Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Gene expression profiles of serous ovarian cancer samples

ABSTRACT: 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.

ORGANISM(S): Homo sapiens

SUBMITTER: Kosuke Yoshihara

PROVIDER: E-GEOD-12470 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Gene expression profiling of advanced-stage serous ovarian cancers distinguishes novel subclasses and implicates ZEB2 in tumor progression and prognosis.

Yoshihara Kosuke K Tajima Atsushi A Komata Dai D Yamamoto Tadashi T Kodama Shoji S Fujiwara Hiroyuki H Suzuki Mitsuaki M Onishi Yoshitaka Y Hatae Masayuki M Sueyoshi Kazunobu K Fujiwara Hisaya H Kudo Yoshiki Y Inoue Ituro I Tanaka Kenichi K

Cancer science 20090526 8

To elucidate the mechanisms of rapid progression of serous ovarian cancer, gene expression profiles from 43 ovarian cancer tissues comprising eight early stage and 35 advanced stage tissues were carried out 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 ...[more]

PMID: 19486012

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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.

Dataset Information

Gene expression profiles of serous ovarian cancer samples

Publications

Gene expression profiling of advanced-stage serous ovarian cancers distinguishes novel subclasses and implicates ZEB2 in tumor progression and prognosis.

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