Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA148341 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:To identify the potential ovarian cancer stem cell gene expression profile from isolated side population of fresh ascites obtained from women with high-grade advanced stage papillary serous ovarian adenocarcinoma Microarrays were used to interrogate the differentially expressed genes between side population (SP) and main population (MP) isolated from fresh ascites obtained from women with high-grade advanced stage papillary serous ovarian adenocarcinoma, and the results were analyzed by paired T-test using BRB-ArrayTools
2011-11-23 | GSE33874 | GEO
Project description:To identify the potential ovarian cancer stem cell gene expression profile from isolated side population of fresh ascites obtained from women with high-grade advanced stage papillary serous ovarian adenocarcinoma Microarrays were used to interrogate the differentially expressed genes between side population (SP) and main population (MP) isolated from fresh ascites obtained from women with high-grade advanced stage papillary serous ovarian adenocarcinoma, and the results were analyzed by paired T-test using BRB-ArrayTools Gene expression profiling was completed for 10 SP and MP pairs using the Affymetrix human U133 Plus 2.0 Arrays
2011-11-23 | E-GEOD-33874 | biostudies-arrayexpress
Project description:To demonstrate the use of a whole-genome oligonucleotide array to perform expression profiling on a series of microdissected late-stage, high-grade papillary serous ovarian adenocarcinomas to establish a prognostic gene signature correlating with survival and to identify novel survival factors in ovarian cancer. Advanced stage papillary serous tumors of the ovary are responsible for the majority of ovarian cancer deaths, yet the molecular determinants modulating patient survival are poorly characterized. We identify and validate a prognostic gene expression signature correlating with survival in a series of microdissected serous ovarian tumors. Experiment Overall Design: We identified 53 advanced stage, high-grade primary tumor specimens and 10 normal ovarian surface epithelium (OSE) brushings.
2009-10-23 | E-GEOD-18520 | biostudies-arrayexpress
Project description:To demonstrate the use of a whole-genome oligonucleotide array to perform expression profiling on a series of microdissected late-stage, high-grade papillary serous ovarian adenocarcinomas to establish a prognostic gene signature correlating with survival and to identify novel survival factors in ovarian cancer. Advanced stage papillary serous tumors of the ovary are responsible for the majority of ovarian cancer deaths, yet the molecular determinants modulating patient survival are poorly characterized. We identify and validate a prognostic gene expression signature correlating with survival in a series of microdissected serous ovarian tumors.
2009-10-17 | GSE18520 | GEO
Project description:Comparative genomic hybridization analysis on advanced stage high-grade serous ovarian cancer. CGH was performed on 42 DNA isolated from microdissected advanced stage high-grade serous ovarian cancer.
2009-10-02 | E-GEOD-18154 | biostudies-arrayexpress
Project description:Gene expression profiling on 63 stage III-IV papillary serous ovarian cancer samples resected during primary debulking at the University of Turin, Italy. Only the primary ovarian mass and no metastases were included in this analysis. The study focused on ovarian cancer chemokine expressions
2014-12-04 | GSE62873 | GEO
Project description:Comparative genomic hybridization analysis on advanced stage high-grade serous ovarian cancer.
