GQIcombi application to subdue glioma via differentiation therapy
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE250617 | GEO | 2024/01/09
REPOSITORIES: GEO
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Project description:Diffusely infiltrative growth of human astrocytic gliomas is one of the major obstacles to successful tumor therapy. Thorough insights into the miRNAs inolved in regulating glioma cell invasion thus appear of major relevance for the development of novel and advanced therapies. miRNA expression profiling on microdissected human tumor biopsy specimens was performed to identify differentially expressed miRNAs in invading glioblastoma cells in vivo. miRNA was extracted from the infiltrative rim (INF) as well as from the central tumor areas (CEN) of 7 patients with malignant glioma. The Micro Fluidic Card System (Applied Biosystems) was used according to the manufacturerM-bM-^@M-^Ys protocol for miRNA expression profiling.
2012-05-03 | E-GEOD-37737 | biostudies-arrayexpress
Project description:Diffuse infiltrating gliomas are the most common primary brain malignancy found in adults, and Glioblastoma multiforme, the highest grade glioma, is associated with a median survival of 7 months. Transcriptional profiling has been applied to 85 gliomas from 74 patients to elucidate glioma biology, prognosticate survival, and define tumor sub-classes. These studies reveal that transcriptional profiling of gliomas is more accurate at predicting survival than traditional pathologic grading, and that gliomas characteristically express coordinately regulated genes of one of four molecular signatures: neurogenesis, synaptic transmission, mitotic, or extra-cellular matrix. Elucidation of these survival associated molecular signatures will aid in tumor prognostication and define targets for future directed therapy. Evaluate a large number of diffuse infiltrating gliomas through transcriptional profiling. Glioma tumor sub-classes may be identified through large scale gene expression studies. All patients undergoing surgical treatment at the University of California, Los Angeles for primary brain cancers between 1996 and 2003 were invited to participate in this Institutional Review Board approved study. 74 of the patients participating in this broad protocol were analyzed as part of this study if their initial tumor was diagnosed as a grade III (n=24) or IV (n=50) glioma of any histologic type on initial surgical treatment and fresh frozen material was obtained. Only grade III and IV gliomas were included in this study as the distinction between these grades is subtle and prone to misclassification. The time in days elapsed from resection to the day of death, or if the patient has remained alive, to the current day was recorded for all samples studied. Patient ages at diagnosis varied from 18 to 82 years. There were 46 females and 28 males. Probes were prepared using standard Affymetrix protocols, and hybridized to Affymetrix HG-U133A and HG-U133B arrays.
2007-12-20 | E-GEOD-4412 | biostudies-arrayexpress
Project description:Glial cell-derived brain tumors (gliomas) are devastating diseases without effective curative therapies. Gliomas are classified according to various schemes including the cancer-initiating cell type, World Health Organization tumor grades, and genetic markers such as Isocitrate dehydrogenase (IDH) mutations and chromosomal 1p/19q codeletion status. Genomics, transcriptomics and methylomics approaches are emerging as powerful means to refine classification. However, various aspects of cancer biology are solely reflected on the proteomelevel. Here, we employ mass spectrometry (MS) to characterize the proteomes and phospho-proteomes of IDHmut glioma entities with and without 1p/19q codeletion, IDHwt gliomas and control tissue from a total of 42 patients. Our data-dependent acquisition MS workflow on average quantifies more than 5000 proteins and 3000 phospho-sites per sample of formalin-fixed paraffin-embedded (FFPE) brain sections. The tumor proteomes reflected genetic alterations such as the loss of chromosome 1p/19q proteins, the loss of ATRX in non-codeletion IDHmut glioma, and the frequent loss and amplification of chromosomes 10 and 7, respectively,in IDH-wild type glioma. Nevertheless, 1p/19q codeletion status was not the major determinant of IDHmut glioma proteomes. Instead, the proteome profiles suggest an alternative classification of IDHmut gliomas that correlates with the loss of mitochondrial DNA-encoded proteins, the abundance of respiratory chain proteins, a distinct tumor suppressor and oncoprotein profile, an extracellular matrix signature, and alterations in the phospho-proteome. Moreover, the glioma association of numerous proteins implicated in other cancers by this dataset provides a resource for further mechanistic investigation of glioma genesis and progression.
