14 Gene Signature for Serous Ovarian Carcinoma Diagnosis and Prognosis

University Health Network - Technology Development and Commercialization
posted on 01/13/2011

Introduction: Epithelial ovarian cancer is the fifth most common disease responsible for female cancer deaths and serous ovarian carcinoma is the most prevalent histologic subtype, representing 70% of all cases. The five-year prognosis for this disease is unfavourable with a low 30% survival rate. There are currently no clinically useful biomarkers that are able to accurately determine the prognosis of these patients in terms of recurrence and overall survival. Background Research for Technology The authors of this patent have identified a 14 biomarker signature that is differentially expressed in serous ovarian carcinomas with favourable and poor prognosis. This panel was obtained by training prognostic risk models for overall survival of ovarian cancer patients using the largest available ovarian cancer data set, which include 252 samples of which serous carcinoma represents the most common subtype. External validation of these models was undergone using 8 publically available data sets. The utility of the new signature developed, was compared with four sources of cancer related genes and 41 previously determined ovarian cancer gene signatures. Risk score calculations were performed based on biomarker expression levels to identify the molecular subsets with statistically significant differences in survival. Comparison of this 14 gene set against other publically available signatures using the aforementioned largest ovarian cancer dataset, revealed that this unique set of biomarkers was one of the most successful at segregating patients with favourable and poor prognosis. This unique panel of genes has for the first time been linked to clinical outcome of ovarian carcinoma, as it can be subdivided into biomarkers that can categorize patients based on prognosis.

Suggested Uses

prognostic biomarker for ovarian cancer

Innovation Details

Detailed Description

Technology Description:
The technology represents a new method of determining prognosis for patients with serous ovarian carcinoma, with use of the 14 gene signature. In this invention, the expression levels of three or more biomarkers can easily be quantified from a flash frozen piece of tumour and compared to a reliable control. Biomarker expression levels can be clinically tested using assay kits that quantify nucleic acids or proteins. RNA quantification could be accomplished using Q-PCR, SAGE, microarrays, RNA sequencing, RNase protection assays or Northern Blots. Conversely, protein quantification could be undergone using Western Blots analysis. A risk score can thereby be generated for each patient using the relative expression of each gene, and compared to a pre-determined threshold to indicate a favourable or poor prognosis. Computer software could additionally be utilized to help compare biomarker expression profile inputs with appropriate reference profiles, and will display patient specific prognosis based on the similarity between test sample and control.
Research Results:
Validation of this signature at the genetic level was achieved using the Oncomine bioinformatics infrastructure, which indicated the abundance of this gene set in a large number of microarray cohorts of serous tumours. The presence and differential expression of signature members was also validated by specialized pathologists at the protein level in a large set of human ovarian cancer biopsy samples using immunohistochemistry. Mouse model experiments were utilized for quantification of the biomarker signature in secreted serum, in order to extend the use of this technology to simple and non-invasive prognosis testing in humans using ascites, serum or blood. These validation methods have indicated a robust invention for clinical use in serous ovarian carcinoma prognosis.

File Number: 1-0011

Disease: Cancer

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