Kuzu Omer F, Nguyen Felix D, Noory Mohammad A, Sharma Arati
Department of Pharmacology, The Pennsylvania State University College of Medicine, Hershey, PA, USA.
The University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
Cancer Growth Metastasis. 2015 Oct 6;8(Suppl 1):81-94. doi: 10.4137/CGM.S21214. eCollection 2015.
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.
尽管在理解人类癌症生物学方面取得了显著进展,以及在药物发现方面技术有所进步,但对于大多数患有晚期疾病(包括黑色素瘤)的癌症患者来说,治疗失败仍然是不可避免的结果。尽管美国食品药品监督管理局(FDA)批准的针对晚期黑色素瘤的BRAF靶向疗法显示出很大的前景,但快速产生耐药性限制了其成功。因此,与其他恶性肿瘤相比,黑色素瘤治疗的总体成功率仍然是最差的之一。下一代测序技术的进步使得能够更好地识别引发黑色素瘤发展的改变。由于成功疗法的开发强烈依赖于临床相关的临床前模型,随着新发现的出现,已经产生了更先进的黑色素瘤模型。在本文中,除了传统的黑色素瘤小鼠模型外,我们还将讨论最近的模型,如患者来源的肿瘤异种移植模型、局部诱导的BRAF小鼠模型和基于RCAS/TVA的模型,以及它们的优点和局限性。尽管黑色素瘤小鼠模型经常被批评为实验药物是否会成为有效治疗方法的不良预测指标,但新的和更相关模型的开发可能在不久的将来规避这个问题。