Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA401890 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Mouse models have been developed to investigate colorectal cancer etiology and evaluate new anti-cancer therapies. While genetically engineered and carcinogen-induced mouse models have provided important information with regard to the mechanisms underlying the oncogenic process, xenograft models remain the standard for the evaluation of new chemotherapy and targeted drug treatments for clinical use. However, it remains unclear if drug efficacy data obtained from xenograft models translate into clinically-relevant treatment modalities. In this study, we have generated a panel of 28 patient-derived colorectal cancer explants (PDCCEs), an extension of our previous work, by direct transplantation of human colorectal cancer (CRC) tissues into NOD-SCID mice. A comprehensive histological and molecular evaluation of PDCCEs and their corresponding patient tumor demonstrates that PDCCEs maintain histological features and global biology through multiple passages. Furthermore, we demonstrate that in vivo sensitivity of PDCCEs to oxaliplatin can predict patient outcomes. Our findings suggest that PDCCEs maintain similarity to the patient tumor from which they are derived and can serve as a reliable preclinical model that can be incorporated into future strategies to optimize individual therapy for patients with CRC. 28 human primary colorectal and 37 mouse derived colorectal explant tumors
2012-06-06 | E-GEOD-35144 | biostudies-arrayexpress
Project description:Mouse models have been developed to investigate colorectal cancer etiology and evaluate new anti-cancer therapies. While genetically engineered and carcinogen-induced mouse models have provided important information with regard to the mechanisms underlying the oncogenic process, xenograft models remain the standard for the evaluation of new chemotherapy and targeted drug treatments for clinical use. However, it remains unclear if drug efficacy data obtained from xenograft models translate into clinically-relevant treatment modalities. In this study, we have generated a panel of 28 patient-derived colorectal cancer explants (PDCCEs), an extension of our previous work, by direct transplantation of human colorectal cancer (CRC) tissues into NOD-SCID mice. A comprehensive histological and molecular evaluation of PDCCEs and their corresponding patient tumor demonstrates that PDCCEs maintain histological features and global biology through multiple passages. Furthermore, we demonstrate that in vivo sensitivity of PDCCEs to oxaliplatin can predict patient outcomes. Our findings suggest that PDCCEs maintain similarity to the patient tumor from which they are derived and can serve as a reliable preclinical model that can be incorporated into future strategies to optimize individual therapy for patients with CRC.
2012-06-07 | GSE35144 | GEO
Project description:Prostate cancer discovery and translational research are hampered by a lack of preclinical models which accurately reproduce the biological heterogeneity observed in patients. Accordingly, we have established a bank of transplantable patient-derived prostate tumor xenograft lines, using subrenal capsule grafting of human tumor tissue into immuno-deficient mice. This panel includes the first lines generated from primary prostate cancer tissue, and also new lines from metastatic tissue. Critically, the lines retained salient features of the original patient tumors, including histopathology, clinical marker expression, chromosomal aberration and gene expression profiles. Furthermore, they span major histopathological and molecular subtypes of prostate cancer, capturing diverse inter- and intra-tumoral heterogeneity. Host castration led to the development of castrate-resistant tumors, including the first model of complete neuroendocrine transdifferentiation. This publicly-available resource provides novel tools to advance mechanistic understanding of disease progression and response to therapy, and delivers clinically-relevant model systems for evaluation of preclinical drug efficacy. 3 primary tumors and 21 xenograft tumors
2013-01-12 | E-GEOD-41188 | biostudies-arrayexpress
Project description:Prostate cancer discovery and translational research are hampered by a lack of preclinical models which accurately reproduce the biological heterogeneity observed in patients. Accordingly, we have established a bank of transplantable patient-derived prostate tumor xenograft lines, using subrenal capsule grafting of human tumor tissue into immuno-deficient mice. This panel includes the first lines generated from primary prostate cancer tissue, and also new lines from metastatic tissue. Critically, the lines retained salient features of the original patient tumors, including histopathology, clinical marker expression, chromosomal aberration and gene expression profiles. Furthermore, they span major histopathological and molecular subtypes of prostate cancer, capturing diverse inter- and intra-tumoral heterogeneity. Host castration led to the development of castrate-resistant tumors, including the first model of complete neuroendocrine transdifferentiation. This publicly-available resource provides novel tools to advance mechanistic understanding of disease progression and response to therapy, and delivers clinically-relevant model systems for evaluation of preclinical drug efficacy. 3 primary tumors and 22 xenograft tumors
2013-01-12 | E-GEOD-41192 | 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: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:Pancreatic neuroendocrine tumor (PanNET) is relatively infrequent but is nevertheless metastatic. Seeking to extend a new paradigm of personalized medicine, we performed an integrative analysis of transcriptomic (mRNA and microRNA) and mutational profiles and defined three clinically relevant human PanNET subtypes. Importantly, cross-species analysis revealed two of these three subtypes in a well-characterized, genetically engineered mouse model (RIP1-Tag2) of PanNET and its cell lines. Each subtype share similarities to distinct cell types in pancreatic neuroendocrine development, features are reflected in their metabolic profiles. Subtype-specific molecular signatures metabolites are proposed to identify these subtypes. RNA was extracted from fresh frozen archival patient PanNET samples and hybridized on Affymetrix GeneChip human Gene 1.0 ST arrays. The CEL files were processed using R based bioconductor and normalized values were obtained using RMA.
