Localized metabolomic gradients in patient-derived xenograft models of glioblastoma
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB35120 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| ERR3625080_1.fastq.gz | Fastqsanger.gz | |||
| ERR3625080_2.fastq.gz | Fastqsanger.gz | |||
| ERR3625081_1.fastq.gz | Fastqsanger.gz | |||
| ERR3625081_2.fastq.gz | Fastqsanger.gz | |||
| ERR3625082_1.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 12 |
Similar Datasets
Project description:Glioblastoma (GBM) is increasingly recognized as a disease involving dysfunctional cellular metabolism. GBMs are known to be complex heterogeneous systems containing multiple distinct cell populations and are supported by an aberrant network of blood vessels. A better understanding of GBM metabolism, its variation with respect to the tumor microenvironment, and resulting regional changes in chemical composition is required. This may shed light on the observed heterogeneous drug distribution, which cannot be fully described by limited or uneven disruption of the blood-brain barrier. In this work, we used mass spectrometry imaging (MSI) to map metabolites and lipids in patient-derived xenograft models of GBM. A data analysis workflow revealed that distinctive spectral signatures were detected from different regions of the intracranial tumor model. A series of long-chain acylcarnitines were identified and detected with increased intensity at the tumor edge. A 3D MSI dataset demonstrated that these molecules were observed throughout the entire tumor/normal interface and were not confined to a single plane. mRNA sequencing demonstrated that hallmark genes related to fatty acid metabolism were highly expressed in samples with higher acylcarnitine content. These data suggest that cells in the core and the edge of the tumor undergo different fatty acid metabolism, resulting in different chemical environments within the tumor. This may influence drug distribution through changes in tissue drug affinity or transport and constitute an important consideration for therapeutic strategies in the treatment of GBM. SIGNIFICANCE: GBM tumors exhibit a metabolic gradient that should be taken into consideration when designing therapeutic strategies for treatment.See related commentary by Tan and Weljie, p. 1231.
| S-EPMC7073296 | biostudies-literature
Project description:This SuperSeries is composed of the following subset Series: GSE38814: Glioblastoma Orthotopic Xenograft Transcriptome GSE38815: Glioblastoma Xenograft Comparative Genomic Hybridization Arrays Refer to individual Series
2012-07-10 | E-GEOD-39242 | biostudies-arrayexpress
Project description:Expression data from glioblastoma derived xenograft and original glioblastoma tumors
| PRJNA1172693 | ENA
Project description:Frequent discrepancies between preclinical and clinical results of anti-cancer agents demand a reliable translational platform that can precisely recapitulate the biology of human cancers. Another critical unmet need is the ability to predict therapeutic responses for individual patients. Toward this goal, we have established a library of orthotopic glioblastoma (GBM) xenograft models using surgical samples of GBM patients. These patient-specific GBM xenograft tumors recapitulate histopathological properties and maintain genomic characteristics of parental GBMs in situ. Furthermore, in vivo irradiation, chemotherapy, and targeted therapy of these xenograft tumors mimic the treatment response of parental GBMs. We also found that establishment of orthotopic xenograft models portends poor prognosis of GBM patients and identified the gene signatures and pathways signatures associated with the clinical aggressiveness of GBMs. Together, the patient-specific orthotopic GBM xenograft library represent the preclinically and clinically valuable “patient tumor’s phenocopy” that represents molecular and functional heterogeneity of GBMs. aCGH experiments were performed for a human glioblastoma tissue (sample ID: PC-NS08-559) and the matching xenograft tumor tissue using the Agilent Human Whole Genome CGH 244K microarray according to manufacturer's protocol (2-color).
2013-01-18 | E-GEOD-42577 | biostudies-arrayexpress
Project description:Transcriptional profiling of glioblastoma orthotopic xenografts Descriptive experiment, comparison of 39 glioblastoma tumors as orthotopic xenografts
2012-07-10 | E-GEOD-38814 | biostudies-arrayexpress
Project description:Frequent discrepancies between preclinical and clinical results of anti-cancer agents demand a reliable translational platform that can precisely recapitulate the biology of human cancers. Another critical unmet need is the ability to predict therapeutic responses for individual patients. Toward this goal, we have established a library of orthotopic glioblastoma (GBM) xenograft models using surgical samples of GBM patients. These patient-specific GBM xenograft tumors recapitulate histopathological properties and maintain genomic characteristics of parental GBMs in situ. Furthermore, in vivo irradiation, chemotherapy, and targeted therapy of these xenograft tumors mimic the treatment response of parental GBMs. We also found that establishment of orthotopic xenograft models portends poor prognosis of GBM patients and identified the gene signatures and pathways signatures associated with the clinical aggressiveness of GBMs. Together, the patient-specific orthotopic GBM xenograft library represent the preclinically and clinically valuable “patient tumor’s phenocopy” that represents molecular and functional heterogeneity of GBMs. Gene expression profiling experiments were conducted for 58 human glioblastoma samples using Affymetrix Human Gene 1.0 ST arrays according to manufacturer's protocol.
