Epithelial ovarian cancer: Focus on genetics and animal models

  • Shan W
  • Liu J
  • 5


    Mendeley users who have this article in their library.
  • 24


    Citations of this article.


Despite rapid advances in understanding ovarian cancer etiology, epithelial ovarian cancer remains the most lethal form of gynecologic cancers in the United States. The four morphologically-defined epithelial ovarian cancer subtypes-serous, endometrioid, mucinous, and clear cell carcinomas--are generally believed to originate from ovarian epithelial cells. Although it remains unclear how this single cell layer gives rise to morphologically distinct cancers, it has been suggested that early genetic events may direct the differentiation of ovarian epithelial cells. A number of genetic alterations are frequently encountered during ovarian tumorigenesis, including oncogenic activities of KRAS, BRAF and AKT, and silencing mutations of TP53, RB and PTEN. However, knowledge about how these genetic elements are coordinated during ovarian cancer initiation and progression is very limited. The establishment of cell-culture systems and rodent-based models has made big strides towards a better understanding of the genetic bases of human epithelial ovarian tumorigenesis. More importantly, the rise of genetically-engineered rodent and human models, particularly in the past five years, has provided key insight in the role of specific genes during ovarian tumorigenesis. In this review, we offer a comprehensive coverage of currently-available in vitro and in vivo models of human epithelial ovarian cancer, focusing on latest updates of genetically-modified rodent and human models and the valuable information conveyed by them.

Author-supplied keywords

  • Epithelial ovarian cancer
  • Genetically-modified animal models
  • Ovarian epithelial cells
  • Review
  • Tumorigenesis

Get free article suggestions today

Mendeley saves you time finding and organizing research

Sign up here
Already have an account ?Sign in

Find this document

Get full text


  • Weiwei Shan

  • Jinsong Liu

Cite this document

Choose a citation style from the tabs below

Save time finding and organizing research with Mendeley

Sign up for free