2022-11-09 | PXD024427 | Pride
Project description:Hypoxia is negatively associated with glioblastoma patient survival and contributes strongly to tumor resistance. Unfortunately novel anti-angiogenic therapy increases hypoxia and activates survival pathways in tumor cells leading to inevitable tumor relapse. Here we demonstrate that primary glioma cultures and cell lines depend on autophagy to survive severe hypoxia but also at normal oxygen levels. Positive regulators of autophagy are expressed at higher levels in tumor cells and induction in severe hypoxia is more prominent compared to normal brain cells. We demonstrate that autophagy is an essential/critical target for novel treatment in glioblastoma. We show ATG9A is induced by severe hypoxia and could be a novel player of the autophagic response in glioma cells. ATG9A targeting inhibited tumor growth, suggesting an essential role in glioma cell survival in vivo. While autophagy induction was also observed in normal astrocytes, glioma cells displayed a higher sensitivity towards autophagy inhibitors. Importantly, patient-derived cultures exhibited varying sensitivity towards anti-autophagy treatment, where certain cultures were dependent on autophagy already in normoxic conditions. The treatment of tumor bearing mice with the autophagy inhibitor chloroquine significantly increased mice survival, but combination treatment of the agent with bevacizumab did not reveal additive or synergistic effect. The present study demonstrates that inhibition of autophagy using chloroquine as a single agent provides a novel treatment strategy against glioblastoma. It remains to be seen whether autophagy inhibition will improve current standard of care treatment of newly diagnosed glioblastoma patients and whether more specific inhibitors will lead to stronger therapeutic outcome. (Provisional)
2015-11-10 | E-MTAB-3085 | biostudies-arrayexpress
Project description:Background: Molecular profiling of diffuse gliomas has provided significant insights into the pathogenesis, classification and prognostication of these malignancies. However, previous molecular studies of glioma have largely focused on genomic readouts and targeted proteomic profiling technologies. Consequently, proteomic and downstream functional landscape of gliomas in general, and molecular subgroups in particular, remains largely unexplored. Here, we utilize liquid chromatography tandem mass spectrometry to profile genomically-defined cohorts of gliomas spanning the full range of World Health Organization (WHO) grades. Methods: Bulk frozen tissue and purified micro-dissected regions from formalin-fixed paraffin-embedded (FFPE) tissues were assembled and utilized to define robust proteomic signatures of both low grade, infiltrative and high-grade tumors. As a final analysis, primary tumor tissue was compared with both IDH-mutated and IDH-wildtype glioblastoma stem cell (GSC) lines to further overcome tissue heterogeneity and pinpoint proteins differences likely arising in the relevant glial cellular drivers of tumor development. Results: In aggregate, 5,496 unique proteins over 3 glioma cohorts were identified, and span common molecular subclasses based on IDH and 1p19q co-deletion status and all four WHO grades. Supervised clustering highlights substantial proteome and systems-level pathway differences between different genetically defined glioma subtypes and WHO grades. By using bulk tumor statistical analysis, 833 proteins distinguish different WHO grade tumors, while FFPE tumor dissection reveals 287 proteins in GBMs with abundance changes according to IDH mutation status. Using our integrative approach, calcium signaling, proteins of the endoplasmic reticulum and extracellular integrin proteins are most conserved proteomic markers that distinguish aggressive, IDH-wt, from IDH-mut GBM tumors in primary and tissue culture models gliomagenesis. Conclusions: This proteomic survey provides the largest and most diverse unbiased protein-based brain tumor resource to date. Current treatments for glial tumors are largely non-specific and overlap between genomic subtypes and WHO grades. Our analysis provides early insight into the vast downstream and epigenetic protein-level differences within this molecular framework. Given the central position proteins occupy in driving biology and phenotype, further characterization of the substantial proteomic diversity that exist between the molecular subtypes and grades of gliomas, proteomics may help define more personalized prognostic and predictive biomarkers for precision care.