2013-01-18 | E-GEOD-42669 | biostudies-arrayexpress
Project description:Panobinostat is a non-selective histone deactylase inhibitor which has been approved by FDA for treatment of mutiple myeloma. Whether and how the drug works on glioblastoma remains unclear. Here we treated mice implanted with patient derived xenograft glioblastoma G43 with DMSO or Panobinostat and harvest the tumors for microarray analysis for gene expression results.
2019-01-09 | GSE108957 | GEO
Project description:Glioblastoma (GBM) is among the most aggressive cancers. Despite aggressive radiotherapy and treatment with the alkylating agent temozolomide (TMZ), patients ultimately succumb to the disease. Although much interest has focused on highly tumorigenic GBM stem cells (GSCs), adaption of a concept from microbial research proposes that a minor population of dormant âpersisterâ cells in cancer evade current therapies. To separate dormant and treatment-resistant tumor cells in human GBM tumorspheres, we have refined density gradient protocols previously used for separation of neurosphere-forming neural stem cells (NSCs). We find that a minor cell population in human GBM tumorsphere cultures and patient-derived tumor biopsies display increased cell density. These high-density GBM cells (HDGCs) display dormancy, variable expression of proposed GSC markers, and 10-100 fold higher levels of reprogramming gene expression compared to low-density GBM cells (LDGCs). Transcriptional profiling data confirmed the slow-cycling state of HDGCs. As a result, HDGCs show decreased tumorsphere formation capacity in vitro and reduced tumorigenicity in vivo. Using tumorspheres and xenografts, we demonstrated that HDGCs show increased treatment-resistance to ionizing radiation (IR) and temozolomide treatment compared to LDGCs. Similar to the NSC lineage, our data suggest that dormant HDGCs become increasingly sensitive to anti-proliferative therapies as they become activated and further differentiate. In conclusion, density gradients represents a marker-independent approach to separate dormant and treatment-resistant tumor cells in human GBMs and other solid cancers. 12 samples, no replicates, derived from 5 individual patients
2016-07-01 | E-GEOD-71116 | biostudies-arrayexpress
Project description:Glioblastoma (GBM) heterogeneity in the genomic and phenotypic properties has potentiated personalized approach against specific therapeutic targets of each GBM patient. The Cancer Genome Atlas (TCGA) Research Network has been established the comprehensive genomic abnormalities of GBM, which sub-classified GBMs into 4 different molecular subtypes. The molecular subtypes could be utilized to develop personalized treatment strategy for each subtype. We applied a classifying method, NTP (Nearest Template Prediction) method to determine molecular subtype of each GBM patient and corresponding orthotopic xenograft animal model. The models were derived from GBM cells dissociated from patient's surgical sample. Specific drug candidates for each subtype were selected using an integrated pharmacological network database (PharmDB), which link drugs with subtype specific genes. Treatment effects of the drug candidates were determined by in vitro limiting dilution assay using patient-derived GBM cells primarily cultured from orthotopic xenograft tumors. The consistent identification of molecular subtype by the NTP method was validated using TCGA database. When subtypes were determined by the NTP method, orthotopic xenograft animal models faithfully maintained the molecular subtypes of parental tumors. Subtype specific drugs not only showed significant inhibition effects on the in vitro clonogenicity of patient-derived GBM cells but also synergistically reversed temozolomide resistance of MGMT-unmethylated patient-derived GBM cells. However, inhibitory effects on the clonogenicity were not totally subtype-specific. Personalized treatment approach based on genetic characteristics of each GBM could make better treatment outcomes of GBMs, although more sophisticated classifying techniques and subtype specific drugs need to be further elucidated. Gene expression profiling experiments were conducted for 25 patient-derived xenograft glioblastoma samples using Affymetrix Human Gene 1.0 ST arrays according to manufacturer's protocol.
2014-06-12 | E-GEOD-58400 | biostudies-arrayexpress
Project description:DNA copy number profiling of 32 glioblastoma orthotopic xenografts Descriptive experiment, comparison of 39 glioblastoma tumors as orthotopic xenografts flow sorted for anueploidy
2012-07-10 | E-GEOD-38815 | biostudies-arrayexpress