Identification of genes differentailly expressed in cancer stem-like cells of ovarian serous carcinoma and its clinical significance
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE60765 | GEO | 2014/08/27
SECONDARY ACCESSION(S): PRJNA259510
REPOSITORIES: GEO
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Project description:We found gene expression profiling of spheroid-forming cell (cancer stem-like cell) by cDNA microarray and validated the genes as prognostic markers of ovarian serous carcinoma. Total RNA obtained from four different spheroid-forming cell (S3, S4, S5, and sample 7) compared to corresponding parent cancer cell (control3-1, C4, C5 and control7) by cDNA microarray.
2014-08-27 | E-GEOD-60765 | 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: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:Differential transcriptome signature of FACS purified cell population (EpiCAM/CD45 dual positive cells vs EpiCAM only) from the ascites of human serous ovarian cancer. Primary objective: To characterize the phenotypic expression of stem cells markers, elucidation of differential gene expression and oncogenic functions in EpiCAM/CD45 dual positive vs EpiCAM cells. Methods: Cell Sorting (FACS) from ascites of human serous ovarian cancer patients, apoptotic assay, Drug sensitivity assay, tumor spheroid assay, Cell invasion and cell migration assay.
2016-11-13 | GSE75036 | GEO
Project description:We previously showed that DYRK1A is essential for ovarian cancer spheroid cell survival. DYRK1A regulates transcription by assembling the DREAM repressor complex and also regulates RNA polymerase II. However, the present understanding of how DYRK1A regulates transcription in high-grade serous ovarian cancer (HGSOC) spheroid cells to promote quiescence and survival is lacking. Here we performed GO-CRISPR screens in a panel of HGSOC spheroid cells in combination with transcriptional analyses of DYRK1A deficient spheroid cells. We identified netrin signaling components as essential factors of HGSOC spheroid cell survival. Netrin is well-characterized in axon development but has recently been implicated in other cancer types. We found that knockout of netrin ligands or receptors affects viability of spheroid cells. Netrin ligands and receptors are upregulated in HGSOC cells in suspension conditions. Together, this work suggests that the netrin signaling pathway may be a potential therapeutic target to specifically eliminate spheroid cells in HGSOC and highlights it as an important area requiring further investigation in the context of ovarian cancer.
2023-04-01 | GSE190294 | GEO
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
Project description:The presence of tumor cells in effusions within serosal cavities is a clinical manifestation of advanced-stage cancer and is generally associated with poor survival. Identifying molecular targets may help to design efficient treatments to eradicate these aggressive cancer cells and improve patient survival. Using a state-of-the-art Taqman-based qRT-PCR assay, we investigated the multidrug resistance (MDR) transcriptome of 32 unpaired ovarian serous carcinoma effusion samples obtained at diagnosis or at disease recurrence following chemotherapy. MDR genes were selected a priori based on an extensive curation of the literature published during the last three decades. We found three gene signatures with a statistically significant correlation with overall survival (OS), response to treatment (complete response - CR vs. other), and progression free survival (PFS). The median log-rank p-values for the signatures were 0.023, 0.034, and 0.008, respectively. No correlation was found with residual tumor status after cytoreductive surgery, treatment (with or without chemotherapy) and stage defined according to the International Federation of Gynecology and Obstetrics. Further analyses demonstrated that gene expression alone can effectively predict the survival outcome of women with ovarian serous carcinoma (OS: log-rank p=0.0000 and PFS: log-rank p=0.002). Interestingly, the signature for overall survival is the same in patients at first presentation and those who had chemotherapy and relapsed. This pilot study highlights two new gene signatures that may help in optimizing the treatment for ovarian carcinoma patients with effusions. In the study presented here, effusion samples were obtained from 32 patients diagnosed with serous ovarian carcinoma (n=25), primary peritoneal serous carcinoma (n=6) or tubal serous carcinoma (n=1). They were accrued at the Division of Pathology in the Norwegian Radium Hospital from 2000-2006. RNA was used to study the expression profile of 381 multidrug resistant-related genes.
2011-11-17 | E-GEOD-29702 | biostudies-arrayexpress
Project description:Ovarian cancer is the most lethal gynecologic cancer. High-grade serous ovarian carcinoma (HGSOC) is the most common histologic subtype, accounting for three quarters of ovarian cancer. To clarify the changes of gene expression in serous ovarian cancer, we performed lncRNA and mRNA microarrays to identify differentially expressed lncRNAs and mRNAs in High-grade and Low-grade serous ovarian carcinoma compared with Normal fallopian tube.
2020-02-12 | GSE135886 | GEO
Project description:To identify and evaluate the prognostic ability of progression-free survival-related profile for advanced-stage ovarian cancer, advanced-stage serous ovarian cancer tissues from 110 patients who received primary surgery and a platinum/taxane-based chemotherapy were profiled using oligonucleotide microarrays of more than 40,000 transcripts. We first selected 88 genes by a univariate Cox proportional hazard analysis (p<0.01) and next optimized regression coefficients by ridge regression model using 10-fold cross-validation. The prognostic index was independently associated with PFS time compared to other clinical factors in multivariate analysis [hazard ratio (HR), 3.72; 95% confidence interval (CI), 2.66–5.43; p,0.0001]. In an external dataset, multivariate analysis revealed that this prognostic index was significantly correlated with PFS time (HR, 1.54; 95% CI, 1.20–1.98; p = 0.0008). Furthermore, the correlation between the prognostic index and overall survival time was confirmed in the two independent external datasets (log rank test, p = 0.0010 and 0.0008). In multivariable analysis, our prognostic index was independently associated with progression-free survival times compared to other clinical factors (p<0.001). Furthermore, the prognostic ability of our prognostic index was validated in external, publicly available dataset (n = 87), and was proved in multivariate analysis (p = 0.0032). These results suggest that disease progression or recurrence of advanced-stage serous ovarian cancer can be predicted by gene expression profile. The prognostic ability of our index based on the 88-gene expression profile in ridge regression Cox hazard model was shown to be independent of other clinical factors in predicting cancer prognosis across two distinct datasets. Further study will be necessary to improve predictive accuracy of the prognostic index toward clinical application for evaluation of the risk of recurrence in patients with advanced-stage serous ovarian cancer.
2010-03-22 | GSE17260 | GEO