Predicting drug response in human prostate cancer from preclinical analysis of in vivo mouse models
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PROVIDER: PRJNA284909 | ENA |
REPOSITORIES: ENA
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Project description:Analysis of the transcriptome of mouse models of prostate cancer after treatment with rapamycin and PD0325901 combination therapy or standard of care docetaxel. The Nkx3.1CreERT2/+; Ptenflox/flox; KrasLSL-G12D/+ (NPK mice) was used in this study. Two months after tumor induction, mice were randomly assigned to vehicle (Veh) or treatments groups, such as rapamycin and PD0325901 (RAPPD) or docetaxel (Docetaxel). For the treatment groups mice were administered rapamycin (10 mg/kg) and PD0325901 (10 mg/kg) or docetaxel (10 mg/kg) for 5 days (SHORT) or for 1 month (LONG). At the end of the treatment, mice were euthanized, tumors harvested and snap frozen for subsequent molecular analysis. Total RNA obtained from prostate tumors/tissues. Prostate tumors/tissues were harvested and processed for RNA isolation and transcriptome analysis using the MagMAX RNA isolation kit (Ambion). Total RNA was amplified and labelled for subsequent microarrays hybridization using the Illumina TotalPrep RNA Amplification Kit.
2015-09-17 | E-GEOD-69211 | biostudies-arrayexpress
Project description:Rational selection of syngeneic preclinical tumor models for immunotherapeutic drug discovery
| PRJNA338671 | ENA
Project description:Analysis of the transcriptome of mouse models of prostate cancer after treatment with rapamycin and PD0325901 combination therapy or standard of care docetaxel. The Nkx3.1CreERT2/+; Ptenflox/flox; KrasLSL-G12D/+ (NPK mice) was used in this study. Two months after tumor induction, mice were randomly assigned to vehicle (Veh) or treatments groups, such as rapamycin and PD0325901 (RAPPD) or docetaxel (Docetaxel). For the treatment groups mice were administered rapamycin (10 mg/kg) and PD0325901 (10 mg/kg) or docetaxel (10 mg/kg) for 5 days (SHORT) or for 1 month (LONG). At the end of the treatment, mice were euthanized, tumors harvested and snap frozen for subsequent molecular analysis.
2015-09-17 | GSE69211 | GEO
Project description:This SuperSeries is composed of the SubSeries listed below. Refer to individual Series
2015-09-17 | E-GEOD-69214 | biostudies-arrayexpress
Project description:Analysis of the transcriptome of allografted mouse tumors after treatment with rapamycin and PD0325901. Nkx3.1CreERT2/+; Ptenflox/flox; KrasLSL-G12D/+ (NPK mice) were induced and their tumors removed to generate allograft lines by implanting a 1.5 mm3 tumor fragment in the subcutaneous space of athymic nude mice. Allografted NPK tumors were allowed to grow until they reached a volume of 1 cm3, at which moment they were randomly assigned to either vehicle (Veh) or combination therapy using rapamycin and PD0325901 (RAPPD). Allografted mice were administered rapamycin (10 mg/kg) and PD0325901 (10 mg/kg) during five consecutive days (Allo SHORT). Mice were euthanized in the fifth day 6 hours after having received the last treatment and the tumors were harvested and snap frozen for subsequent molecular analysis. Total RNA obtained from prostate tumors/tissues. Prostate tumors/tissues were harvested and processed for RNA isolation and transcriptome analysis using the MagMAX RNA isolation kit (Ambion). Total RNA was amplified and labelled for subsequent microarrays hybridization using the Illumina TotalPrep RNA Amplification Kit.
2015-09-17 | E-GEOD-69213 | biostudies-arrayexpress
Project description:This SuperSeries is composed of the SubSeries listed below.
2015-09-17 | GSE69214 | GEO
Project description:Although genetically engineered mouse (GEM) models are often used to evaluate cancer therapies, extrapolation of such preclinical data to human cancer can be challenging. Here, we introduce an approach that uses drug perturbation data from GEM models to predict drug efficacy in human cancer. Network-based analysis of expression profiles from in vivo treatment of GEM models identified drugs and drug combinations that inhibit the activity of FOXM1 and CENPF, which are master regulators of prostate cancer malignancy. Validation of mouse and human prostate cancer models confirmed the specificity and synergy of a predicted drug combination to abrogate FOXM1/CENPF activity and inhibit tumorigenicity. Network-based analysis of treatment signatures from GEM models identified treatment-responsive genes in human prostate cancer that are potential biomarkers of patient response. More generally, this approach allows systematic identification of drugs that inhibit tumor dependencies, thereby improving the utility of GEM models for prioritizing drugs for clinical evaluation.
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Project description:Analysis of the transcriptome of allografted mouse tumors after treatment with rapamycin and PD0325901. Nkx3.1CreERT2/+; Ptenflox/flox; KrasLSL-G12D/+ (NPK mice) were induced and their tumors removed to generate allograft lines by implanting a 1.5 mm3 tumor fragment in the subcutaneous space of athymic nude mice. Allografted NPK tumors were allowed to grow until they reached a volume of 1 cm3, at which moment they were randomly assigned to either vehicle (Veh) or combination therapy using rapamycin and PD0325901 (RAPPD). Allografted mice were administered rapamycin (10 mg/kg) and PD0325901 (10 mg/kg) during five consecutive days (Allo SHORT). Mice were euthanized in the fifth day 6 hours after having received the last treatment and the tumors were harvested and snap frozen for subsequent molecular analysis.
2015-09-17 | GSE69213 | GEO
Project description:The therapeutic regimens of adjuvant and neoadjuvant chemotherapy for colorectal cancer (CRC) remain largely relied on clinical experience, and thus preclinical models are needed to guide individualized medicine. The investigators are going to establish 3D bioprinted CRC models and organoids from surgically resected tumor tissues of CRC patients with or without liver metastases. In vitro 3D models and organoids will be treated with the same chemotherapy drugs with the corresponding patients from whom the models are derived. The sensitivity of chemotherapy drugs will be tested in these two types of in vitro models, and the actual response to chemotherapy in patients will be evaluated. The predictive ability of 3D models for chemotherapy sensitivity in CRC patients will be compared with that of the organoids. This observational study will validate the potential value of 3D bioprinted tumor models in predicting the response to chemotherapy in CRC.
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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