2009-10-02 | GSE18154 | GEO
Project description:To date, a variety of studies have employed gene expression profiling to classify ovarian carcinomas in clinically relevant subtypes. These studies provided valuable first clues to molecular changes in ovarian cancer that might be exploited in new treatment strategies. However, most studies were of relatively limited size and the number of overlapping genes in the identified profiles was minimal. Although identification of gene expression profiles associated with clinically relevant subtypes in ovarian cancer is important, knowledge is now emerging rapidly on how genes interact in pathways, networks and complexes; this allows us to unravel those cellular pathways determining the biological behavior of ovarian cancer, that might be successfully targeted with drugs. The aim of our study was: 1) To develop a gene expression profile associated with overall survival in advanced stage serous ovarian cancer, 2) to assess the association of pathways and transcription factors with overall survival, and 3) to validate our identified profile and pathways/transcription factors in an independent set of ovarian cancers. According to a randomized design, profiling of 157 advanced stage serous ovarian cancers was performed in duplicate using ~35K 70-mer oligonucleotide microarrays. A continuous predictor of overall survival was built taking into account well-known issues in microarray analysis, such as multiple testing and overfitting. A functional class scoring analysis was utilized to assess pathways/transcription factors for their association with overall survival. The prognostic value of genes that constitute our overall survival profile was validated on a fully independent, publicly available data set of 118 well-defined primary serous ovarian cancers. Furthermore, functional class scoring analysis was also performed on this independent data set to assess the similarities with results from our own data set. An 86-gene overall survival profile discriminated between patients with unfavorable and favorable prognosis (median survival, 19 vs. 41 months, respectively; permutation p-value of log-rank statistic = 0.015) and maintained its independent prognostic value in multivariate analysis. Genes that comprised the overall survival profile were also able to discriminate between the two risk groups in the independent data set. In our dataset 17/167 pathways and 13/111 transcription factors were associated with overall survival of which 16 and 12 respectively were confirmed in the independent dataset. Our study provides new clues to genes, pathways and transcription factors which contribute to the clinical outcome of serous ovarian cancer and might be exploited in designing new treatment strategies. Keywords: Oncology/Gynecological Cancers, Genetics and Genomics/Cancer Genetics, Genetics and Genomics/Gene Expression, Genetics and Genomics/Genomics According to a randomized design, profiling of 157 advanced stage serous ovarian cancers was performed in duplicate using ~35K 70-mer oligonucleotide microarrays. Two randomly selected samples were hybridized together on the arrays for intensity-based instead of ratio-based analysis of the microarray data.
2008-12-10 | E-GEOD-13876 | biostudies-arrayexpress
Project description:Gene expression profiling on 63 stage III-IV papillary serous ovarian cancer samples resected during primary debulking at the University of Turin, Italy. Only the primary ovarian mass and no metastases were included in this analysis. The study focused on ovarian cancer chemokine expressions Only the primary ovarian mass and no metastases were included in this analysis.
2014-10-31 | E-GEOD-62873 | biostudies-arrayexpress
Project description:To elucidate the mechanisms of rapid progression of serous ovarian cancer, gene expression profiles from forty-three ovarian cancer tissues comprising eight early stage and thirty-five advanced stage tissues were performed using oligonucleotide microarrays of 18,716 genes. By non-negative matrix factorization analysis using 178 genes, which were extracted as stage-specific genes, 35 advanced-stage cases were classified into two subclasses with superior (n = 17) and poor (n = 18) outcome evaluated by progression-free survival (logrank test, p = 0.03). Of the 178 stage-specific genes, 112 genes were identified as showing different expression between the two subclasses. Of the 48 genes selected for biological function by Gene Ontology analysis or Ingenuity Pathway Analysis, 5 genes (ZEB2, CDH1, LTBP2, COL16A1 and ACTA2) were extracted as candidates for prognostic factors associated with progression-free survival. The relationship between high ZEB2 or low CDH1 expression and shorter progression-free survival was validated by real-time RT-PCR experiments of 37 independent advanced-stage cancer samples. ZEB2 expression was negatively correlated with CDH1 expression in advanced-stage samples, whereas ZEB2 knockdown in ovarian adenocarcinoma SKOV3 cells resulted in an increase in CDH1 expression. Multivariate analysis showed that high ZEB2 expression was independently associated with poor prognosis. Furthermore, the prognostic effect of E-cadherin encoded by CDH1 was verified using immunohistochemical analysis of an independent advanced-stage cancer samples set (n = 74). These findings suggest that the expressions of epithelial-mesenchymal transition-related genes such as ZEB2 and CDH1 may play important roles in the invasion process of advanced-stage serous ovarian cancer. Forty-three serous ovarian cancer samples were analyzed. Ten normal peritoneum samples were used as controls.
2009-07-19 | E-GEOD-12470 | biostudies-arrayexpress