Pradnya R Kamble1, Apoorva Pawar1, Ananya A Breed1, Grishma Kasle1,2, Bhakti R Pathak3. 1. Cellular and Structural Biology Division, National Institute for Research in Reproductive Health (ICMR), Jehangir Merwanji Street, Parel, Mumbai, 400012, India. 2. Division of Biological Sciences, IISER, Kolkata, India. 3. Cellular and Structural Biology Division, National Institute for Research in Reproductive Health (ICMR), Jehangir Merwanji Street, Parel, Mumbai, 400012, India. pathakb@nirrh.res.in.
Abstract
BACKGROUND: Ovarian cancer is usually detected at an advanced stage with frequent recurrence. The recurrence-free survival and overall survival is influenced by the age at diagnosis, tumor stage and histological subtype. Nonetheless, quantifiable prognostic biomarkers are needed for early identification of the high-risk patients and for personalized medicine. Several studies link tumor-specific dysregulated expression of certain proteins with ovarian cancer prognosis. However, careful investigation of presence of these prognostically relevant proteins in ovarian cancer secretome is lacking. OBJECTIVE: To critically analyze the recent published data on prognostically relevant proteins for ovarian cancer and to carefully search how many of them are reported in the published ovarian cancer secretome datasets. DESIGN: A search for relevant studies in the past 2 years was conducted in PubMed and a comprehensive list of proteins associated with the ovarian cancer prognosis was prepared. These were cross-referred to the published ovarian cancer secretome profiles. The proteins identified in the secretome were further shortlisted based on a scoring strategy employing stringent criteria. RESULTS: A panel of seven promising secretory biomarkers associated with ovarian cancer prognosis is proposed. CONCLUSION: Scanning the ovarian cancer secretome datasets provides the opportunity to identify if tumor-specific biomarkers could be tested as secretory biomarkers. Detecting their levels in the body fluid would be more advantageous than evaluating the expression in the tissue, since it could be monitored multiple times over the course of the disease to have a better judgment of the prognosis and response to therapy.
BACKGROUND: Ovarian cancer is usually detected at an advanced stage with frequent recurrence. The recurrence-free survival and overall survival is influenced by the age at diagnosis, tumor stage and histological subtype. Nonetheless, quantifiable prognostic biomarkers are needed for early identification of the high-risk patients and for personalized medicine. Several studies link tumor-specific dysregulated expression of certain proteins with ovarian cancer prognosis. However, careful investigation of presence of these prognostically relevant proteins in ovarian cancer secretome is lacking. OBJECTIVE: To critically analyze the recent published data on prognostically relevant proteins for ovarian cancer and to carefully search how many of them are reported in the published ovarian cancer secretome datasets. DESIGN: A search for relevant studies in the past 2 years was conducted in PubMed and a comprehensive list of proteins associated with the ovarian cancer prognosis was prepared. These were cross-referred to the published ovarian cancer secretome profiles. The proteins identified in the secretome were further shortlisted based on a scoring strategy employing stringent criteria. RESULTS: A panel of seven promising secretory biomarkers associated with ovarian cancer prognosis is proposed. CONCLUSION: Scanning the ovarian cancer secretome datasets provides the opportunity to identify if tumor-specific biomarkers could be tested as secretory biomarkers. Detecting their levels in the body fluid would be more advantageous than evaluating the expression in the tissue, since it could be monitored multiple times over the course of the disease to have a better judgment of the prognosis and response to therapy.
Authors: Estrid V S Høgdall; Lise Christensen; Susanne K Kjaer; Jan Blaakaer; Anette Kjaerbye-Thygesen; Simon Gayther; Ian J Jacobs; Claus K Høgdall Journal: Gynecol Oncol Date: 2006-11-17 Impact factor: 5.482