Ontology highlight
ABSTRACT:
PROVIDER: PRJNA174963 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Characterization of novel ovarian tumor cell lines that retain the phenotype of primary tumors [Illumina]
| PRJNA174965 | ENA
Project description:Characterization of novel ovarian tumor cell lines that retain the phenotype of primary tumors [MIP]
| PRJNA174966 | ENA
Project description:Characterization of novel ovarian tumor cell lines that retain the phenotype of primary tumors [SNP]
| PRJNA174967 | ENA
Project description:The inability to establish stable cell lines from the vast majority of human tumors has limited the use of in vitro models to study human cancer. Currently available tumor cell lines fail to represent the biological diversity of human tumors. We have developed a cell culture medium that enabled us to routinely establish cell lines from diverse subtypes of ovarian tumors. Importantly, the twenty-five ovarian tumor cell lines described here retain the genomic landscape, histopathology, and molecular features of the original tumors. Furthermore, the molecular profile and drug response of these cell lines correlated with distinct groups of primary tumors with different outcomes. Thus, tumor cell lines derived using this methodology represent a significantly improved new platform to study human tumor biology and treatment. DNA was extracted from 25 OCI (human ovarian cancer) cell lines.
2015-06-16 | E-GEOD-40786 | biostudies-arrayexpress
Project description:The inability to establish stable cell lines from the vast majority of human tumors has limited the use of in vitro models to study human cancer. Currently available tumor cell lines fail to represent the biological diversity of human tumors. We have developed a cell culture medium that enabled us to routinely establish cell lines from diverse subtypes of ovarian tumors. Importantly, the twenty-five ovarian tumor cell lines described here retain the genomic landscape, histopathology, and molecular features of the original tumors. Furthermore, the molecular profile and drug response of these cell lines correlated with distinct groups of primary tumors with different outcomes. Thus, tumor cell lines derived using this methodology represent a significantly improved new platform to study human tumor biology and treatment. 41 samples were analyzed in singlicate. DNA was extracted from 16 OCI cell lines and the 16 uncultured tumor tissue samples from which they were derived. DNA was also extracted from 9 standard ovarian cancer cell lines.
2015-06-16 | E-GEOD-40787 | biostudies-arrayexpress
Project description:The inability to establish stable cell lines from the vast majority of human tumors has limited the use of in vitro models to study human cancer. Currently available tumor cell lines fail to represent the biological diversity of human tumors. We have developed a cell culture medium that enabled us to routinely establish cell lines from diverse subtypes of ovarian tumors. Importantly, the twenty-five ovarian tumor cell lines described here retain the genomic landscape, histopathology, and molecular features of the original tumors. Furthermore, the molecular profile and drug response of these cell lines correlated with distinct groups of primary tumors with different outcomes. Thus, tumor cell lines derived using this methodology represent a significantly improved new platform to study human tumor biology and treatment.
2015-06-16 | GSE40787 | GEO
Project description:The inability to establish stable cell lines from the vast majority of human tumors has limited the use of in vitro models to study human cancer. Currently available tumor cell lines fail to represent the biological diversity of human tumors. We have developed a cell culture medium that enabled us to routinely establish cell lines from diverse subtypes of ovarian tumors. Importantly, the twenty-five ovarian tumor cell lines described here retain the genomic landscape, histopathology, and molecular features of the original tumors. Furthermore, the molecular profile and drug response of these cell lines correlated with distinct groups of primary tumors with different outcomes. Thus, tumor cell lines derived using this methodology represent a significantly improved new platform to study human tumor biology and treatment.
2015-06-16 | GSE40786 | GEO
Project description:The inability to establish stable cell lines from the vast majority of human tumors has limited the use of in vitro models to study human cancer. Currently available tumor cell lines fail to represent the biological diversity of human tumors. We have developed a cell culture medium that enabled us to routinely establish cell lines from diverse subtypes of ovarian tumors. Importantly, the twenty-five ovarian tumor cell lines described here retain the genomic landscape, histopathology, and molecular features of the original tumors. Furthermore, the molecular profile and drug response of these cell lines correlated with distinct groups of primary tumors with different outcomes. Thus, tumor cell lines derived using this methodology represent a significantly improved new platform to study human tumor biology and treatment.
2015-06-16 | GSE40785 | GEO
Project description:The inability to establish stable cell lines from the vast majority of human tumors has limited the use of in vitro models to study human cancer. Currently available tumor cell lines fail to represent the biological diversity of human tumors. We have developed a cell culture medium that enabled us to routinely establish cell lines from diverse subtypes of ovarian tumors. Importantly, the twenty-five ovarian tumor cell lines described here retain the genomic landscape, histopathology, and molecular features of the original tumors. Furthermore, the molecular profile and drug response of these cell lines correlated with distinct groups of primary tumors with different outcomes. Thus, tumor cell lines derived using this methodology represent a significantly improved new platform to study human tumor biology and treatment. Total RNA was obtained from untreated ovarian cancer cell lines and clustering analysis was performed. The 'Median-Cent_5147_probes.txt' is a list of the 5147 gene probes that has at least 2-fold difference relative to median value across cell lines in at least 4 samples. These are the probes that were used for hierarchial clustering analysis. The 'Combined_and_GSE9891.txt' is a combination of gene probes from this study of ovarian cell lines and of human ovarian cancer cell lines (GSE9891[GPL570]: Expression profile of 285 ovarian tumour samples). Only the 3832 overlapping gene probes between the this study and the GSE9891[GPL570] study are listed. The 3832 gene probes listed have at least 2-fold difference relative to median value across samples in at least 4 samples.
2015-06-16 | E-GEOD-40785 | biostudies-arrayexpress
Project description:Solid tumors are complex organs comprising neoplastic cells and stroma, yet cancer cell lines remain widely used to study tumor biology, biomarkers and experimental therapy. Here, we performed a fully integrative analysis of global proteomic data comparing human colorectal cancer (CRC) cell lines to primary tumors and normal tissues. We found a significant, systematic difference between cell line and tumor proteomes, with a major contribution from tumor stroma proteomes. Nevertheless, cell lines overall mirrored the proteomic differences observed between tumors and normal tissues, in particular for genetic information processing and metabolic pathways, indicating that cell lines provide a system for the study of the intrinsic molecular programs in cancer cells. Intersection of cell line data with tumor data provided insights into tumor cell specific proteome alterations driven by genomic alterations. Our integration of cell line proteogenomic data with drug sensitivity data highlights the potential of proteomic data in predicting therapeutic response. We identified representative cell lines for the proteomic subtypes of primary tumors, and linked these to drug sensitivity data to identify subtype-specific drug candidates.
2016-12-01 | MSV000080374 | GNPS