Ontology highlight
ABSTRACT:
PROVIDER: PRJNA506146 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Murine syngeneic tumor models
| PRJNA314697 | ENA
Project description:Bulk RNA sequencing analysis of murine syngeneic orthotopic GL261-luc2 and CT2A-luc glioblastoma tumour models
2023-11-01 | GSE215123 | GEO
Project description:Murine syngeneic tumor models are the cornerstone of novel immuno-oncology (IO)-based therapy development but the molecular and immunological features of these models are still not clearly defined. The translational relevance of differences between the models is not fully understood, impeding appropriate preclinical model selection for target validation, and ultimately hindering drug development. Within a panel of commonly-used murine syngeneic tumor models, we showed variable responsiveness to IO-therapies. We employed aCGH, whole-exome sequencing, exon microarray analysis and flow cytometry to extensively characterise these models and revealed striking differences that may underlie these contrasting response profiles. We identified strong differential gene expression in immune-related pathways and changes in immune cell-specific genes that suggested differences in tumor immune infiltrates between models. We further investigated this using flow cytometry, which showed differences in both the composition and magnitude of the tumor immune infiltrates, identifying models that harbor ‘inflamed’ and ‘non-inflamed’ tumor immune infiltrate phenotypes. Moreover, we found that immunosuppressive cell types predominated in syngeneic mouse tumor models that did not respond to immune-checkpoint blockade, whereas cytotoxic effector immune cells were enriched in responsive models. A cytotoxic cell-rich tumor immune infiltrate has been correlated with increased efficacy of IO-therapy in the clinic and these differences could underlie the varying response profiles to IO-therapy between the syngeneic models. This characterisation highlighted the importance of extensive profiling and will enable investigators to select appropriate models to interrogate the activity of IO-therapies as well as combinations with targeted therapies in vivo.
2016-12-07 | GSE85508 | GEO
Project description:We examined the effects of an oral small molecule DPP inhibitor (BXCL701) on PDAC tumor growth and tumor immune landscape using mT3-2D and Pan02 subcutaneous syngeneic murine models in C57BL/6 mice
2024-04-22 | GSE173441 | GEO
Project description:Murine syngeneic tumor models are the cornerstone of novel immuno-oncology (IO)-based therapy development but the molecular and immunological features of these models are still not clearly defined. The translational relevance of differences between the models is not fully understood, impeding appropriate preclinical model selection for target validation, and ultimately hindering drug development. Within a panel of commonly-used murine syngeneic tumor models, we showed variable responsiveness to IO-therapies. We employed aCGH, whole-exome sequencing, exon microarray analysis and flow cytometry to extensively characterise these models and revealed striking differences that may underlie these contrasting response profiles. We identified strong differential gene expression in immune-related pathways and changes in immune cell-specific genes that suggested differences in tumor immune infiltrates between models. We further investigated this using flow cytometry, which showed differences in both the composition and magnitude of the tumor immune infiltrates, identifying models that harbor ‘inflamed’ and ‘non-inflamed’ tumor immune infiltrate phenotypes. Moreover, we found that immunosuppressive cell types predominated in syngeneic mouse tumor models that did not respond to immune-checkpoint blockade, whereas cytotoxic effector immune cells were enriched in responsive models. A cytotoxic cell-rich tumor immune infiltrate has been correlated with increased efficacy of IO-therapy in the clinic and these differences could underlie the varying response profiles to IO-therapy between the syngeneic models. This characterisation highlighted the importance of extensive profiling and will enable investigators to select appropriate models to interrogate the activity of IO-therapies as well as combinations with targeted therapies in vivo.
2016-12-07 | GSE85507 | GEO
Project description:Mutations in isocitrate dehydrogenase 2 (IDH2) occur in many cancers including Acute Myeloid Leukemia (AML). In preclinical models mutant IDH2 causes partial hemopoietic differentiation arrest. Recently, we showed that single agent Enasidenib, a first-in-class, selective mutant IDH2 inhibitor, produces a 40% response in relapsed/refractory AML patients by promoting differentiation. Yet, the rate, extend and duration of the clinical benefits of Enasidenib vary from one patient to another. To investigate how the genetic mutational landscape, at baseline or at relapse, contributes in modulating response to Enasidenib, WES analyses on FACS-sorted blasts from baseline, best response and/or relapse samples from 16 Enasidenib-treated patients were performed. WES analyses were also performed on the CD3+ cells from the same patients, which may be used as germinal control samples.
2018-08-13 | E-MTAB-6299 | biostudies-arrayexpress
Project description:WES was used to analyze the mutational landscape of KPC and Panc02, two murine pancreatic cancer cell lines. As expected, a relatively low mutational burden was identified in KPC cells.
2021-04-15 | GSE172105 | GEO