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Current State of Animal (Mouse) Modeling in Melanoma Research
Omer F Kuzu1, Felix D Nguyen2, Mohammad A Noory1
1Department of Pharmacology, The Pennsylvania State University College of Medicine, Hershey, PA, USA.
Abstract:
Despite the considerable progress in understanding the biology of human cancer and technological advancement in drug discovery, treatment failure remains an inevitable outcome for most cancer patients with advanced diseases, including melanoma. Despite FDA-approved BRAF-targeted therapies for advanced stage melanoma showed a great deal of promise, development of rapid resistance limits the success. Hence, the overall success rate of melanoma therapy still remains to be one of the worst compared to other malignancies. Advancement of next-generation sequencing technology allowed better identification of alterations that trigger melanoma development. As development of successful therapies strongly depends on clinically relevant preclinical models, together with the new findings, more advanced melanoma models have been generated. In this article, besides traditional mouse models of melanoma, we will discuss recent ones, such as patient-derived tumor xenografts, topically inducible BRAF mouse model and RCAS/TVA-based model, and their advantages as well as limitations. Although mouse models of melanoma are often criticized as poor predictors of whether an experimental drug would be an effective treatment, development of new and more relevant models could circumvent this problem in the near future.
Insights
Developing advanced melanoma models is crucial for overcoming treatment resistance and improving therapeutic success rates in melanoma patients. New models offer better prediction of drug efficacy for this challenging cancer.
Area of Science:
- Oncology
- Cancer Biology
- Drug Discovery
Background:
- Melanoma treatment failure is common, especially in advanced stages, due to rapid resistance to targeted therapies like BRAF inhibitors.
- Despite advancements, melanoma therapy success rates remain low compared to other cancers.
- Next-generation sequencing aids in identifying genetic alterations driving melanoma development.
Purpose of the Study:
- To review and discuss the advantages and limitations of various melanoma preclinical models.
- To highlight the importance of clinically relevant models for advancing melanoma therapy.
- To explore recent developments in melanoma modeling beyond traditional approaches.
Main Methods:
- Review of traditional mouse models for melanoma research.
- Discussion of advanced models including patient-derived tumor xenografts (PDTXs).
- Analysis of topical BRAF mouse models and RCAS/TVA-based systems.
Main Results:
- Various melanoma models exist, each with unique strengths and weaknesses.
- Advanced models like PDTXs offer greater clinical relevance.
- Newer models show promise in overcoming limitations of traditional approaches.
Conclusions:
- Development of more relevant preclinical melanoma models is essential for predicting drug efficacy.
- Improved models can help circumvent the current limitations in predicting treatment success.
- Future research focusing on advanced melanoma models may significantly improve therapeutic outcomes.
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