Expression data of progesterone regulated miRNAs in U251 cells, derived from human glioblastoma
Ontology highlight
ABSTRACT:
ORGANISM(S): synthetic construct Homo sapiens
PROVIDER: GSE144204 | GEO | 2020/01/25
REPOSITORIES: GEO
Similar Datasets
Project description:In this study was determined the global expression pattern of long non-coding RNAs, mRNAs, and miRNAs in pediatric astrocytoma of different histological grades. The Affymetrix HTA 2.0 array showed expression changes on one hundred-sixty two and two hundred-fifteen long non-coding RNAs in tumors (versus the control) and in GBM (versus low-grade astrocytoma), respectively. A total of seven astrocytic tumors and two control tissues were collected during the period of 2012–2014: four low-grade Ast (three pilocytic Ast (PAst) and one diffuse Ast (DAst)) and four high-grade Ast (four glioblastoma multiforme (GBM)).RNA was extracted from tissue samples using TRIzol (Ambion life technologies, Thermo Scientific Inc.) following the methodology described by Hongbao et al. 2008 and with certain modifications described by Vujovic et al. 2013. For expression analysis, Human Transcriptome Array 2.0 (HTA) (Santa Clara, CA, USA) was employed. in this study was determined the global expression pattern of long non-coding RNAs, mRNAs, and miRNAs in pediatric astrocytoma of different histological grades. The HTA 2.0 array showed expression changes on one hundred-sixty two and two hundred-fifteen long non-coding RNAs in tumors (versus the control) and in GBM (versus low-grade astrocytoma), respectively.
2015-08-25 | E-GEOD-72269 | biostudies-arrayexpress
Project description:In this study was determined the global expression pattern of long non-coding RNAs, mRNAs, and miRNAs in pediatric astrocytoma of different histological grades. The Affymetrix HTA 2.0 array showed expression changes on one hundred-sixty two and two hundred-fifteen long non-coding RNAs in tumors (versus the control) and in GBM (versus low-grade astrocytoma), respectively.
2015-08-25 | GSE72269 | GEO
Project description:Glioblastoma (GBM) is the most aggressive form of astrocytoma and is difficult to diagnose at early stage. In this study, our goal is to find and validate biomarkers for GBM through serum proteome expression profiling, which would assist in the early diagnosis, and management of GBMs. In the discovery phase, we performed shotgun proteomics of control and GBM pooled serum samples using untargeted 4-plex iTRAQ (isobaric Tags for Relative and Absolute Quantitation) mass spectrometry to identify candidate biomarkers with differential abundance The two candidates, S100A8 and S100A9 were prioritized for verification based on their maximal abundance in GBM serum in our discovery phase.
2019-03-04 | PXD012207 | Pride
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: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-58399 | biostudies-arrayexpress
Project description:Clinical studies have linked use of progestins (synthetic progesterone (P4)) to breast cancer risk. However, little is understood regarding the role native P4, signaling through the progesterone receptor (PR), plays in formation of breast tumors. Studies published by our lab highlighted a link between PR and immune signaling pathways, suggesting PR induces PR to repress the interferon signaling pathway. Given these findings, we sought to investigate whether P4/PR drive immunomodulation in the mammary gland and development of mammary gland tumors. We found that mice treated with P4 displayed changes in the mammary gland suggesting inhibited immune response compared to placebo-treated mice. Furthermore, transgenic mice with PR overexpression demonstrated decreased numbers of immune cell populations in their mammary gland, lymph nodes, and spleens. Upon long-term monitoring, we determined that multi-parous PR overexpressing mice developed significantly more mammary gland tumors than control mice. Additionally, tumors of PR overexpressing mice contained fewer infiltrating immune cells. Finally, RNA sequencing analysis of tumor samples revealed that immune-related gene signatures were enriched in tumors of control mice compared to tumors of PR overexpressing mice. Together, these findings provide a novel mechanism behind P4-mediated promotion of mammary gland tumor development and provide rationale to investigate anti-progestin treatment to promote immune-mediated elimination of mammary gland tumors.
2021-09-15 | GSE158134 | GEO
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.
2014-06-12 | GSE58399 | GEO
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.
2014-06-12 | GSE58400 | GEO
Project description:GBM mouse model: The goal of this study is to compare the transcriptomic landscape at the endpoint of GBMs upon senescent cells deletion. We introduced the p16-3MR transgene in the GBM mouse model to selectively delete senescent cells expressing high level of p16Ink4a (p16Ink4a Hi) upon ganciclovir (GCV) injection. We compared p16-3MR+GCV GBMs to two control conditions, either WT+GCV or p16-3MR+GCV. We showed a slight decreased of p16Ink4a transcripts in p16-3MR+GCV compared to WT+GCV GBMs and GSEA demonstrated significant down-regulation of senescence pathways in p16-3MR+GCV GBMs compared to control GBMs. GBM-derived organoids: We used a mouse GBM-derived organoids model to further explore the function of Nrf2, that we identified as one potential trigger of the pro-tumoral action of p16Ink4a Hi malignant cells. We compared GBM-derived organoids treated with the senolytic ABT263 (Navitoclax; inhibitor of the anti-apoptotic proteins Blcl2 and BCL-xL) or vehicle (vhc) after 14 days in culture. We validated ABT263 efficacy via the significant downregulation of the expression of p16Ink4a, p15Ink4b and p21Cip1 senescent markers. We further identified upon senolytic treatment, downregulated genes encoding for SASP. Importantly, GSEA revealed a significant downregulation of Nrf2 pathway upon senolytic treatment.
2022-12-15 | GSE168037 | GEO
Project description:Glioblastomas (GBMs) are highly aggressive, infiltrative, and heterogeneous brain tumors driven by complex driver mutations and glioma stem cells (GSCs). The neurodevelopmental transcription factors ASCL1 and OLIG2 are co-expressed in GBMs, but their role in regulating the heterogeneity and hierarchy of GBM tumor cells is unclear. Here, we show that oncogenic driver mutations lead to dysregulation of ASCL1 and OLIG2, which function redundantly to initiate brain tumor formation in a mouse model of GBM. Subsequently, the dynamic levels and reciprocal binding of ASCL1 and OLIG2 to each other and to downstream target genes then determine the cell types and degree of migration of tumor cells. Single-cell RNA sequencing (scRNA-seq) reveals that a high level of ASCL1 is key in defining GSCs by upregulating a collection of ribosomal protein, mitochondrial, neural stem cell (NSC), and cancer metastasis genes – all essential for sustaining the high proliferation, migration, and therapeutic resistance of GSCs.
2024-06-30 | GSE247977 | GEO