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

被引:8
|
作者
Han, Jeremy Z. R. [1 ]
Hastings, Jordan E. [1 ]
Phimmachanh, Monica [1 ]
Fey, Dirk [2 ,3 ]
Kolch, Walter [2 ,3 ]
Croucher, David R. [1 ,4 ]
机构
[1] Garvan Inst Med Res, Sydney, NSW 2010, Australia
[2] Univ Coll Dublin, Sch Med, Syst Biol Ireland, Dublin 4, Ireland
[3] Univ Coll Dublin, Conway Inst, Dublin 4, Ireland
[4] UNSW Sydney, St Vincents Hosp Clin Sch, Sydney, NSW 2052, Australia
来源
JOURNAL OF PERSONALIZED MEDICINE | 2021年 / 11卷 / 05期
基金
澳大利亚国家健康与医学研究理事会; 爱尔兰科学基金会;
关键词
neuroblastoma; personalized medicine; chemotherapy; dynamic modelling; patient-specific modelling; apoptosis; HISTONE DEACETYLASE INHIBITORS; REFRACTORY SOLID TUMORS; HIGH-RISK NEUROBLASTOMA; GROWTH-FACTOR RECEPTOR; DNA METHYLATION; TRK GENE; PHASE-I; CANCER; EXPRESSION; RESISTANCE;
D O I
10.3390/jpm11050395
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
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.
引用
收藏
页数:16
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