Ovarian cancer biomarkers for molecular biosensors and translational medicine. (November 2010)

• Record Type: Journal Article
• Authors: Suh, K Stephen; Park, Sang W; Castro, Angelica; Patel, Hiren; Blake, Patrick; Liang, Michael; Goy, Andre
• Is Part Of: Expert review of molecular diagnostics. Volume 10:Number 8(2010)
• Page Start: 1069
• Page End: 1083
• Publication Date: 2010-11
• Subjects: biomarker -- biosensor -- ovarian cancer -- personalized medicine -- tissue bank; Molecular diagnosis -- Periodicals; 616.0758205
• DOI: 10.1586/erm.10.87
• Languages: English
• ISSNs: 1473-7159

Abstract

Multiple omics researches in the past two decades have identified over 200 potential biomarkers for ovarian cancer. Discoveries during the 1990s were more focused on clinicopathology-based biomarkers that were targeted to support diagnosis, but the emphasis has shifted to the identification of prognostic biomarkers in the past 10 years. The post-genomic era has opened the door for personalized cancer treatments and the trend of discovery is moving forward to identify more stratified biomarkers to accurately predict the progression of disease, as well as efficacy biomarkers to precisely determine drug response. To better meet future challenges, biomedical research needs the reformed and standardized infrastructure of tissue banks/biorepositories, with national and international initiatives. Of the hundreds of biomarker candidates for ovarian cancer, only a small number are actively being validated with clinical samples, owing to the lack of biomaterials that are linked with accurate clinical data. The purpose of this article is to present selected biomarkers from the past 20 years of ovarian cancer research, placing special emphasis on biomarkers that are strongly associated with positive or negative clinical outcomes. The article also presents a global view of all known potential biomarkers and mutations for ovarian cancer from NCI's Cancer Gene Index developed by Sophic, and Sanger's Catalogue of Somatic Mutations in Cancer database.