Project description:Glioblastoma (GBM) is classified as World Health Organization grade IV tumors of the central nervous system, and it is the most malignant form of glioma. The current GBM therapies could not completely eliminate the tumor mass and the occurrence of therapeutic resistance of surviving GBM cells is considered as an obstacle to be overcome. We used microarrays to detail the global program of gene expression underlying development of radioresistance of GBM and identified a variety of genes whose expressions were regulated during this process.
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).
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.
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.
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.
Project description:This SuperSeries is composed of the following subset Series: GSE38814: Glioblastoma Orthotopic Xenograft Transcriptome GSE38815: Glioblastoma Xenograft Comparative Genomic Hybridization Arrays Refer to individual Series
Project description:This SuperSeries is composed of the following subset Series: GSE25690: Global analysis of mRNA expression in prospectively purified human prostate orthotopic xenograft tumor cells with varying S/TFE. GSE25691: Global analysis of miRNA expression in prospectively purified human prostate orthotopic xenograft tumor cells with varying S/TFE. Refer to individual Series
Project description:Metastasis is a major factor for mortality in patients with hepatocellular carcinoma (HCC). Thus, there is a need for predictive biomarker(s) for detecting the tipping point before metastasis, so as to prevent further deterioration. To discover early warning signals of pulmonary metastasis in HCC, we analysed time-series gene expression data in the spontaneous pulmonary metastasis mouse HCCLM3-RFP model with our novel dynamic network biomarker (DNB) method. To simulate tumour growth and metastasis in patient livers, we used the spontaneous pulmonary metastasis mouse model, HCCLM3-RFP, which involves the orthotopic transplanted human HCCLM3 cell line labelled with a stable fluorescent protein.We observed that, hepatic tumours in orthotopic xenograft HCCLM3-RFP mice grew gradually from the second to the fifth week after orthotopic implantation in the primary liver tissue, whereas spontaneous pulmonary metastasis occurredonly at the last time point (the fifth week after orthotopic implantation).Thus, we chose the second, third, fourth, and fifth weeks after orthotopic implantation as observation points to collect liver tumours of five orthotopic xenograft mice at each time point and to assess the whole-genome expression.