He Binsheng, Hou Fangxing, Ren Changjing, Bing Pingping, Xiao Xiangzuo
Academician Workstation, Changsha Medical University, Changsha, China.
Queen Mary School, Nanchang University, Jiangxi, China.
Front Oncol. 2021 Jul 22;11:711225. doi: 10.3389/fonc.2021.711225. eCollection 2021.
Drug repositioning is a new way of applying the existing therapeutics to new disease indications. Due to the exorbitant cost and high failure rate in developing new drugs, the continued use of existing drugs for treatment, especially anti-tumor drugs, has become a widespread practice. With the assistance of high-throughput sequencing techniques, many efficient methods have been proposed and applied in drug repositioning and individualized tumor treatment. Current computational methods for repositioning drugs and chemical compounds can be divided into four categories: (i) feature-based methods, (ii) matrix decomposition-based methods, (iii) network-based methods, and (iv) reverse transcriptome-based methods. In this article, we comprehensively review the widely used methods in the above four categories. Finally, we summarize the advantages and disadvantages of these methods and indicate future directions for more sensitive computational drug repositioning methods and individualized tumor treatment, which are critical for further experimental validation.
药物重新定位是将现有治疗方法应用于新疾病适应症的一种新方式。由于开发新药的成本过高且失败率高，继续使用现有药物进行治疗，尤其是抗肿瘤药物，已成为一种普遍做法。在高通量测序技术的辅助下，已经提出并应用了许多有效的方法用于药物重新定位和个体化肿瘤治疗。当前用于药物和化合物重新定位的计算方法可分为四类：（i）基于特征的方法，（ii）基于矩阵分解的方法，（iii）基于网络的方法，以及（iv）基于逆转录组的方法。在本文中，我们全面回顾了上述四类中广泛使用的方法。最后，我们总结了这些方法的优缺点，并指出了更敏感的计算药物重新定位方法和个体化肿瘤治疗的未来方向，这对于进一步的实验验证至关重要。
