Browse
Submit Data
Databases
API
Help

Dataset Information

28 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Pathway-based classification of glioblastoma uncovers a mitochondrial subtype with therapeutic vulnerabilities.

ABSTRACT: The transcriptomic classification of glioblastoma (GBM) has failed to predict survival and therapeutic vulnerabilities. A computational approach for unbiased identification of core biological traits of single cells and bulk tumors uncovered four tumor cell states and GBM subtypes distributed along neurodevelopmental and metabolic axes, classified as proliferative/progenitor, neuronal, mitochondrial and glycolytic/plurimetabolic. Each subtype was enriched with biologically coherent multiomic features. Mitochondrial GBM was associated with the most favorable clinical outcome. It relied exclusively on oxidative phosphorylation for energy production, whereas the glycolytic/plurimetabolic subtype was sustained by aerobic glycolysis and amino acid and lipid metabolism. Deletion of the glucose-proton symporter SLC45A1 was the truncal alteration most significantly associated with mitochondrial GBM, and the reintroduction of SLC45A1 in mitochondrial glioma cells induced acidification and loss of fitness. Mitochondrial, but not glycolytic/plurimetabolic, GBM exhibited marked vulnerability to inhibitors of oxidative phosphorylation. The pathway-based classification of GBM informs survival and enables precision targeting of cancer metabolism.

SUBMITTER: Garofano L

PROVIDER: S-EPMC7935068 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

High-resolution structural genomics reveals new therapeutic vulnerabilities in glioblastoma.

Project description:We investigated the role of 3D genome architecture in instructing functional properties of glioblastoma stem cells (GSCs) by generating sub-5-kb resolution 3D genome maps by in situ Hi-C. Contact maps at sub-5-kb resolution allow identification of individual DNA loops, domain organization, and large-scale genome compartmentalization. We observed differences in looping architectures among GSCs from different patients, suggesting that 3D genome architecture is a further layer of inter-patient heterogeneity for glioblastoma. Integration of DNA contact maps with chromatin and transcriptional profiles identified specific mechanisms of gene regulation, including the convergence of multiple super enhancers to individual stemness genes within individual cells. We show that the number of loops contacting a gene correlates with elevated transcription. These results indicate that stemness genes are hubs of interaction between multiple regulatory regions, likely to ensure their sustained expression. Regions of open chromatin common among the GSCs tested were poised for expression of immune-related genes, including CD276 We demonstrate that this gene is co-expressed with stemness genes in GSCs and that CD276 can be targeted with an antibody-drug conjugate to eliminate self-renewing cells. Our results demonstrate that integrated structural genomics data sets can be employed to rationally identify therapeutic vulnerabilities in self-renewing cells.

| S-EPMC6673710 | biostudies-literature

Multi-Platform Classification of IDH-Wild-Type Glioblastoma Based on ERK/MAPK Pathway: Diagnostic, Prognostic and Therapeutic Implications.

Project description:Glioblastoma is the most aggressive and frequent glioma in the adult population. Because current therapy regimens confer only minimal survival benefit, molecular subgrouping to stratify patient prognosis and therapy design is warranted. This study presents a multi-platform classification of glioblastoma by analyzing a large, ethnicity-inclusive 101-adult-patient cohort. It defines seven non-redundant IDH-wild-type glioblastoma molecular subgroups, G1-G7, corresponding to the upstream receptor tyrosine kinase (RTK) and RAS-RAF segment of the ERK/MAPK signal transduction pathway. These glioblastoma molecular subgroups are classified as G1/EGFR, G2/FGFR3, G3/NF1, G4/RAF, G5/PDGFRA, G6/Multi-RTK, and G7/Other. The comprehensive genomic analysis was refined by expression landscaping of all RTK genes, as well as of the major associated growth pathway mediators, and used to hierarchically cluster the subgroups. Parallel demographic, clinical, and histologic pattern analyses were merged with the molecular subgrouping to yield the first inclusive multi-platform classification for IDH-wild-type glioblastoma. This straightforward classification with diagnostic and prognostic significance may be readily used in neuro-oncological practice and lays the foundation for personalized targeted therapy approaches.

| S-EPMC8470497 | biostudies-literature

Identification of a Dexamethasone Mediated Radioprotection Mechanism Reveals New Therapeutic Vulnerabilities in Glioblastoma.

Project description:(1) Background: Despite the indisputable effectiveness of dexamethasone (DEXA) to reduce inflammation in glioblastoma (GBM) patients, its influence on tumour progression and radiotherapy response remains controversial. (2) Methods: We analysed patient data and used expression and cell biological analyses to assess effects of DEXA on GBM cells. We tested the efficacy of tyrosine kinase inhibitors in vitro and in vivo. (3) Results: We confirm in our patient cohort that administration of DEXA correlates with worse overall survival and shorter time to relapse. In GBM cells and glioma stem-like cells (GSCs) DEXA down-regulates genes controlling G2/M and mitotic-spindle checkpoints, and it enables cells to override the spindle assembly checkpoint (SAC). Concurrently, DEXA up-regulates Platelet Derived Growth Factor Receptor (PDGFR) signalling, which stimulates expression of anti-apoptotic regulators BCL2L1 and MCL1, required for survival during extended mitosis. Importantly, the protective potential of DEXA is dependent on intact tyrosine kinase signalling and ponatinib, sunitinib and dasatinib, all effectively overcome the radio-protective and pro-proliferative activity of DEXA. Moreover, we discovered that DEXA-induced signalling creates a therapeutic vulnerability for sunitinib in GSCs and GBM cells in vitro and in vivo. (4) Conclusions: Our results reveal a novel DEXA-induced mechanism in GBM cells and provide a rationale for revisiting the use of tyrosine kinase inhibitors for the treatment of GBM.

