriptomic profile. Moreover, we show that both mesenchymal GBMs and progenitor-like BTSCs are characterized by over-activated STAT3/EMT pathways and that SLUG is the primary epithelial to mesenchymal transition (EMT) transcription factor directly regulated by STAT3 in BTSCs. SLUG overexpression in BTSCs enhances invasiveness, promotes inflammation, and shortens survival. Importantly, SLUG overexpression in a quiescent stem-like BTSC line enhances tumorigenesis. Finally, we report that recurrence is associated with SLUG-induced transcriptional changes in both BTSCs and GBM patient samples. Collectively, our findings show that a STAT3-driven precursor state transition, mediated by SLUG, may prime BTSCs to initiate more aggressive mesenchymal recurrence. Targeting the STAT3/SLUG pathway may maintain BTSCs in a quiescent stem-like precursor state, delaying recurrence and improving survival in GBM.
Project description:BACKGROUND: Aberrant activation of beta-catenin/TCF4 and STAT3 signaling in glioblastoma multiforme (GBM) has been reported. However, the molecular mechanisms related to this process are still poorly understood. METHODS: Genome-wide screening of the binding characteristics of the transcription factors TCF4 and STAT3 in GBM cells was performed by chromatin immunoprecipitation sequencing (ChIP-seq) assay. Hierarchical clustering was used to analyze the association of TCF4 and STAT3 coregulated genes with The Cancer Genome Atlas (TCGA) GBM subtypes (classical, mesenchymal, neural, and proneural). New molecular classification of GBM was proposed and validated in Western and Asian populations. RESULTS: We identified 1250 overlapping putative target genes that were coregulated by TCF4 and STAT3. Further, the coregulated genes had the potential to guide TCGA GBM subtypes. Finally, we proposed a new molecular classification of GBM into 2 subtypes (proneural-like and mesenchymal-like) and showed that the new classification could be applied to both Western and Asian populations. In addition, the GBM response to temozolomide therapy differed depending on its subtype; mesenchymal-like GBM benefited, while there was no benefit for proneural-like GBM. CONCLUSIONS: This is the first comprehensive study to combine a ChIP-seq assay of TCF4 and STAT3 and data mining of patient cohorts to derive molecular subtypes of GBM.
Project description:There is variation in the survival and therapeutic outcome of patients with glioblastomas (GBMs). Therapy resistance is an important challenge in the treatment of GBM patients. The aim of this study was to identify Temozolomide (TMZ) related genes and confirm their clinical relevance. The TMZ-related genes were discovered by analysis of the gene-expression profiling in our cell-based microarray. Their clinical relevance was verified by in silico meta-analysis of the Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA) datasets. Our results demonstrated that BICD1 expression could predict both prognosis and response to therapy in GBM patients. First, high BICD1 expression was correlated with poor prognosis in the TCGA GBM cohort (n=523) and in the CGGA glioma cohort (n=220). Second, high BICD1 expression predicted poor outcome in patients with TMZ treatment (n=301) and radiation therapy (n=405). Third, multivariable Cox regression analysis confirmed BICD1 expression as an independent factor affecting the prognosis and therapeutic response of TMZ and radiation in GBM patients. Additionally, age, MGMT and BICD1 expression were combinedly utilized to stratify GBM patients into more distinct risk groups, which may provide better outcome assessment. Finally, we observed a strong correlation between BICD1 expression and epithelial-mesenchymal transition (EMT) in GBMs, and proposed a possible mechanism of BICD1-associated survival or therapeutic resistance in GBMs accordingly. In conclusion, our study suggests that high BICD1 expression may result in worse prognosis and could be a predictor of poor response to TMZ and radiation therapies in GBM patients.
Project description:Accurate classification of glioblastoma multiforme (GBM) is crucial for understanding its biologic diversity and informing diagnosis and treatment. The Cancer Genome Atlas (TCGA) project identified four GBM classes using gene expression data and separately identified three classes using methylation data. We sought to integrate multiple data types in GBM classification, understand biologic features of the newly defined subtypes, and reconcile with prior studies.We used allele-specific copy number data to estimate the aneuploid content of each tumor and incorporated this measure of intratumor heterogeneity in class discovery. We estimated the potential cell of origin of individual subtypes and the euploid and aneuploid fractions using reference datasets of known neuronal cell types.There exists an unexpected correlation between aneuploid content and the observed among-tumor diversity of expression patterns. Joint use of DNA and mRNA data in ab initio class discovery revealed a distinct group that resembles the Proneural subtype described in a separate study and the glioma-CpG island methylator phenotype (G-CIMP+) class based on methylation data. Three additional subtypes, Classical, Proliferative, and Mesenchymal, were also identified and revised the assignment for many samples. The revision showed stronger differences in patient outcome and clearer cell type-specific signatures. Mesenchymal GBMs had higher euploid content, potentially contributed by microglia/macrophage infiltration.We clarified the confusion about the "Proneural" subtype that was defined differently in different prior studies. The ability to infer within-tumor heterogeneity improved class discovery, leading to new subtypes that are closer to the fundamental biology of GBM.
