Literature DB >> 23434073

Revisiting ovarian cancer preclinical models: implications for a better management of the disease.

Francesca Ricci1, Massimo Broggini, Giovanna Damia.   

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.
Copyright © 2013 Elsevier Ltd. All rights reserved.

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Year:  2013        PMID: 23434073     DOI: 10.1016/j.ctrv.2013.01.005

Source DB:  PubMed          Journal:  Cancer Treat Rev        ISSN: 0305-7372            Impact factor:   12.111


  18 in total

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Journal:  Mater Today (Kidlington)       Date:  2022-02-23       Impact factor: 26.943

4.  Methodologies for the establishment of an orthotopic transplantation model of ovarian cancer in mice.

Authors:  Cunjian Yi; Lei Zhang; Fayun Zhang; Li Li; Shengrong Ling; Xiaowen Wang; Xiangqiong Liu; Wei Liang
Journal:  Front Med       Date:  2014-01-25       Impact factor: 4.592

Review 5.  Personalized models of heterogeneous 3D epithelial tumor microenvironments: Ovarian cancer as a model.

Authors:  Eric N Horst; Michael E Bregenzer; Pooja Mehta; Catherine S Snyder; Taylor Repetto; Yang Yang-Hartwich; Geeta Mehta
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6.  Murine model for non-invasive imaging to detect and monitor ovarian cancer recurrence.

Authors:  Natalia J Sumi; Eydis Lima; John Pizzonia; Sean P Orton; Vinicius Craveiro; Wonduk Joo; Jennie C Holmberg; Marta Gurrea; Yang Yang-Hartwich; Ayesha Alvero; Gil Mor
Journal:  J Vis Exp       Date:  2014-11-02       Impact factor: 1.355

7.  A new spontaneously transformed syngeneic model of high-grade serous ovarian cancer with a tumor-initiating cell population.

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Review 8.  Advances in tumor screening, imaging, and avatar technologies for high-grade serous ovarian cancer.

Authors:  Anders W Ohman; Noor Hasan; Daniela M Dinulescu
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Review 9.  Recent technological advances in using mouse models to study ovarian cancer.

Authors:  Carrie Danielle House; Lidia Hernandez; Christina Messineo Annunziata
Journal:  Front Oncol       Date:  2014-02-13       Impact factor: 6.244

10.  First in-mouse development and application of a surgically relevant xenograft model of ovarian carcinoma.

Authors:  Oystein Helland; Mihaela Popa; Olav K Vintermyr; Anders Molven; Bjørn Tore Gjertsen; Line Bjørge; Emmet McCormack
Journal:  PLoS One       Date:  2014-03-04       Impact factor: 3.240

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