| S-EPMC7836009 | biostudies-literature

A Compendium of Syngeneic, Transplantable Pediatric High-Grade Glioma Models Reveals Subtype-Specific Therapeutic Vulnerabilities.

Project description:Pediatric high-grade gliomas (pHGG) are lethal, incurable brain tumors frequently driven by clonal mutations in histone genes. They often harbor a range of additional genetic alterations that correlate with different ages, anatomic locations, and tumor subtypes. We developed models representing 16 pHGG subtypes driven by different combinations of alterations targeted to specific brain regions. Tumors developed with varying latencies and cell lines derived from these models engrafted in syngeneic, immunocompetent mice with high penetrance. Targeted drug screening revealed unexpected selective vulnerabilities-H3.3G34R/PDGFRAC235Y to FGFR inhibition, H3.3K27M/PDGFRAWT to PDGFRA inhibition, and H3.3K27M/PDGFRAWT and H3.3K27M/PPM1DΔC/PIK3CAE545K to combined inhibition of MEK and PIK3CA. Moreover, H3.3K27M tumors with PIK3CA, NF1, and FGFR1 mutations were more invasive and harbored distinct additional phenotypes, such as exophytic spread, cranial nerve invasion, and spinal dissemination. Collectively, these models reveal that different partner alterations produce distinct effects on pHGG cellular composition, latency, invasiveness, and treatment sensitivity.SignificanceHistone-mutant pediatric gliomas are a highly heterogeneous tumor entity. Different histone mutations correlate with different ages of onset, survival outcomes, brain regions, and partner alterations. We have developed models of histone-mutant gliomas that reflect this anatomic and genetic heterogeneity and provide evidence of subtype-specific biology and therapeutic targeting. See related commentary by Lubanszky and Hawkins, p. 1516. This article is highlighted in the In This Issue feature, p. 1501.

| S-EPMC10326601 | biostudies-literature

Alternative classification of glioblastoma based on BUB1B-inhibition sensitivity

Project description:We created a computational framework with which to predict BUB1B-GLEBS sensitivity based on gene expression data from BUB1B-inhibition sensitive (BUB1BS) or resistant (BUB1BR) GBM stem cells (GSCs), astrocytes, and neural progenitors. Our classifier examines the expression of 838 genes comprising the BUB1BS signature. Applying this scheme to GBM patient tumor data stratified tumors into BUB1BS and BUB1BR subtypes, revealing that BUB1BS patients have a significantly worse prognosis regardless of their tumor's development subtype (i.e., classical, mesenchymal, neural, proneural). Applying the same scheme to drug sensitivity profiles predicts that BUB1BS cells to be more sensitive to Raf inhibitors as well as other drugs such as type I and II topoisomerase inhibitors among other drugs. Functional genomic profiling of BUB1BR versus BUB1BS GBM isolates revealed differentially reliance of genes enriched in the BUB1BS classifier, including those involved in mitotic cell cycle, microtubule organization, and chromosome segregation. Taken together, our results show that BUB1BR/S classification of GBM tumors, in addition to predicting BUB1B-inhibition sensitivity, may help predict cancer aggressiveness and sensitivity to multiple anti-cancer drugs.

2018-02-01 | GSE94874 | GEO

MRI-based Algorithm for Acute Ischemic Stroke Subtype Classification.

Project description:Background and purposeIn order to improve inter-rater reliability and minimize diagnosis of undetermined etiology for stroke subtype classification, using a stroke registry, we developed and implemented a magnetic resonance imaging (MRI)-based algorithm for acute ischemic stroke subtype classification (MAGIC).MethodsWe enrolled patients who experienced an acute ischemic stroke, were hospitalized in the 14 participating centers within 7 days of onset, and had relevant lesions on MR-diffusion weighted imaging (DWI). MAGIC was designed to reflect recent advances in stroke imaging and thrombolytic therapy. The inter-rater reliability was compared with and without MAGIC to classify the Trial of Org 10172 in Acute Stroke Treatment (TOAST) of each stroke patient. MAGIC was then applied to all stroke patients hospitalized since July 2011, and information about stroke subtypes, other clinical characteristics, and stroke recurrence was collected via a web-based registry database.ResultsThe overall intra-class correlation coefficient (ICC) value was 0.43 (95% CI, 0.31-0.57) for MAGIC and 0.28 (95% CI, 0.18-0.42) for TOAST. Large artery atherosclerosis (LAA) was the most common cause of acute ischemic stroke (38.3%), followed by cardioembolism (CE, 22.8%), undetermined cause (UD, 22.2%), and small-vessel occlusion (SVO, 14.6%). One-year stroke recurrence rates were the highest for two or more UDs (11.80%), followed by LAA (7.30%), CE (5.60%), and SVO (2.50%).ConclusionsDespite several limitations, this study shows that the MAGIC system is feasible and may be helpful to classify stroke subtype in the clinic.

| S-EPMC4200592 | biostudies-literature

LncRNA-Based Classification of Triple Negative Breast Cancer Revealed Inherent Tumor Heterogeneity and Vulnerabilities.

