Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA141387 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:We used microarray CGH analysis with a tiling path BAC DNA microarray to profile DNA copy number alterations in 164 serous ovarian adenocarcinomas. Survival probabilities modelled by proportional hazards were used to stratify cases into good, intermediate or poor survival groups. Comparison of aCGH data from these groups was used to identify genomic alterations associated with patient survival.
2012-06-01 | GSE29503 | GEO
Project description:We used microarray CGH analysis with a tiling path BAC DNA microarray to profile DNA copy number alterations in 164 serous ovarian adenocarcinomas. Survival probabilities modelled by proportional hazards were used to stratify cases into good, intermediate or poor survival groups. Comparison of aCGH data from these groups was used to identify genomic alterations associated with patient survival. A total of 984 cases of serous ovarian adenocarcinoma from three different studies were combined and Cox proportional hazards used to model survival using patient age, tumour stage and residual disease status as covariates. Survival probabilities (Pr) were extracted for all cases and used to stratify 384 cases for which microarray CGH data was available. From these, we identified 70 cases with poor survival (Pr>0.784) and 70 cases with good survival (Pr<0.35). aCGH data from these cases was provided to an iterative Support Vector Machine (SVM) routine to detect copy number changes associated with survival. Candidate regions were then validated by survival analysis in all 384 cases for which aCGH data was available. This series contains aCGH data from 164 tumours from the MALOVA collection.
2012-05-31 | E-GEOD-29503 | biostudies-arrayexpress
Project description:Our study presents the first genetic models of de novo high-grade serous carcinomas (HGSC) that originate in fallopian tube secretory epithelial cells and recapitulate the key genetic alterations and precursor lesions characteristic of human invasive ovarian cancer. Genomic copy number analysis, using array CGH, was performed on murine tumors in order to compare the overlap of copy number alterations between HGSC models and TCGA data.
2013-12-17 | GSE49827 | GEO
Project description:Our study presents the first genetic models of de novo high-grade serous carcinomas (HGSC) that originate in fallopian tube secretory epithelial cells and recapitulate the key genetic alterations and precursor lesions characteristic of human invasive ovarian cancer. Genomic copy number analysis, using array CGH, was performed on murine tumors in order to compare the overlap of copy number alterations between HGSC models and TCGA data. Array CGH was performed on genomic DNA isolated from murine HGSC tumors. Genomic DNA from three normal mouse fallopian tubes was pooled and used as the reference.
2013-12-17 | E-GEOD-49827 | biostudies-arrayexpress
Project description:This study aimed to generate a new panel of comprehensively, genomically characterized high-grade serous ovarian carcinoma (HGSOC) cell line and xenograft models. Multidimensional genomic data were generated and compared between cell lines/xenografts and the tumours they were derived from, indicating the cell lines/xenografts are highly similar to their patient-matched tumours. Cell line/xenograft data were also compared to TCGA ovarian tumours to show the cell lines are good models of clinical HGSOC. Affymetrix SNP 6 arrays were performed according to the manufacturer's instructions on genomic DNA extracted from i) tumour cells purified from ovarian tumour ascites, ii) established cell lines, iii) patient derived xenografts, and iv) lymphoblast lines. Evaluation of the similarity in copy number/methylation/gene expression/mutational profiles of cell lines/tumours/xenografts was performed.
2016-08-11 | E-GEOD-71522 | biostudies-arrayexpress
Project description:This study aimed to generate a new panel of comprehensively, genomically characterized high-grade serous ovarian carcinoma (HGSOC) cell line and xenograft models. Multidimensional genomic data were generated and compared between cell lines/xenografts and the tumours they were derived from, indicating the cell lines/xenografts are highly similar to their patient-matched tumours. Cell line/xenograft data were also compared to TCGA ovarian tumours to show the cell lines are good models of clinical HGSOC. Illumina HT-12 v4 arrays were performed according to the manufacturer's directions on total RNA extracted from i) tumour cells purified from ovarian tumour ascites, and ii) established cell lines. Evaluation of the similarity in copy number/methylation/gene expression/mutational profiles of cell lines/tumours/xenografts was performed.