2019-07-30 | PXD010133 | Pride
Project description:Background: Molecular profiling of diffuse gliomas has provided significant insights into the pathogenesis, classification and prognostication of these malignancies. However, previous molecular studies of glioma have largely focused on genomic readouts and targeted proteomic profiling technologies. Consequently, proteomic and downstream functional landscape of gliomas in general, and molecular subgroups in particular, remains largely unexplored. Here, we utilize liquid chromatography tandem mass spectrometry to profile genomically-defined cohorts of gliomas spanning the full range of World Health Organization (WHO) grades. Methods: Bulk frozen tissue and purified micro-dissected regions from formalin-fixed paraffin-embedded (FFPE) tissues were assembled and utilized to define robust proteomic signatures of both low grade, infiltrative and high-grade tumors. As a final analysis, primary tumor tissue was compared with both IDH-mutated and IDH-wildtype glioblastoma stem cell (GSC) lines to further overcome tissue heterogeneity and pinpoint proteins differences likely arising in the relevant glial cellular drivers of tumor development. Results: In aggregate, 5,496 unique proteins over 3 glioma cohorts were identified, and span common molecular subclasses based on IDH and 1p19q co-deletion status and all four WHO grades. Supervised clustering highlights substantial proteome and systems-level pathway differences between different genetically defined glioma subtypes and WHO grades. By using bulk tumor statistical analysis, 833 proteins distinguish different WHO grade tumors, while FFPE tumor dissection reveals 287 proteins in GBMs with abundance changes according to IDH mutation status. Using our integrative approach, calcium signaling, proteins of the endoplasmic reticulum and extracellular integrin proteins are most conserved proteomic markers that distinguish aggressive, IDH-wt, from IDH-mut GBM tumors in primary and tissue culture models gliomagenesis. Conclusions: This proteomic survey provides the largest and most diverse unbiased protein-based brain tumor resource to date. Current treatments for glial tumors are largely non-specific and overlap between genomic subtypes and WHO grades. Our analysis provides early insight into the vast downstream and epigenetic protein-level differences within this molecular framework. Given the central position proteins occupy in driving biology and phenotype, further characterization of the substantial proteomic diversity that exist between the molecular subtypes and grades of gliomas, proteomics may help define more personalized prognostic and predictive biomarkers for precision care.
2019-07-30 | PXD010099 | Pride
Project description:Background: Molecular profiling of diffuse gliomas has provided significant insights into the pathogenesis, classification and prognostication of these malignancies. However, previous molecular studies of glioma have largely focused on genomic readouts and targeted proteomic profiling technologies. Consequently, proteomic and downstream functional landscape of gliomas in general, and molecular subgroups in particular, remains largely unexplored. Here, we utilize liquid chromatography tandem mass spectrometry to profile genomically-defined cohorts of gliomas spanning the full range of World Health Organization (WHO) grades. Methods: Bulk frozen tissue and purified micro-dissected regions from formalin-fixed paraffin-embedded (FFPE) tissues were assembled and utilized to define robust proteomic signatures of both low grade, infiltrative and high-grade tumors. As a final analysis, primary tumor tissue was compared with both IDH-mutated and IDH-wildtype glioblastoma stem cell (GSC) lines to further overcome tissue heterogeneity and pinpoint proteins differences likely arising in the relevant glial cellular drivers of tumor development. Results: In aggregate, 5,496 unique proteins over 3 glioma cohorts were identified, and span common molecular subclasses based on IDH and 1p19q co-deletion status and all four WHO grades. Supervised clustering highlights substantial proteome and systems-level pathway differences between different genetically defined glioma subtypes and WHO grades. By using bulk tumor statistical analysis, 833 proteins distinguish different WHO grade tumors, while FFPE tumor dissection reveals 287 proteins in GBMs with abundance changes according to IDH mutation status. Using our integrative approach, calcium signaling, proteins of the endoplasmic reticulum and extracellular integrin proteins are most conserved proteomic markers that distinguish aggressive, IDH-wt, from IDH-mut GBM tumors in primary and tissue culture models gliomagenesis. Conclusions: This proteomic survey provides the largest and most diverse unbiased protein-based brain tumor resource to date. Current treatments for glial tumors are largely non-specific and overlap between genomic subtypes and WHO grades. Our analysis provides early insight into the vast downstream and epigenetic protein-level differences within this molecular framework. Given the central position proteins occupy in driving biology and phenotype, further characterization of the substantial proteomic diversity that exist between the molecular subtypes and grades of gliomas, proteomics may help define more personalized prognostic and predictive biomarkers for precision care.
