SCI

19 October 2022

Towards precision oncology with patient-derived xenografts

(Nature Reviews Clinical Oncology, IF: 65.011)

Zanella ER, Grassi E, Trusolino L. Towards precision oncology with patient-derived xenografts. Nat Rev Clin Oncol 2022. DOI: 10.1038/s41571-022-00682-6.

Corresponding author: Livio Trusolino. Candiolo Cancer Institute - FPO IRCCS, Candiolo, Italy. Department of Oncology, University of T orino, Candiolo, Italy. livio.trusolino@ircc.it.

Abstract 摘要

Under the selective pressure of therapy, tumours dynamically evolve multiple adaptive mechanisms that make static interrogation of genomic alterations insufficient to guide treatment decisions. Clinical research does not enable the assessment of how various regulatory circuits in tumours are affected by therapeutic insults over time and space. Likewise, testing different precision oncology approaches informed by composite and ever-changing molecular information is hard to achieve in patients. Therefore, preclinical models that incorporate the biology and genetics of human cancers, facilitate analyses of complex variables and enable adequate population throughput are needed to pinpoint randomly distributed response predictors. Patient-derived xenograft (PDX) models are dynamic entities in which cancer evolution can be monitored through serial propagation in mice. PDX models can also recapitulate interpatient diversity, thus enabling the identification of response biomarkers and therapeutic targets for molecularly defined tumour subgroups. In this Review, we discuss examples from the past decade of the use of PDX models for precision oncology, from translational research to drug discovery. We elaborate on how and to what extent preclinical observations in PDX models have confirmed and/or anticipated findings in patients. Finally, we illustrate emerging methodological efforts that could broaden the application of PDX models by honing their predictive accuracy or improving their versatility.

在治疗的选择性压力下，肿瘤动态进化出多种适应机制，使静态的基因组改变监测不足以指导治疗决策。临床研究无法评估肿瘤中的各种调节回路是如何随时间和空间受到治疗压力的影响。同样，通过复杂且不断变化的分子信息来检测不同的精确肿瘤的方法也很难在患者中实现。因此，需要结合人类癌症的生物学和遗传学，促进复杂变量的分析，并能实现足够的人群吞吐量的临床前模型来精准确定随机分布的反应预测因子。病人来源的异种移植（PDX）模型是动态的实体，其中癌症的进化可以通过小鼠的连续繁殖来监测。PDX模型还可以重现患者间的多样性，从而使分子定义的肿瘤亚群的反应生物标志物和治疗靶点的识别成为可能。在这篇综述中，我们讨论了过去十年在精确肿瘤学中使用PDX模型的例子，从转化研究到药物发现。我们详细阐述了PDX模型的临床前观察如何以及在多大程度上证实和/或预测患者中的发现。最后，我们说明了新兴的方法，可以通过珩磨其预测精度或提高其通用性来扩大PDX模型的应用。

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