阿凡达
斑马鱼
个性化医疗
计算机科学
计算生物学
医学
人机交互
生物
生物信息学
遗传学
基因
作者
Bruna Costa,Marta F Estrada,R. Vilela Mendes,Rita Fior
出处
期刊:Cells
[MDPI AG]
日期:2020-01-25
卷期号:9 (2): 293-293
被引量:53
摘要
Cancer frequency and prevalence have been increasing in the past decades, with devastating impacts on patients and their families. Despite the great advances in targeted approaches, there is still a lack of methods to predict individual patient responses, and therefore treatments are tailored according to average response rates. "Omics" approaches are used for patient stratification and choice of therapeutic options towards a more precise medicine. These methods, however, do not consider all genetic and non-genetic dynamic interactions that occur upon drug treatment. Therefore, the need to directly challenge patient cells in a personalized manner remains. The present review addresses the state of the art of patient-derived invitro and invivo models, from organoids to mouse and zebrafish Avatars. The predictive power of each model based on the retrospective correlation with the patient clinical outcome will be considered. Finally, the review is focused on the emerging zebrafish Avatars and their unique characteristics allowing a fast analysis of local and systemic effects of drug treatments at the single-cell level. We also address the technical challenges that the field has yet to overcome.
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