个性化医疗
抗药性
精密医学
癌症
靶向治疗
限制
医学
计算生物学
基因组学
生物
药品
基因组
深度测序
生物信息学
遗传学
基因
药理学
机械工程
工程类
作者
Bissan Al‐Lazikani,Udai Banerji,Paul Workman
摘要
Over the past decade, whole genome sequencing and other 'omics' technologies have defined pathogenic driver mutations to which tumor cells are addicted. Such addictions, synthetic lethalities and other tumor vulnerabilities have yielded novel targets for a new generation of cancer drugs to treat discrete, genetically defined patient subgroups. This personalized cancer medicine strategy could eventually replace the conventional one-size-fits-all cytotoxic chemotherapy approach. However, the extraordinary intratumor genetic heterogeneity in cancers revealed by deep sequencing explains why de novo and acquired resistance arise with molecularly targeted drugs and cytotoxic chemotherapy, limiting their utility. One solution to the enduring challenge of polygenic cancer drug resistance is rational combinatorial targeted therapy.
科研通智能强力驱动
Strongly Powered by AbleSci AI