Project description:Triple negative breast cancer (TNBC) represents a diverse group of cancers based on their gene expression profiles. While the current mRNA-based classification of TNBC has contributed to our understanding of the heterogeneity of this disease, whether such heterogeneity can be resolved employing a long noncoding RNA (lncRNA) transcriptome has not been established thus far. Herein, we used iterative clustering and guide-gene selection (ICGS) and uniform manifold approximation and projection (UMAP) dimensionality reduction analysis on a large cohort of TNBC transcriptomic data (TNBC = 360, normal = 88) and classified TNBC into four main clusters: LINC00511-enriched, LINC00393-enriched, FIRRE-enriched, and normal tissue-like. Delving into associated gene expression profiles revealed remarkable differences in canonical, casual, upstream, and functional categories among different lncRNA-derived TNBC clusters, suggesting functional consequences for altered lncRNA expression. Correlation and survival analysis comparing mRNA- and lncRNA-based clustering revealed similarities and differences between the two classification approaches. To provide insight into the potential role of the identified lncRNAs in TNBC biology, CRISPR-Cas9 mediated LINC00511 promoter deletion reduced colony formation and enhanced the sensitivity of TNBC cells to paclitaxel, suggesting a role for LINC00511 in conferring tumorigenicity and resistance to therapy. Our data revealed a novel lncRNA-based classification of TNBC and suggested their potential utilization as disease biomarkers and therapeutic targets.

| S-EPMC9326727 | biostudies-literature

Enhancer profiling of glioblastoma uncovers core oncogenic dependency and therapeutic opportunity

Project description:This SuperSeries is composed of the SubSeries listed below.

2021-05-05 | GSE145646 | GEO

Differential localization of glioblastoma subtype: implications on glioblastoma pathogenesis.

Project description:The subventricular zone (SVZ) has been implicated in the pathogenesis of glioblastoma. Whether molecular subtypes of glioblastoma arise from unique niches of the brain relative to the SVZ remains largely unknown. Here, we tested whether these subtypes of glioblastoma occupy distinct regions of the cerebrum and examined glioblastoma localization in relation to the SVZ.Pre-operative MR images from 217 glioblastoma patients from The Cancer Imaging Archive were segmented automatically into contrast enhancing (CE) tumor volumes using Iterative Probabilistic Voxel Labeling (IPVL). Probabilistic maps of tumor location were generated for each subtype and distances were calculated from the centroid of CE tumor volumes to the SVZ. Glioblastomas that arose in a Genetically Modified Murine Model (GEMM) model were also analyzed with regard to SVZ distance and molecular subtype.Classical and mesenchymal glioblastomas were more diffusely distributed and located farther from the SVZ. In contrast, proneural and neural glioblastomas were more likely to be located in closer proximity to the SVZ. Moreover, in a GFAP-CreER; PtenloxP/loxP; Trp53loxP/loxP; Rb1loxP/loxP; Rbl1-/- GEMM model of glioblastoma where tumor can spontaneously arise in different regions of the cerebrum, tumors that arose near the SVZ were more likely to be of proneural subtype (p < 0.0001).Glioblastoma subtypes occupy different regions of the brain and vary in proximity to the SVZ. These findings harbor implications pertaining to the pathogenesis of glioblastoma subtypes.

| S-EPMC5041878 | biostudies-other

One-Carbon Metabolism Associated Vulnerabilities in Glioblastoma: A Review.

Project description:Altered cell metabolism is a hallmark of cancer cell biology, and the adaptive metabolic strategies of cancer cells have been of recent interest to many groups. Metabolic reprogramming has been identified as a critical step in glial cell transformation, and the use of antimetabolites against glioblastoma has been investigated. One-carbon (1-C) metabolism and its associated biosynthetic pathways, particularly purine nucleotide synthesis, are critical for rapid proliferation and are altered in many cancers. Purine metabolism has also been identified as essential for glioma tumourigenesis. Additionally, alterations of 1-C-mediated purine synthesis have been identified as commonly present in brain tumour initiating cells (BTICs) and could serve as a phenotypic marker of cells responsible for tumour recurrence. Further research is required to elucidate mechanisms through which metabolic vulnerabilities may arise in BTICs and potential ways to therapeutically target these metabolic processes. This review aims to summarize the role of 1-C metabolism-associated vulnerabilities in glioblastoma tumourigenesis and progression and investigate the therapeutic potential of targeting this pathway in conjunction with other treatment strategies.

| S-EPMC8235277 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data