'OvMark': a user-friendly system for the identification of prognostic biomarkers in publically available ovarian cancer gene expression datasets

Hdl Handle:
http://hdl.handle.net/10147/336241
Title:
'OvMark': a user-friendly system for the identification of prognostic biomarkers in publically available ovarian cancer gene expression datasets
Authors:
Madden, Stephen F; Clarke, Colin; Stordal, Britta; Carey, Mark S; Broaddus, Russell; Gallagher, William M; Crown, John; Mills, Gordon B; Hennessy, Bryan T
Citation:
Madden, S.F. et al., 2014. 'OvMark': a user-friendly system for the identification of prognostic biomarkers in publically available ovarian cancer gene expression datasets. Molecular Cancer. 2014, 13 (1) p 241
Issue Date:
24-Oct-2014
URI:
http://dx.doi.org/10.1186/1476-4598-13-241; http://hdl.handle.net/10147/336241
Abstract:
Abstract Background Ovarian cancer has the lowest survival rate of all gynaecologic cancers and is characterised by a lack of early symptoms and frequent late stage diagnosis. There is a paucity of robust molecular markers that are independent of and complementary to clinical parameters such as disease stage and tumour grade. Methods We have developed a user-friendly, web-based system to evaluate the association of genes/miRNAs with outcome in ovarian cancer. The OvMark algorithm combines data from multiple microarray platforms (including probesets targeting miRNAs) and correlates them with clinical parameters (e.g. tumour grade, stage) and outcomes (disease free survival (DFS), overall survival). In total, OvMark combines 14 datasets from 7 different array platforms measuring the expression of ~17,000 genes and 341 miRNAs across 2,129 ovarian cancer samples. Results To demonstrate the utility of the system we confirmed the prognostic ability of 14 genes and 2 miRNAs known to play a role in ovarian cancer. Of these genes, CXCL12 was the most significant predictor of DFS (HR = 1.42, p-value = 2.42x10−6). Surprisingly, those genes found to have the greatest correlation with outcome have not been heavily studied in ovarian cancer, or in some cases in any cancer. For instance, the three genes with the greatest association with survival are SNAI3, VWA3A and DNAH12. Conclusions/Impact OvMark is a powerful tool for examining putative gene/miRNA prognostic biomarkers in ovarian cancer (available at http://glados.ucd.ie/OvMark/index.html). The impact of this tool will be in the preliminary assessment of putative biomarkers in ovarian cancer, particularly for research groups with limited bioinformatics facilities.
Item Type:
Article
Language:
en
Keywords:
OVARIAN CANCER; DIAGNOSIS; GENETICS

Full metadata record

DC FieldValue Language
dc.contributor.authorMadden, Stephen Fen_GB
dc.contributor.authorClarke, Colinen_GB
dc.contributor.authorStordal, Brittaen_GB
dc.contributor.authorCarey, Mark Sen_GB
dc.contributor.authorBroaddus, Russellen_GB
dc.contributor.authorGallagher, William Men_GB
dc.contributor.authorCrown, Johnen_GB
dc.contributor.authorMills, Gordon Ben_GB
dc.contributor.authorHennessy, Bryan Ten_GB
dc.date.accessioned2014-11-27T12:35:42Z-
dc.date.available2014-11-27T12:35:42Z-
dc.date.issued2014-10-24-
dc.identifier.citationMadden, S.F. et al., 2014. 'OvMark': a user-friendly system for the identification of prognostic biomarkers in publically available ovarian cancer gene expression datasets. Molecular Cancer. 2014, 13 (1) p 241en_GB
dc.identifier.urihttp://dx.doi.org/10.1186/1476-4598-13-241-
dc.identifier.urihttp://hdl.handle.net/10147/336241-
dc.description.abstractAbstract Background Ovarian cancer has the lowest survival rate of all gynaecologic cancers and is characterised by a lack of early symptoms and frequent late stage diagnosis. There is a paucity of robust molecular markers that are independent of and complementary to clinical parameters such as disease stage and tumour grade. Methods We have developed a user-friendly, web-based system to evaluate the association of genes/miRNAs with outcome in ovarian cancer. The OvMark algorithm combines data from multiple microarray platforms (including probesets targeting miRNAs) and correlates them with clinical parameters (e.g. tumour grade, stage) and outcomes (disease free survival (DFS), overall survival). In total, OvMark combines 14 datasets from 7 different array platforms measuring the expression of ~17,000 genes and 341 miRNAs across 2,129 ovarian cancer samples. Results To demonstrate the utility of the system we confirmed the prognostic ability of 14 genes and 2 miRNAs known to play a role in ovarian cancer. Of these genes, CXCL12 was the most significant predictor of DFS (HR = 1.42, p-value = 2.42x10−6). Surprisingly, those genes found to have the greatest correlation with outcome have not been heavily studied in ovarian cancer, or in some cases in any cancer. For instance, the three genes with the greatest association with survival are SNAI3, VWA3A and DNAH12. Conclusions/Impact OvMark is a powerful tool for examining putative gene/miRNA prognostic biomarkers in ovarian cancer (available at http://glados.ucd.ie/OvMark/index.html). The impact of this tool will be in the preliminary assessment of putative biomarkers in ovarian cancer, particularly for research groups with limited bioinformatics facilities.-
dc.language.isoenen
dc.subjectOVARIAN CANCERen_GB
dc.subjectDIAGNOSISen_GB
dc.subjectGENETICSen_GB
dc.title'OvMark': a user-friendly system for the identification of prognostic biomarkers in publically available ovarian cancer gene expression datasetsen_GB
dc.typeArticleen
dc.language.rfc3066en-
dc.rights.holderStephen F Madden et al.; licensee BioMed Central Ltd.-
dc.description.statusPeer Reviewed-
dc.date.updated2014-10-31T04:03:35Z-
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