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多模型临床前平台预测黑色素瘤对免疫治疗的临床反应。

Multimodel preclinical platform predicts clinical response of melanoma to immunotherapy.

机构信息

Laboratory of Cancer Biology and Genetics, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.

Cancer and Inflammation Program, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.

出版信息

Nat Med. 2020 May;26(5):781-791. doi: 10.1038/s41591-020-0818-3. Epub 2020 Apr 13.

Abstract

Although immunotherapy has revolutionized cancer treatment, only a subset of patients demonstrate durable clinical benefit. Definitive predictive biomarkers and targets to overcome resistance remain unidentified, underscoring the urgency to develop reliable immunocompetent models for mechanistic assessment. Here we characterize a panel of syngeneic mouse models, representing a variety of molecular and phenotypic subtypes of human melanomas and exhibiting their diverse range of responses to immune checkpoint blockade (ICB). Comparative analysis of genomic, transcriptomic and tumor-infiltrating immune cell profiles demonstrated alignment with clinical observations and validated the correlation of T cell dysfunction and exclusion programs with resistance. Notably, genome-wide expression analysis uncovered a melanocytic plasticity signature predictive of patient outcome in response to ICB, suggesting that the multipotency and differentiation status of melanoma can determine ICB benefit. Our comparative preclinical platform recapitulates melanoma clinical behavior and can be employed to identify mechanisms and treatment strategies to improve patient care.

摘要

尽管免疫疗法已经彻底改变了癌症治疗方法,但只有一部分患者能从中获得持久的临床获益。目前仍未确定明确的预测性生物标志物和靶点来克服耐药性,这突显了开发可靠的免疫活性模型以进行机制评估的紧迫性。在这里,我们描述了一组同基因小鼠模型,这些模型代表了人类黑色素瘤的多种分子和表型亚型,并表现出对免疫检查点阻断(ICB)的不同反应范围。对基因组、转录组和肿瘤浸润免疫细胞谱的比较分析表明与临床观察一致,并验证了 T 细胞功能障碍和排除程序与耐药性的相关性。值得注意的是,全基因组表达分析揭示了一个预测黑色素瘤患者对 ICB 反应的黑素细胞可塑性特征,表明黑色素瘤的多能性和分化状态可以决定 ICB 的获益。我们的比较临床前平台再现了黑色素瘤的临床行为,可用于确定改善患者治疗的机制和治疗策略。

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