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

Stephen F. Madden, Colin Clarke, Britta Stordal, Mark S. Carey, Russell Broaddus, William M. Gallagher, John Crown, Gordon Mills, Bryan T. Hennessy

Research output: Contribution to journalArticle

7 Citations (Scopus)

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.

Original languageEnglish (US)
Article number241
JournalMolecular Cancer
Volume13
Issue number1
DOIs
StatePublished - Oct 24 2014
Externally publishedYes

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Neoplasm Genes
Ovarian Neoplasms
Biomarkers
MicroRNAs
Gene Expression
Genes
Disease-Free Survival
Neoplasms
Delayed Diagnosis
Datasets
Computational Biology
Research

ASJC Scopus subject areas

  • Molecular Medicine
  • Oncology
  • Cancer Research

Cite this

Madden, S. F., Clarke, C., Stordal, B., Carey, M. S., Broaddus, R., Gallagher, W. M., ... Hennessy, B. T. (2014). OvMark: A user-friendly system for the identification of prognostic biomarkers in publically available ovarian cancer gene expression datasets. Molecular Cancer, 13(1), [241]. https://doi.org/10.1186/1476-4598-13-241

OvMark : A user-friendly system for the identification of prognostic biomarkers in publically available ovarian cancer gene expression datasets. / Madden, Stephen F.; Clarke, Colin; Stordal, Britta; Carey, Mark S.; Broaddus, Russell; Gallagher, William M.; Crown, John; Mills, Gordon; Hennessy, Bryan T.

In: Molecular Cancer, Vol. 13, No. 1, 241, 24.10.2014.

Research output: Contribution to journalArticle

Madden, Stephen F. ; Clarke, Colin ; Stordal, Britta ; Carey, Mark S. ; Broaddus, Russell ; Gallagher, William M. ; Crown, John ; Mills, Gordon ; Hennessy, Bryan T. / OvMark : A user-friendly system for the identification of prognostic biomarkers in publically available ovarian cancer gene expression datasets. In: Molecular Cancer. 2014 ; Vol. 13, No. 1.
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