2015-10-30 | E-GEOD-73339 | biostudies-arrayexpress
Project description:Resistance to androgen deprivation therapies leads to metastatic castration-resistant prostate cancer (mCRPC) of adenocarcinoma (AdCa) origin that can transform to emergent aggressive variant prostate cancer (AVPC) which has neuroendocrine (NE)-like features. To this end, we used LuCaP patient-derived xenograft (PDX) tumors, clinically relevant models that reflects and retains key features of the tumor from advanced prostate cancer patients. Here we performed proteome and phosphoproteome characterization of 48 LuCaP PDX tumors and identified over 94,000 peptides and 9,700 phosphopeptides corresponding to 7,738 proteins. When we compared 15 NE versus 33 AdCa PDX samples, we identified 309 unique proteins and 476 unique phosphopeptides that were significantly altered and corresponded to proteins that are known to distinguish these two phenotypes. Assessment of protein and RNA concordance from these tumors revealed increased dissonance in transcriptionally regulated proteins in NE and metabolite interconversion enzymes in AdCa.
Keywords: Proteomics, phosphoproteomics, Neuroendocrine, Adenocarcinoma, biomarkers, surfaceome, secretome, blood proteins, prostate cancer, patient-derived xenograft
2023-06-09 | MSV000092139 | MassIVE
Project description:This project describes the establishment and validation of a murine orthotopic xenograft model using fresh human tumor samples that recapitulates the critical components of human pancreatic adenocarcinoma. The authors discuss the proven and theoretical advantages of the model as well as future translational implications. Background: Relevant preclinical models that recapitulate the key features of human pancreatic ductal adenocarcinoma (PDAC) are needed in order to provide biologically tractable models to probe disease progression and therapeutic responses and ultimately improve patient outcomes for this disease. Here, we describe the establishment and clinical, pathological, molecular and genetic validation of a murine, orthotopic xenograft model of PDAC. Methods: Human PDACs were resected and orthotopically implanted and propagated in immunocompromised mice. Patient survival was correlated with xenograft growth and metastatic rate in mice. Human and mouse tumor pathology were compared. Tumors were analyzed for genetic mutations, gene expression, receptor tyrosine kinase (RTK) activation, and cytokine expression. Results: Fifteen human PDACs were propagated orthotopically in mice. Xenografts developed peritoneal and liver metastases. Time to growth and metastatic efficiency in mice each correlated with patient survival. Tumor architecture, nuclear grade and stromal content were similar in patient and xenografted tumors. Propagated tumors closely exhibited the genetic and molecular features known to characterize pancreatic cancer (e.g. high rate of KRAS, p53, SMAD4 mutation and EGFR activation). The correlation coefficient of gene expression between patient tumors and xenografts propagated through multiple generations was 93 to 99%. Analysis of gene expression demonstrated distinct differences between xenografts from fresh patient tumors versus commercially available PDAC cell lines. Conclusions: Our orthotopic xenograft model derived from fresh human PDACs closely recapitulates the clinical, pathologic, genetic and molecular aspects of human disease. This model has resulted in the identification of rational therapeutic strategies to be tested in clinical trials and will permit additional therapeutic approaches and identification of biomarkers of response to therapy. 47 Samples in total were generated for normal pancreatic tissue in patients, pancreatic tumors in patients, pancreatic tumors propagated in a mouse xenograft model, and pancreatic cancer cell lines in vitro. Clustering analysis was performed to evaluate the differences between patient tumors, xenograft tumors, established cancer cell lines, and cell lines derived from xenografts.
2013-10-01 | E-GEOD-46385 | biostudies-arrayexpress
Project description:Generation of an in vitro 3D Engineered Colorectal Cancer Patient-Derived Xenograft Model
| PRJNA634542 | ENA