Ovarian Cancer Canada

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Revisiting Ovarian Cancer Preclinical Models: Implications for a Better Management of the Disease

Despite 30 years of experience with platinum-based therapy for epithelial ovarian cancer, oncologists must still contend with low survival rates for these patients. Italian researchers review current preclinical ovarian cancer models that offer a better understanding of how this malignancy develops, progresses, and metastasizes. The review authors contend that these preclinical models will play a key role in the selection of the most efficacious treatment regimens for epithelial ovarian cancer.” 

Ricci F, Broggini M, Damia G.

http://www.ncbi.nlm.nih.gov/pubmed/23434073Abstract

Epithelial ovarian cancer (EOC) is the most lethal gynecologic malignancy. Despite progress in identifying “hallmark” genetic alterations associated with the main subtypes of epithelial ovarian cancer, the survival rate of women with EOC changed little since platinum-based treatment was introduced more than 30 years ago. The successful identification of new, effective anticancer drugs largely depends on appropriate preclinical experimental models that should ideally mimic the complexity of different cancer forms.

This review examines the preclinical ovarian cancer models available for a better understanding of the biological mechanisms of the development, progression, invasion and metastasis of EOC. We provide evidence that the preclinical models have been instrumental for a better understanding of the pathological events at the basis of ovarian carcinoma.

The genetically engineered mouse (GEM) models of ovarian cancer have overcome some of the weaknesses of the xenograft models, such as the fact that these tumors arise orthotopically in immunologically intact mice and more closely resemble the behavior of human cancers. We envisage that in the near future these GEM models will play a key role in pre-selecting drug regimens with the greatest promise of efficacy in human clinical trials, making it easier and certainly less expensive to test new, different drug combinations.

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This entry was posted on October 16, 2013 by in Research Updates and tagged .

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