2016-08-11 | E-GEOD-71524 | biostudies-arrayexpress
Project description:This study aimed to generate a new panel of comprehensively, genomically characterized high-grade serous ovarian carcinoma (HGSOC) cell line and xenograft models. Multidimensional genomic data were generated and compared between cell lines/xenografts and the tumours they were derived from, indicating the cell lines/xenografts are highly similar to their patient-matched tumours. Cell line/xenograft data were also compared to TCGA ovarian tumours to show the cell lines are good models of clinical HGSOC. Illumina HumanMethylation450 arrays were performed according to the manufacturer's directions on DNA extracted from i) tumour cells purified from ovarian tumour ascites, and ii) established cell lines. Evaluation of the similarity in copy number/methylation/gene expression/mutational profiles of cell lines/tumours/xenografts was performed.
2016-08-11 | E-GEOD-71523 | biostudies-arrayexpress
Project description:Genome-wide copy number variation was measured in TP53 mutation negative ovarian tumours. Analysis described in "Driver mutations in TP53 are ubiquitous in high grade serous carcinoma of the ovary" (Ahmed et al., 2010)
2010-03-04 | GSE19416 | GEO
Project description:Ovarian cancer is characterized by multiple structural aberrations; most are passenger alterations which do not confer tumor growth. Like many cancers, it is a heterogeneous disease and till date, the histotype-specific copy number landscape has been difficult to elucidate. To dissect the heterogeneity of ovarian cancer and understand the pathogenesis of its various histotypes, we developed an in silico hypothesis-driven workflow to identify histotype-specific copy number aberrations across multiple datasets of epithelial ovarian cancer. In concordance with previous studies on global copy number changes, our study showed similar alterations. However, when the landscape was de-convoluted into histotypes, distinct alterations were observed. We report here a comprehensive histotype-specific copy number landscape of ovarian cancer and showed that there is genomic diversity between the histotypes; some involving well known cancer genes and some novel potential driver genes. Besides preferential occurrence of alterations in some histotypes, opposite trends of alteration were observed; such as ERBB2 amplification in mucinous but deletion in serous tumors. The landscape highlights the need for identifying histotype-specific aberrations in ovarian cancer and present potential to tailor management of ovarian cancer based on molecular signature of histotypes. 56 samples containing the 4 histotypes were used for this study. It contained 12 clear cell carcinoma, 6 endometrioid adenocarcinoma, 2 mucinous adenocarcinoma, 5 mucinous-borderline tumors, 26 serous adenocarcinoma, and 5 serous-borderline tumors.
2012-10-25 | E-GEOD-30274 | biostudies-arrayexpress
Project description:Ovarian cancer is characterized by multiple structural aberrations; most are passenger alterations which do not confer tumor growth. Like many cancers, it is a heterogeneous disease and till date, the histotype-specific copy number landscape has been difficult to elucidate. To dissect the heterogeneity of ovarian cancer and understand the pathogenesis of its various histotypes, we developed an in silico hypothesis-driven workflow to identify histotype-specific copy number aberrations across multiple datasets of epithelial ovarian cancer. In concordance with previous studies on global copy number changes, our study showed similar alterations. However, when the landscape was de-convoluted into histotypes, distinct alterations were observed. We report here a comprehensive histotype-specific copy number landscape of ovarian cancer and showed that there is genomic diversity between the histotypes; some involving well known cancer genes and some novel potential driver genes. Besides preferential occurrence of alterations in some histotypes, opposite trends of alteration were observed; such as ERBB2 amplification in mucinous but deletion in serous tumors. The landscape highlights the need for identifying histotype-specific aberrations in ovarian cancer and present potential to tailor management of ovarian cancer based on molecular signature of histotypes. 56 samples containing the 4 histotypes were used for this study. It contained 12 clear cell carcinoma, 6 endometrioid adenocarcinoma, 2 mucinous adenocarcinoma, 5 mucinous-borderline tumors, 26 serous adenocarcinoma, and 5 serous-borderline tumors. Data was pre-processed and normalized with Hapmap JPT using the Affymetric Genotyping Console.
2012-10-25 | E-GEOD-30283 | biostudies-arrayexpress