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神经母细胞瘤的个性化医学:从静态基因型转向药物反应的动态模拟

Personalized Medicine for Neuroblastoma: Moving from Static Genotypes to Dynamic Simulations of Drug Response.

作者信息

Han Jeremy Z R, Hastings Jordan F, Phimmachanh Monica, Fey Dirk, Kolch Walter, Croucher David R

机构信息

Garvan Institute of Medical Research, Sydney, NSW 2010, Australia.

Systems Biology Ireland, School of Medicine, University College Dublin, Belfield, Dublin 4, Ireland.

出版信息

J Pers Med. 2021 May 11;11(5):395. doi: 10.3390/jpm11050395.

Abstract

High-risk neuroblastoma is an aggressive childhood cancer that is characterized by high rates of chemoresistance and frequent metastatic relapse. A number of studies have characterized the genetic and epigenetic landscape of neuroblastoma, but due to a generally low mutational burden and paucity of actionable mutations, there are few options for applying a comprehensive personalized medicine approach through the use of targeted therapies. Therefore, the use of multi-agent chemotherapy remains the current standard of care for neuroblastoma, which also conceptually limits the opportunities for developing an effective and widely applicable personalized medicine approach for this disease. However, in this review we outline potential approaches for tailoring the use of chemotherapy agents to the specific molecular characteristics of individual tumours by performing patient-specific simulations of drug-induced apoptotic signalling. By incorporating multiple layers of information about tumour-specific aberrations, including expression as well as mutation data, these models have the potential to rationalize the selection of chemotherapeutics contained within multi-agent treatment regimens and ensure the optimum response is achieved for each individual patient.

摘要

高危神经母细胞瘤是一种侵袭性儿童癌症,其特征是化疗耐药率高且频繁发生转移性复发。许多研究已经对神经母细胞瘤的基因和表观遗传特征进行了描述,但由于总体突变负担较低且可操作的突变较少,通过使用靶向疗法应用全面的个性化医疗方法的选择有限。因此,使用多药化疗仍然是目前神经母细胞瘤的治疗标准,这在概念上也限制了为这种疾病开发有效且广泛适用的个性化医疗方法的机会。然而,在本综述中,我们概述了通过对药物诱导的凋亡信号进行患者特异性模拟,根据个体肿瘤的特定分子特征调整化疗药物使用的潜在方法。通过整合关于肿瘤特异性畸变的多层信息,包括表达以及突变数据,这些模型有可能使多药治疗方案中所含化疗药物的选择合理化,并确保每个患者都能实现最佳反应。

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