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Gene expression profiling and prediction of clinical outcome in ovarian cancer
Authors:Renaud  Pascal  Nathalie  Daniel  Franois
Institution:aCentre de Recherche en Cancérologie de Marseille (CRCM), Département d’Oncologie Moléculaire, UMR891 Inserm, Institut Paoli-Calmettes (IPC), IFR137, Marseille, France;bDépartement d’Oncologie Médicale, IPC, Marseille, France;cFaculté de Médecine, Université de la Méditerranée, Marseille, France
Abstract:Epithelial ovarian cancer is the most lethal gynaecological cancer. Despite debulking surgery and platinum/taxane-based chemotherapy, the prognosis remains poor with not, vert, similar25% 5-year survival. Current histo-clinical prognostic factors are insufficient to capture the complex cascade of events that drive the heterogeneous clinical behaviour of the disease. There is a crucial need to identify new prognostic subclasses of disease as well as new therapeutic targets. Today, DNA microarrays allow the simultaneous and quantitative analysis of the mRNA expression levels of thousands of genes in a tumour sample. They have been applied to ovarian cancer research for predicting initial surgical resectability, survival and response to first-line chemotherapy. The first results are promising. In this review, we describe recent applications of DNA microarrays in ovarian cancer research and discuss some issues to address in the near future to allow the technology to reach its full potential in clinical practice.
Keywords:Ovarian cancer  DNA microarray  Prognosis  Gene expression profiling
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