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Current Genomics

Editor-in-Chief

ISSN (Print): 1389-2029
ISSN (Online): 1875-5488

Ovarian Cancer Biomarkers: A Focus on Genomic and Proteomic Findings

Author(s): Andrea Tinelli, Daniele Vergara, Roberta Martignago, Giuseppe Leo, Antonio Malvasi, Raffaele Tinelli, Santo Marsigliante, Michele Maffia and Vito Lorusso

Volume 8, Issue 5, 2007

Page: [335 - 342] Pages: 8

DOI: 10.2174/138920207782446142

Price: $65

Abstract

Among the gynaecological malignancies, ovarian cancer is one of the neoplastic forms with the poorest prognosis and with the bad overall and disease-free survival rates than other gynaecological cancers; several studies, analyzing clinical data and pathological features on ovarian cancers, have focused on the identification of both diagnostic and prognostic markers for applications in clinical practice. High-throughput technologies have accelerated the process of biomarker discovery, but their validity should be still demonstrated by extensive researches on sensibility and sensitivity of ovarian cancer novel biomarkers, determining whether gene profiling and proteomics could help differentiate between patients with metastatic ovarian cancer and primary ovarian carcinomas, and their potential impact on management. Therefore, considerable interest lies in identifying molecular prognostic biomarkers and protein indicators to guide treatment decisions and clinical follow up; the current state of knowledge about the potential clinical value of gene expression profiling in ovarian cancer is discussed, focusing on three main areas: distinguishing normal ovarian tissue from ovarian tumors, identifying different subtypes of ovarian cancer and identifying cancer likely to be responsive to therapy. In this elaborate we discuss the use of novel molecules, discovered by proteomics and genomics approaches, as potential protein biomarkers in the management of ovarian cancer, to improve the anticancer therapy for malignant ovarian tumors and to monitor the clinical follow up.

Keywords: Ovarian cancer, biomarkers, proteomics, genomics, management


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