Patient-derived cancer models have been used for decades to improve our understanding of cancer and test anticancer treatments. Advances in radiation delivery have made these models more attractive for studying radiation sensitizers and understanding an individual patient's radiation sensitivity. Advances in the use of patient-derived cancer models lead to a more clinically relevant outcome, although many questions remain regarding the optimal use of patient-derived xenografts and patient-derived spheroid cultures. The use of patient-derived cancer models as personalized predictive avatars through mouse and zebrafish models is discussed, and the advantages and disadvantages of patient-derived spheroids are reviewed. In addition, the use of large repositories of patient-derived models to develop predictive algorithms to guide treatment selection is discussed. Finally, we review methods for establishing patient-derived models and identify key factors that influence their use as both avatars and models of cancer biology.

几十年来，患者衍生的癌症模型一直被用来提高我们对癌症的理解并测试抗癌治疗。放射输送的进步使这些模型对于研究放射增敏剂和了解个体患者的放射敏感性更具吸引力。尽管关于患者来源的异种移植物和患者来源的球体培养物的最佳使用仍存在许多问题，但患者来源的癌症模型的使用进展带来了更具临床相关性的结果。讨论了通过小鼠和斑马鱼模型使用患者来源的癌症模型作为个性化预测化身，并回顾了患者来源的球体的优点和缺点。此外，还讨论了使用源自患者的模型的大型存储库来开发预测算法来指导治疗选择。最后，我们回顾了建立患者衍生模型的方法，并确定了影响其用作癌症生物学的化身和模型的关键因素。