báo cáo hóa học:" Ovarian cancer mouse models: a summary of current models and their limitations"

Tuyển tập các báo cáo nghiên cứu về hóa học được đăng trên tạp chí sinh học quốc tế đề tài : Ovarian cancer mouse models: a summary of current models and their limitations | Journal of Ovarian Research BioMed Central Open Access Review Ovarian cancer mouse models a summary of current models and their limitations Miranda Y Fong and Sham S Kakar Address Department of Physiology and Biophysics James Graham Brown Cancer Center University of Louisville Louisville KY 40202 USA Email Miranda Y Fong - myfong01@ Sham S Kakar - sskaka01@ Corresponding author Published 28 September 2009 Received 30 July 2009 Journal of Ovarian Research 2009 2 12 doi 1757-2215-2-12 Accepted 28 September 2009 This article is available from http content 2 1 12 2009 Fong and Kakar licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License http licenses by which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. Abstract Development of mouse models representing human spontaneous ovarian cancer has been hampered by the lack of understanding of the etiology of this very complex disease. Mouse models representing the different types of ovarian cancer are needed to understand how epithelial ovarian cancer differs from granulosa cell tumors. Many different methods have been used to generate a viable genetic model with limited success. This review focuses on the methods of various investigators and the limitations of each model in establishing a reproducible and inheritable line to study this disease. Introduction Ovarian cancer OC is the most lethal malignancy of the female reproductive system and the fifth leading cause of cancer death in women 1 . Ninety percent of OC are thought to arise from the epithelium and its inclusion cysts 2 due to multiple genetic changes 3 . However the etiology of spontaneous epithelial E OC is poorly understood partially due to a lack of an appropriate experimental model. While many approaches have been used model .

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