Related Experiment Video
Updated: May 13, 2026
Murine Model for Non-invasive Imaging to Detect and Monitor Ovarian Cancer Recurrence
Published on: November 2, 2014
Revisiting ovarian cancer preclinical models: implications for a better management of the disease
Francesca Ricci1, Massimo Broggini, Giovanna Damia
1Laboratory of Molecular Pharmacology, Department of Oncology, Istituto di Ricerche Farmacologiche Mario Negri, Via La Masa 19, 20156 Milan, Italy.
Abstract:
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 30years 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.
Insights
Preclinical ovarian cancer models, especially genetically engineered mouse (GEM) models, are crucial for understanding epithelial ovarian cancer (EOC) development and progression. These advanced models aid in testing new drug combinations for improved patient outcomes.
Area of Science:
- Oncology
- Gynecologic Oncology
- Cancer Biology
Background:
- Epithelial ovarian cancer (EOC) remains a highly lethal gynecologic malignancy with limited survival improvements despite advances in genetic understanding.
- Current platinum-based treatments, introduced over 30 years ago, have not significantly altered patient survival rates.
- Effective development of novel anticancer drugs necessitates accurate preclinical models that replicate human cancer complexity.
Purpose of the Study:
- To review and analyze available preclinical ovarian cancer models.
- To understand the biological mechanisms underlying EOC development, progression, invasion, and metastasis.
- To evaluate the utility of different models in advancing ovarian cancer research.
Main Methods:
- Literature review of preclinical ovarian cancer models.
- Comparative analysis of xenograft models and genetically engineered mouse (GEM) models.
- Examination of how these models contribute to understanding EOC pathology.
Main Results:
- Preclinical models have been instrumental in elucidating the pathological events in ovarian carcinoma.
- Genetically engineered mouse (GEM) models offer advantages over xenograft models, including orthotopic tumor development and immunocompetence.
- GEM models more closely mimic the behavior and complexity of human ovarian cancers.
Conclusions:
- Preclinical models are vital for advancing the understanding of epithelial ovarian cancer.
- Genetically engineered mouse (GEM) models represent a significant improvement for studying EOC.
- GEM models are poised to play a key role in optimizing drug regimens for clinical trials, potentially reducing costs and improving efficacy.