2019-07-30 | PXD010098 | Pride
Project description:In this study, we describe a novel relationship between glioblastoma CSCs and the Notch pathway, which involves the constitutive activation of STAT3 and NF-κB signaling. We demonstrate that adherent glioma CSCs exhibit characteristics previously described for CSCs grown in suspension culture. The expression of CD133, Sox2 and Nestin increased when compared to glioma cells grown in monolayer, and the adherent CSCs were ~100 times more tumorigenic in vivo than monolayer cultured glioma cells. We also found that while the STAT3 and NF-κB signaling pathways are constitutively activated in glioma lines, these pathways are dramatically activated in glioma CSCs. Treatment with STAT3 inhibitors led to a loss of nuclear activation of STAT3 signaling and suppression of growth in both monolayer and CSC conditions. There was a markedly greater growth suppressive effect on glioma CSCs, suggesting that targeted therapy of these key pathways in glioma CSCs may be possible. To further investigate potential biomarkers in glioma CSCs, microarray analysis was performed and revealed deregulation of the Notch signaling pathway. This constitutive activation of STAT3, NF-κB, and Notch pathways in glioma CSCs helps identify novel therapeutic targets for the treatment of glioma. GBM6 cells were continuously maintained as subcutaneous xenografts in NSG mice, and monolayer and CSC cultures were derived from freshly harvested tumor tissue. A total of 6 samples were subjected to microarray analysis, with three biological replicates for each experimental condition.
2013-06-19 | E-GEOD-48079 | biostudies-arrayexpress
Project description:High-grade gliomas are amongst the most deadly human tumors. Treatment results are overall disappointing. Nevertheless, in several trials around 20% of patients respond to therapy. Diagnostic strategies to identify those patients that will ultimately profit from a specific targeted therapy are urgently needed. Gene expression profiling of untreated tumors is a well established approach for identifying biomarkers or diagnostic signatures. However, reliable signatures predicting treatment response in gliomas do not exist. Here we suggest a novel strategy for developing diagnostic signatures. We postulate that predictive gene expression patterns emerge only after tumor cells have been treated with the agent in vitro. Moreover, we postulate that enriching specimens for tumor initiating cells sharpens predictive expression patterns. Here, we report on the prediction of treatment response of cancer cells in vitro. As a proof of principle we analyzed gene expression in 18 short-term serum-free cultures of high-grade gliomas enhanced for brain tumor initiating cells (BTIC) before and after in vitro treatment with the tyrosine kinase inhibitor Sunitinib. Profiles from treated but not from untreated glioma cells allowed to predict therapy-induced impairment of proliferation of glioma cells in vitro. Prediction can be achieved with as little as 6 genes allowing for a straightforward translation into the clinic once the predictive power of the signature is shown also in vivo. Our strategy of using expression profiles from in vitro treated BTIC-enriched cultures opens new ways for trial design for patients with malignant gliomas. 72 samples; 18 brain tumor initiating cells (BTICs); 4 treatment conditions: 1 µM Sunitinib or 0.00025% DMSO with and without the combination of recombinant growth factors VEGF and PDGF-AB for 6 hours
2014-10-07 | E-GEOD-51305 | biostudies-arrayexpress
Project description:Diffuse infiltrating gliomas are the most common primary brain malignancy found in adults, and Glioblastoma multiforme, the highest grade glioma, is associated with a median survival of 7 months. Transcriptional profiling has been applied to 85 gliomas from 74 patients to elucidate glioma biology, prognosticate survival, and define tumor sub-classes. These studies reveal that transcriptional profiling of gliomas is more accurate at predicting survival than traditional pathologic grading, and that gliomas characteristically express coordinately regulated genes of one of four molecular signatures: neurogenesis, synaptic transmission, mitotic, or extra-cellular matrix. Elucidation of these survival associated molecular signatures will aid in tumor prognostication and define targets for future directed therapy. Evaluate a large number of diffuse infiltrating gliomas through transcriptional profiling. Glioma tumor sub-classes may be identified through large scale gene expression studies. All patients undergoing surgical treatment at the University of California, Los Angeles for primary brain cancers between 1996 and 2003 were invited to participate in this Institutional Review Board approved study. 74 of the patients participating in this broad protocol were analyzed as part of this study if their initial tumor was diagnosed as a grade III (n=24) or IV (n=50) glioma of any histologic type on initial surgical treatment and fresh frozen material was obtained. Only grade III and IV gliomas were included in this study as the distinction between these grades is subtle and prone to misclassification. The time in days elapsed from resection to the day of death, or if the patient has remained alive, to the current day was recorded for all samples studied. Patient ages at diagnosis varied from 18 to 82 years. There were 46 females and 28 males. Probes were prepared using standard Affymetrix protocols, and hybridized to Affymetrix HG-U133A and HG-U133B arrays. Keywords: disease state analysis
2006-03-08 | GSE4412 | GEO