Project description:The hepatocyte growth factor receptor (c-Met) and a constitutively active mutant of the epidermal growth factor receptor (ΔEGFR/EGFRvIII) are frequently overexpressed in glioblastoma (GBM) and promote tumorigenesis. The mechanisms underlying elevated hepatocyte growth factor (HGF) production in GBM are not understood. We found higher, coordinated mRNA expression levels of HGF and c-Met in mesenchymal (Mes) GBMs, a subtype associated with poor treatment response and shorter overall survival. In an HGF/c-Met-dependent GBM cell line, HGF expression declined upon silencing of c-Met using RNAi or by inhibiting its activity with SU11274. Silencing c-Met decreased anchorage-independent colony formation and increased the survival of mice bearing intracranial GBM xenografts. Consistent with these findings, c-Met activation by ΔEGFR also elevated HGF expression, and the inhibition of ΔEGFR with AG1478 reduced HGF levels. Interestingly, c-Met expression was required for ΔEGFR-mediated HGF production, anchorage-independent growth, and in vivo tumorigenicity, suggesting that these pathways are coupled. Using an unbiased mass spectrometry-based screen, we show that signal transducer and activator of transcription 3 (STAT3) Y705 is a downstream target of c-Met signaling. Suppression of STAT3 phosphorylation with WP1193 reduced HGF expression in ΔEGFR-expressing GBM cells, whereas constitutively active STAT3 partially rescued HGF expression and colony formation in c-Met knockdown cells expressing ΔEGFR. These results suggest that the c-Met/HGF signaling axis is enhanced by ΔEGFR through increased STAT3-dependent HGF expression and that targeting c-Met in Mes GBMs may be an important strategy for therapy.
Project description:Epilepsy at presentation is an independent favorable prognostic factor in glioblastoma (GBM). In this study, we analyze the oncologic signaling pathways that associate with epilepsy in human GBMs, and that can underlie this prognostic effect. Following ethical approval and patient consent, fresh frozen GBM tissue was obtained from 76 patient surgeries. Hospital records were screened for the presence of seizures at presentation of the disease. mRNA and miRNA expression-based and gene set enrichment analyses were performed on these tissues, to uncover candidate oncologic pathways that associate with epilepsy. We performed qPCR experiments and immunohistochemistry on tissue microarrays containing 286 GBMs to further explore the association of these candidate pathways and of markers of mesenchymal transformation (NF-?B, CEBP-?, STAT3, STAT5b, VEGFA, SRF) with epilepsy. Gene sets involved in hypoxia/HIF-1?, STAT5, CEBP-? and epithelial-mesenchymal transformation signaling were significantly downregulated in epileptogenic GBMs. On confirmatory protein expression analyses, epileptogenic tumors were characterized by a significant downregulation of phospho-STAT5b, a target of HIF-1?. Epilepsy status did not associate with molecular subclassification or miRNA expression patterns of the tumors. Epileptogenic GBMs correlate with decreased hypoxia/ HIF-1?/STAT5b signaling compared to glioblastomas that do not present with epilepsy.
Project description:Glioblastoma multiforme (GBM) is an umbrella designation that includes a heterogeneous group of primary brain tumors. Several classification strategies of GBM have been reported, some by clinical course and others by resemblance to cell types either in the adult or during development. From a practical and therapeutic standpoint, classifying GBMs by signal transduction pathway activation and by mutation in pathway member genes may be particularly valuable for the development of targeted therapies.We performed targeted proteomic analysis of 27 surgical glioma samples to identify patterns of coordinate activation among glioma-relevant signal transduction pathways, then compared these results with integrated analysis of genomic and expression data of 243 GBM samples from The Cancer Genome Atlas (TCGA). In the pattern of signaling, three subclasses of GBM emerge which appear to be associated with predominance of EGFR activation, PDGFR activation, or loss of the RAS regulator NF1. The EGFR signaling class has prominent Notch pathway activation measured by elevated expression of Notch ligands, cleaved Notch receptor, and downstream target Hes1. The PDGF class showed high levels of PDGFB ligand and phosphorylation of PDGFRbeta and NFKB. NF1-loss was associated with lower overall MAPK and PI3K activation and relative overexpression of the mesenchymal marker YKL40. These three signaling classes appear to correspond with distinct transcriptomal subclasses of primary GBM samples from TCGA for which copy number aberration and mutation of EGFR, PDGFRA, and NF1 are signature events.Proteomic analysis of GBM samples revealed three patterns of expression and activation of proteins in glioma-relevant signaling pathways. These three classes are comprised of roughly equal numbers showing either EGFR activation associated with amplification and mutation of the receptor, PDGF-pathway activation that is primarily ligand-driven, or loss of NF1 expression. The associated signaling activities correlating with these sentinel alterations provide insight into glioma biology and therapeutic strategies.