后见之明:葡萄膜黑色素瘤新治疗方法开发的临床前疾病模型综述

Hindsight: Review of Preclinical Disease Models for the Development of New Treatments for Uveal Melanoma.

作者信息

Goldrick Caoimhe, Palanga Letizia, Tang Bobby, Mealy Grace, Crown John, Horgan Noel, Kennedy Susan, Walsh Naomi

机构信息

National Institute for Cellular Biotechnology, School of Biotechnology, Dublin City University, Dublin, Ireland.

Royal Victoria Eye and Ear Research Foundation, Royal Victoria Eye and Ear Hospital, Adelaide Road, Dublin, Ireland.

出版信息

J Cancer. 2021 Jun 4;12(15):4672-4685. doi: 10.7150/jca.53954. eCollection 2021.

Abstract

The molecular, histopathological, genomic and transcriptomic characteristics of uveal melanoma (UM) have identified four molecular subgroups with different clinical outcomes. Despite the improvements in UM classification and biological pathology, current treatments do not reduce the occurrence of metastasis. The development of effective adjuvant and metastatic therapies for UM has been slow and extremely limited. Preclinical models that closely resemble the molecular and genetic UM subgroups are essential for translating molecular findings into improved clinical treatment. In this review, we provide a retrospective view of the existing preclinical models used to study UM, and give an overview of their strengths and limitations. We review targeted therapy clinical trial data to evaluate the gap in the translation of preclinical findings to human studies. Reflecting on the current high attrition rates of clinical trials for UM, preclinical models that effectively recapitulate the human situation and/or accurately reflect the subtype classifications would enhance the translational impact of experimental data and have crucial implications for the advancement of personalised medicine.

摘要

葡萄膜黑色素瘤(UM)的分子、组织病理学、基因组和转录组特征已确定了具有不同临床结局的四个分子亚组。尽管UM分类和生物病理学有所改进,但目前的治疗方法并未降低转移的发生率。针对UM的有效辅助治疗和转移治疗的发展一直缓慢且极为有限。与UM分子和基因亚组极为相似的临床前模型对于将分子研究结果转化为改进的临床治疗至关重要。在本综述中,我们对用于研究UM的现有临床前模型进行了回顾,并概述了它们的优点和局限性。我们回顾了靶向治疗临床试验数据,以评估临床前研究结果转化为人体研究方面的差距。鉴于目前UM临床试验的高失败率,能够有效重现人体情况和/或准确反映亚型分类的临床前模型将增强实验数据的转化影响,并对个性化医学的发展具有至关重要的意义。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fec7/8210544/3e24fcd7c60d/jcav12p4672g001.jpg

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