A novel patient stratification strategy to enhance the therapeutic efficacy of dasatinib in glioblastoma [Agilent]
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PROVIDER: PRJNA669848 | ENA |
REPOSITORIES: ENA
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Project description:Abstract. Background: Glioblastoma is the most common primary malignancy of the central nervous system with dismal prognosis. Differential gene expression classifies IDH-wildtype glioblastoma into three subtypes: proneural, mesenchymal and classical. Dasatinib, an inhibitor of the proto-oncogene tyrosine-protein kinase SRC, is one of many therapeutics that, despite promising preclinical results, has failed to improve overall survival in glioblastoma patients in clinical trials. We examined whether glioblastoma subtypes differ in their response to dasatinib therapy and could hence be used for patient enrichment strategies in clinical trials. Methods: We carried out in silico analyses of the TCGA glioblastoma gene expression data and single-cell RNA-Seq data, in combination with in vitro experiments using glioblastoma stem-like cells (GSCs) derived from primary patient tumors with complimentary gene expression profiling and immunohistochemistry analyses of tumor samples. Results: Patients suffering from the mesenchymal subtype of glioblastoma showed higher SRC pathway activation based on gene expression profiling, and accordingly, mesenchymal cells were more sensitive to SRC inhibition by dasatinib compared to proneural and classical cells. Furthermore, SERPINH1, a heat-shock protein relevant in many cancer entities, was shown to highly correlate with dasatinib response and with the mesenchymal subtype. Notably, SRC phosphorylation status was not able to reliably predict response to dasatinib treatment. Conclusion: This work highlights the need for rational methods of patient selection for clinical trials, and retrospectively sheds light on a possible gene expression subtype-led patient stratification strategy that could have improved the outcome of SRC inhibition in patients and could have implications for future trials.
2020-10-20 | GSE159605 | GEO
Project description:A novel patient stratification strategy to enhance the therapeutic efficacy of dasatinib in glioblastoma
| PRJNA669855 | ENA
Project description:A novel patient stratification strategy to enhance the therapeutic efficacy of dasatinib in glioblastoma [Illumina]
| PRJNA670013 | ENA
Project description:Abstract. Background: Glioblastoma is the most common primary malignancy of the central nervous system with dismal prognosis. Differential gene expression classifies IDH-wildtype glioblastoma into three subtypes: proneural, mesenchymal and classical. Dasatinib, an inhibitor of the proto-oncogene tyrosine-protein kinase SRC, is one of many therapeutics that, despite promising preclinical results, has failed to improve overall survival in glioblastoma patients in clinical trials. We examined whether glioblastoma subtypes differ in their response to dasatinib therapy and could hence be used for patient enrichment strategies in clinical trials. Methods: We carried out in silico analyses of the TCGA glioblastoma gene expression data and single-cell RNA-Seq data, in combination with in vitro experiments using glioblastoma stem-like cells (GSCs) derived from primary patient tumors with complimentary gene expression profiling and immunohistochemistry analyses of tumor samples. Results: Patients suffering from the mesenchymal subtype of glioblastoma showed higher SRC pathway activation based on gene expression profiling, and accordingly, mesenchymal cells were more sensitive to SRC inhibition by dasatinib compared to proneural and classical cells. Furthermore, SERPINH1, a heat-shock protein relevant in many cancer entities, was shown to highly correlate with dasatinib response and with the mesenchymal subtype. Notably, SRC phosphorylation status was not able to reliably predict response to dasatinib treatment. Conclusion: This work highlights the need for rational methods of patient selection for clinical trials, and retrospectively sheds light on a possible gene expression subtype-led patient stratification strategy that could have improved the outcome of SRC inhibition in patients and could have implications for future trials.
2020-10-20 | GSE159607 | GEO
Project description:This SuperSeries is composed of the SubSeries listed below.
2020-10-20 | GSE159609 | GEO
Project description:BackgroundGlioblastoma is the most common primary malignancy of the central nervous system with a dismal prognosis. Genomic signatures classify isocitrate dehydrogenase 1 (IDH)-wildtype glioblastoma into three subtypes: proneural, mesenchymal, and classical. Dasatinib, an inhibitor of proto-oncogene kinase Src (SRC), is one of many therapeutics which, despite promising preclinical results, have failed to improve overall survival in glioblastoma patients in clinical trials. We examined whether glioblastoma subtypes differ in their response to dasatinib and could hence be evaluated for patient enrichment strategies in clinical trials.MethodsWe carried out in silico analyses on glioblastoma gene expression (TCGA) and single-cell RNA-Seq data. In addition, in vitro experiments using glioblastoma stem-like cells (GSCs) derived from primary patient tumors were performed, with complementary gene expression profiling and immunohistochemistry analysis of tumor samples.ResultsPatients with the mesenchymal subtype of glioblastoma showed higher SRC pathway activation based on gene expression profiling. Accordingly, mesenchymal GSCs were more sensitive to SRC inhibition by dasatinib compared to proneural and classical GSCs. Notably, SRC phosphorylation status did not predict response to dasatinib treatment. Furthermore, serpin peptidase inhibitor clade H member 1 (SERPINH1), a collagen-related heat-shock protein associated with cancer progression, was shown to correlate with dasatinib response and with the mesenchymal subtype.ConclusionThis work highlights further molecular-based patient selection strategies in clinical trials and suggests the mesenchymal subtype as well as SERPINH1 to be associated with response to dasatinib. Our findings indicate that stratification based on gene expression subtyping should be considered in future dasatinib trials.
| S-EPMC8730774 | biostudies-literature
Project description:The strategy of a novel way to enhance bacterial motility
| PRJNA693394 | ENA
Project description:Gene profiles from three dasatinib-resistant and three dasatinib-sensitive pancreatic cancer cell lines were compared by microarray analysis.
2015-02-24 | GSE59357 | GEO
Project description:Gene profiles from three dasatinib-resistant and three dasatinib-sensitive pancreatic cancer cell lines were compared by microarray analysis. RNA from three dasatinib-resistant (MiaPaCa2, Panc1, SU8686) and three dasatinib-sensitive (Panc0504, Panc0403, Panc1005) pancreatic cancer cell lines were extracted. Biological triplicates were employed for each cell line. Complementary DNA microarray analysis was performed using Illumina Human HT-12 v4 BeadChip (Illumina, San Diego, CA) at the National University of Singapore Core Facility following the manufacturer’s instructions.
2015-02-24 | E-GEOD-59357 | biostudies-arrayexpress
Project description:Dasatinib has demonstrated efficacy in patients with chronic-phase chronic myeloid leukemia (CML) who had resistance or intolerance to imatinib. However, some patients also develop resistance or intolerance to dasatinib. To identify potential molecular pathways involved in primary resistance to dasatinib in CML, we analyzed gene expression profiles of mononuclear cells of 7 imatinib-resistant patients, collected before and after 1-year dasatinib treatment. Large-scale gene expression was measured with Agilent microarrays covering protein-coding genes and long (>200 nt) noncoding RNAs (lncRNAs). Sets of genes and lncRNAs significantly differentially expressed (>1.5 fold-change; q value ≤10%) were identified. Ingenuity Pathway Analysis pointed to a number of functions, canonical pathways and gene networks that were significantly enriched with differentially expressed genes. In addition to protein-coding genes, lncRNAs have been recently implicated in pathways leading to tumorigenesis. Our data point to new possible regulatory elements involved in dasatinib resistance in CML.
2013-07-31 | GSE33290 | GEO