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Reprod Biol Endocrinol. 2003; 1: 67.
Published online 2003 October 7. doi: 10.1186/1477-7827-1-67.
PMCID: PMC270002
Animal models of ovarian cancer
Barbara C Vanderhyden,corresponding author1,2,3 Tanya J Shaw,1,3 and Jean-François Ethier1,3
1Department of Cellular and Molecular Medicine, University of Ottawa, 451 Smyth Road, Ottawa, Ontario, Canada K1H 8M5
2Department of Obstetrics and Gynecology, University of Ottawa, 501 Smyth Road, Ottawa, Ontario, Canada K1H 8L6
3Ottawa Regional Cancer Centre, 503 Smyth Road, Ottawa, Ontario, Canada K1H 1C4
corresponding authorCorresponding author.
Barbara C Vanderhyden: Barbara.Vanderhyden/at/orcc.on.ca; Tanya J Shaw: tshaw018/at/uottawa.ca; Jean-François Ethier: jfethier/at/uottawa.ca
Received June 28, 2003; Accepted October 7, 2003.
Abstract
Ovarian cancer is the most lethal of all of the gynecological cancers and can arise from any cell type of the ovary, including germ cells, granulosa or stromal cells. However, the majority of ovarian cancers arise from the surface epithelium, a single layer of cells that covers the surface of the ovary. The lack of a reliable and specific method for the early detection of epithelial ovarian cancer results in diagnosis occurring most commonly at late clinical stages, when treatment is less effective. In part, the deficiency in diagnostic tools is due to the lack of markers for the detection of preneoplastic or early neoplastic changes in the epithelial cells, which reflects our rather poor understanding of this process. Animal models which accurately represent the cellular and molecular changes associated with the initiation and progression of human ovarian cancer have significant potential to facilitate the development of better methods for the early detection and treatment of ovarian cancer. This review describes some of the experimental animal models of ovarian tumorigenesis that have been reported, including those involving specific reproductive factors and environmental toxins. Consideration has also been given to the recent progress in modeling ovarian cancer using genetically engineered mice.