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PROVIDER: PRJNA182599 | ENA |
REPOSITORIES: ENA
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Project description:Patient specific orthotopic glioblastoma xenograft models recapitulate the histopathology and biology of human glioblastomas in situ (CGH)
| PRJNA182600 | ENA
Project description:Patient specific orthotopic glioblastoma xenograft models recapitulate the histopathology and biology of human glioblastomas in situ (gene expression)
| PRJNA182601 | ENA
Project description:Frequent discrepancies between preclinical and clinical results of anti-cancer agents demand a reliable translational platform that can precisely recapitulate the biology of human cancers. Another critical unmet need is the ability to predict therapeutic responses for individual patients. Toward this goal, we have established a library of orthotopic glioblastoma (GBM) xenograft models using surgical samples of GBM patients. These patient-specific GBM xenograft tumors recapitulate histopathological properties and maintain genomic characteristics of parental GBMs in situ. Furthermore, in vivo irradiation, chemotherapy, and targeted therapy of these xenograft tumors mimic the treatment response of parental GBMs. We also found that establishment of orthotopic xenograft models portends poor prognosis of GBM patients and identified the gene signatures and pathways signatures associated with the clinical aggressiveness of GBMs. Together, the patient-specific orthotopic GBM xenograft library represent the preclinically and clinically valuable “patient tumor’s phenocopy” that represents molecular and functional heterogeneity of GBMs. Gene expression profiling experiments were conducted for 58 human glioblastoma samples using Affymetrix Human Gene 1.0 ST arrays according to manufacturer's protocol.
2013-01-18 | E-GEOD-42669 | biostudies-arrayexpress
Project description:Frequent discrepancies between preclinical and clinical results of anti-cancer agents demand a reliable translational platform that can precisely recapitulate the biology of human cancers. Another critical unmet need is the ability to predict therapeutic responses for individual patients. Toward this goal, we have established a library of orthotopic glioblastoma (GBM) xenograft models using surgical samples of GBM patients. These patient-specific GBM xenograft tumors recapitulate histopathological properties and maintain genomic characteristics of parental GBMs in situ. Furthermore, in vivo irradiation, chemotherapy, and targeted therapy of these xenograft tumors mimic the treatment response of parental GBMs. We also found that establishment of orthotopic xenograft models portends poor prognosis of GBM patients and identified the gene signatures and pathways signatures associated with the clinical aggressiveness of GBMs. Together, the patient-specific orthotopic GBM xenograft library represent the preclinically and clinically valuable “patient tumor’s phenocopy” that represents molecular and functional heterogeneity of GBMs. aCGH experiments were performed for a human glioblastoma tissue (sample ID: PC-NS08-559) and the matching xenograft tumor tissue using the Agilent Human Whole Genome CGH 244K microarray according to manufacturer's protocol (2-color).
2013-01-18 | E-GEOD-42577 | biostudies-arrayexpress
Project description:Frequent discrepancies between preclinical and clinical results of anti-cancer agents demand a reliable translational platform that can precisely recapitulate the biology of human cancers. Another critical unmet need is the ability to predict therapeutic responses for individual patients. Toward this goal, we have established a library of orthotopic glioblastoma (GBM) xenograft models using surgical samples of GBM patients. These patient-specific GBM xenograft tumors recapitulate histopathological properties and maintain genomic characteristics of parental GBMs in situ. Furthermore, in vivo irradiation, chemotherapy, and targeted therapy of these xenograft tumors mimic the treatment response of parental GBMs. We also found that establishment of orthotopic xenograft models portends poor prognosis of GBM patients and identified the gene signatures and pathways signatures associated with the clinical aggressiveness of GBMs. Together, the patient-specific orthotopic GBM xenograft library represent the preclinically and clinically valuable “patient tumor’s phenocopy” that represents molecular and functional heterogeneity of GBMs.
2013-01-18 | GSE42669 | GEO
Project description:Frequent discrepancies between preclinical and clinical results of anti-cancer agents demand a reliable translational platform that can precisely recapitulate the biology of human cancers. Another critical unmet need is the ability to predict therapeutic responses for individual patients. Toward this goal, we have established a library of orthotopic glioblastoma (GBM) xenograft models using surgical samples of GBM patients. These patient-specific GBM xenograft tumors recapitulate histopathological properties and maintain genomic characteristics of parental GBMs in situ. Furthermore, in vivo irradiation, chemotherapy, and targeted therapy of these xenograft tumors mimic the treatment response of parental GBMs. We also found that establishment of orthotopic xenograft models portends poor prognosis of GBM patients and identified the gene signatures and pathways signatures associated with the clinical aggressiveness of GBMs. Together, the patient-specific orthotopic GBM xenograft library represent the preclinically and clinically valuable “patient tumor’s phenocopy” that represents molecular and functional heterogeneity of GBMs.
2013-01-18 | GSE42577 | GEO
Project description:Epithelial ovarian cancer (EOC) is the most lethal gynecological malignancy. On the basis of its histopathology and molecular-genomic changes ovarian cancer has been divided into subtypes, each with distinct biology and outcome. The aim of this study was to develop a panel of patient-derived EOC-xenografts that recapitulate the molecular and biological heterogeneity of human ovarian cancer. Thirty-four EOC-xenografts were successfully established, either subcutaneously or intraperitoneally, in nude mice. The xenografts were histologically similar to the corresponding patient tumor and comprised all the major ovarian cancer subtypes. After orthotopic transplantation in the bursa of the mouse ovary, they disseminate into the organs of the peritoneal cavity and produce ascites, typical of ovarian cancer. Gene expression analysis and mutation status indicated a high degree of similarity with the original patient and discriminate different subsets of xenografts. They were very responsive, responsive and resistant to cisplatin, resembling the clinical situation in ovarian cancer. This panel of patient-derived EOC-xenografts that recapitulate the recently type I and type II classification serves to study the biology of ovarian cancer, identify tumor-specific molecular markers and develop novel treatment modalities. EOC-xenografts collected from subcutis, abdominal masses and ascitic fluid of mice engrafted with tumors at different passages (from 1 to 6) and from patient specimens, underwent one-color microarray-based gene expression profiling. To assess the amount of human- and mouse-derived cells in the xenograft tumors, total RNA was evaluated by species specific qPCR assays for beta actin. Only samples with a human RNA content > 75% were analyzed. Nine patient specimens and 62 xenograft samples (representing 29 EOC-xenograft models) underwent gene expression analysis with SurePrint G3 Human GE V2 8x60K microarrays.
2015-01-07 | E-GEOD-56920 | 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:We established 21 patient-derived pHGG orthotopic xenograft (PDOX) models and 8 matched cell lines from diverse pHGG subgroups. Models recapitulated histopathology, DNA methylation signatures, mutations and gene expression patterns of the patient tumors from which they were derived, and included rare subgroups not well-represented by existing models. We also included 6 DIPG cell lines generously shared by Dr. Michelle Monje (Stanford University). An online interactive data portal is available to explore associated detailed molecular characterization and HTS chemical sensitivity data.
2020-12-09 | GSE152035 | GEO