Prevention and early detection offers a substantial opportunity to improve management of ovarian cancer. Given the prevalence of ovarian cancer in the general population, screening strategies must be highly sensitive and specific. Identification of women at increased risk for sporadic ovarian cancer could reduce the stringent requirement for specificity and enhance the cost effectiveness of screening. No protein biomarker for ovarian cancer risk has yet been identified. We have demonstrated that prolactin (PRL), a multifunctional hormone/cytokine, is elevated in blood of over 60% of healthy women with a strong family history of ovarian cancer suggesting that PRL may be a risk biomarker for this cancer. There is increasing evidence that PRL plays a role in several types of cancer via local production or accumulation. PRL has been reported to activate several oncogenes including Ras oncogenes. We hypothesize that PRL is a risk factor for ovarian cancer in both familial and sporadic disease. PRL is involved in promotion of ovarian tumorigenesis by activation of Ras oncogenes. We further hypothesize that local production of extra pituitary PRL is involved in tumor growth. To test these hypotheses, the following Specific Aims are proposed. 1. Detect PRL expression in sera from a large cohort of women at increased risk with a strong family history of ovarian cancer and in women at conventional risk destined to develop ovarian cancer in a retrospective longitudinal PLCO study. Serum PRL will be analyzed in a large cohort of women with strong family history of ovarian cancer. In the PLCO study, serum PRL levels will be measured in women who are destined to develop ovarian cancer and in women who did not develop cancer to determine how soon elevated serum PRL levels can be observed prior to diagnosis and how frequently elevated serum PRL levels are observed 5-7 years prior to diagnosis. 2. Identify the source of elevated serum PRL in ovarian cancer. As prolactin can be produced by the pituitary as well as by cancer tissue, we will correlate expression of PRL in ovarian tumors with its serum expression. 3. Determine whether PRL can promote progression of Ras-driven ovarian oncogenesis in human models both in vitro and in xenografts. We will utilize cell lines derived from normal ovarian surface epithelium cells by disruption of p53 and Rb pathway by SV40 and introduction of hTERT. These cell lines are immortalized but not transformed, and become fully transformed and tumorigenic upon activation of Ras. These cells will be incubated with PRL or transfected with hPRL construct to assess the effects of elevated PRL on Ras activation and cell transformation. Cell transformation will be assessed based on the clonogenic capacity and in vivo tumorigenicity of cells subjected to elevated PRL. At the conclusion of this project, we expect to confirm the role of PRL as a risk factor for ovarian cancer, and to begin discerning mechanistic basis of this phenomenon. The successful completion of the proposed studies will allow identification of subpopulation of women with high risk of ovarian cancer and eventually development of effective chemopreventive strategy. Anna Lokshin R03 Narrative - Prolactin as a risk biomarker of ovarian cancer in this application, we propose to test the hypothesis that prolactin, a multifunctional pituitary protein, is a risk factor for ovarian cancer. This hypothesis will be examined using retrospectively collected longitudinal samples from PLSO/NIH trial. We further hypothesize that prolactin promotes neoplastic transformation via activation of Ras oncogene. This model will be tested in a mouse model using partially transformed ovarian epithelium cell lines. At the conclusion of the proposed study we expect to verify a role of prolactin as a risk factor of ovarian cancer, and start discerning the mechanisms of its activity as a promoter in ovarian neoplastic transformation. Upon successful completion of the proposed study future studies will be designed to inhibit prolactin expression for ovarian cancer prevention. ? ? ?
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