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Gene expression profile for predicting survival in advanced-stage serous ovarian cancer across two independent datasets.

Yoshihara K, Tajima A, Yahata T, Kodama S, Fujiwara H, Suzuki M, Onishi Y, Hatae M, Sueyoshi K, Fujiwara H, Kudo Y, Kotera K, Masuzaki H, Tashiro H, Katabuchi H, Inoue I, Tanaka K - PLoS ONE (2010)

Bottom Line: However, there is a wide range of outcomes for individual patients.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).

View Article: PubMed Central - PubMed

Affiliation: Department of Obstetrics and Gynecology, Niigata University Graduate School of Medical and Dental Sciences, Niigata, Japan.

ABSTRACT

Background: Advanced-stage ovarian cancer patients are generally treated with platinum/taxane-based chemotherapy after primary debulking surgery. However, there is a wide range of outcomes for individual patients. Therefore, the clinicopathological factors alone are insufficient for predicting prognosis. Our aim is to identify a progression-free survival (PFS)-related molecular profile for predicting survival of patients with advanced-stage serous ovarian cancer.

Methodology/principal findings: Advanced-stage serous ovarian cancer tissues from 110 Japanese patients who underwent primary surgery and platinum/taxane-based chemotherapy were profiled using oligonucleotide microarrays. We selected 88 PFS-related genes by a univariate Cox model (p<0.01) and generated the prognostic index based on 88 PFS-related genes after adjustment of regression coefficients of the respective genes by ridge regression Cox 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).

Conclusions/significance: 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.

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Related in: MedlinePlus

Biological characteristics of 88 progression-free survival-related genes.Significantly over-represented 8 gene ontology (GO) categories in GO-based profiling of 88 genes after multiple testing correction of the Benjamini–Hochberg false discovery rate method (FDR q-value<0.10). Over-represented GO categories were identified using all genes on Agilent platform as a background set of genes for the determining p-values. The actual number of the PFS-related genes involved in each category is given in parentheses.
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pone-0009615-g004: Biological characteristics of 88 progression-free survival-related genes.Significantly over-represented 8 gene ontology (GO) categories in GO-based profiling of 88 genes after multiple testing correction of the Benjamini–Hochberg false discovery rate method (FDR q-value<0.10). Over-represented GO categories were identified using all genes on Agilent platform as a background set of genes for the determining p-values. The actual number of the PFS-related genes involved in each category is given in parentheses.

Mentions: We conducted GO analysis to understand the biological characteristics of 88 PFS-related genes. To characterize the gene list based on GO classification on ‘biological process’, ‘molecular function’, and ‘cellular component’, we examined which categories were highly associated with the 88 genes. After multiple testing corrections using the FDR method [26], 8 categories were significantly overrepresented (FDR q-value<0.10) (Figure 4). In the 88 PFS-related genes, genes involved in GTPase binding (GO17016, GO31267 and GO51020), cellular localization (GO51649 and GO51641), intracellular transport (GO46907 and GO6886), and/or ciliary or flagellar motility (GO1539) were notably enriched. We investigated similarities in overrepresented GO categories between our 88 PFS-related genes and the previously reported gene expression profiles which were correlated to prognosis in ovarian cancer [11], [13]. However, we could not identify common GO categories between our profile and the previously reported profiles (data not shown).


Gene expression profile for predicting survival in advanced-stage serous ovarian cancer across two independent datasets.

Yoshihara K, Tajima A, Yahata T, Kodama S, Fujiwara H, Suzuki M, Onishi Y, Hatae M, Sueyoshi K, Fujiwara H, Kudo Y, Kotera K, Masuzaki H, Tashiro H, Katabuchi H, Inoue I, Tanaka K - PLoS ONE (2010)

Biological characteristics of 88 progression-free survival-related genes.Significantly over-represented 8 gene ontology (GO) categories in GO-based profiling of 88 genes after multiple testing correction of the Benjamini–Hochberg false discovery rate method (FDR q-value<0.10). Over-represented GO categories were identified using all genes on Agilent platform as a background set of genes for the determining p-values. The actual number of the PFS-related genes involved in each category is given in parentheses.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2837379&req=5

pone-0009615-g004: Biological characteristics of 88 progression-free survival-related genes.Significantly over-represented 8 gene ontology (GO) categories in GO-based profiling of 88 genes after multiple testing correction of the Benjamini–Hochberg false discovery rate method (FDR q-value<0.10). Over-represented GO categories were identified using all genes on Agilent platform as a background set of genes for the determining p-values. The actual number of the PFS-related genes involved in each category is given in parentheses.
Mentions: We conducted GO analysis to understand the biological characteristics of 88 PFS-related genes. To characterize the gene list based on GO classification on ‘biological process’, ‘molecular function’, and ‘cellular component’, we examined which categories were highly associated with the 88 genes. After multiple testing corrections using the FDR method [26], 8 categories were significantly overrepresented (FDR q-value<0.10) (Figure 4). In the 88 PFS-related genes, genes involved in GTPase binding (GO17016, GO31267 and GO51020), cellular localization (GO51649 and GO51641), intracellular transport (GO46907 and GO6886), and/or ciliary or flagellar motility (GO1539) were notably enriched. We investigated similarities in overrepresented GO categories between our 88 PFS-related genes and the previously reported gene expression profiles which were correlated to prognosis in ovarian cancer [11], [13]. However, we could not identify common GO categories between our profile and the previously reported profiles (data not shown).

Bottom Line: However, there is a wide range of outcomes for individual patients.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).

View Article: PubMed Central - PubMed

Affiliation: Department of Obstetrics and Gynecology, Niigata University Graduate School of Medical and Dental Sciences, Niigata, Japan.

ABSTRACT

Background: Advanced-stage ovarian cancer patients are generally treated with platinum/taxane-based chemotherapy after primary debulking surgery. However, there is a wide range of outcomes for individual patients. Therefore, the clinicopathological factors alone are insufficient for predicting prognosis. Our aim is to identify a progression-free survival (PFS)-related molecular profile for predicting survival of patients with advanced-stage serous ovarian cancer.

Methodology/principal findings: Advanced-stage serous ovarian cancer tissues from 110 Japanese patients who underwent primary surgery and platinum/taxane-based chemotherapy were profiled using oligonucleotide microarrays. We selected 88 PFS-related genes by a univariate Cox model (p<0.01) and generated the prognostic index based on 88 PFS-related genes after adjustment of regression coefficients of the respective genes by ridge regression Cox 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).

Conclusions/significance: 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.

Show MeSH
Related in: MedlinePlus