Liu Yijun, Song Fuhu, Li Zhi, Chen Liang, Xu Ying, Sun Huiyan, Chang Yi
School of Artificial Intelligence, Jilin University, Changchun, China.
Medical Oncology Department, The First Affiliated Hospital of China Medical University, Shenyang, China.
Front Pharmacol. 2023 Jan 12;14:1085765. doi: 10.3389/fphar.2023.1085765. eCollection 2023.
Cancer precision medicine is an effective strategy to fight cancers by bridging genomics and drug discovery to provide specific treatment for patients with different genetic characteristics. Although some public databases and modelling frameworks have been developed through studies on drug response, most of them only considered the ramifications of the drug on the cell line and the effects on the patient still require a huge amount of work to integrate data from various databases and calculations, especially concerning precision treatment. Furthermore, not only efficacy but also the adverse effects of drugs on patients should be taken into account during cancer treatment. However, the adverse effects as essential indicators of drug safety assessment are always neglected. A holistic estimation explores various drugs' efficacy levels by calculating their potency both in reversing and enhancing cancer-associated gene expression change. And a method for bridging the gap between cell culture and living tissue estimates the effectiveness of a drug on individual patients through the mappings of various cell lines to each person according to their genetic mutation similarities. We predicted the efficacy of FDA-recommended drugs, taking into account both efficacy and toxicity, and obtained consistent results. We also provided an intuitive and easy-to-use web server called DBPOM (http://www.dbpom.net/, a comprehensive database of pharmaco-omics for cancer precision medicine), which not only integrates the above methods but also provides calculation results on more than 10,000 small molecule compounds and drugs. As a one-stop web server, clinicians and drug researchers can also analyze the overall effect of a drug or a drug combination on cancer patients as well as the biological functions that they target. DBPOM is now public, free to use with no login requirement, and contains all the data and code. Both the positive and negative effects of drugs during precision treatment are essential for practical application of drugs. DBPOM based on the two effects will become a vital resource and analysis platform for drug development, drug mechanism studies and the discovery of new therapies.
癌症精准医学是一种通过将基因组学与药物研发相结合,为具有不同遗传特征的患者提供个性化治疗,从而对抗癌症的有效策略。尽管通过对药物反应的研究已经开发了一些公共数据库和建模框架,但其中大多数仅考虑了药物对细胞系的影响,而要整合来自各种数据库的数据和计算来评估药物对患者的影响,尤其是精准治疗方面,仍需要大量工作。此外,在癌症治疗过程中,不仅要考虑药物的疗效,还应考虑其对患者的不良反应。然而,作为药物安全性评估重要指标的不良反应却一直被忽视。一种整体评估方法通过计算各种药物在逆转和增强癌症相关基因表达变化方面的效力来探索其疗效水平。一种弥合细胞培养与活体组织之间差距的方法,通过根据个体患者与各种细胞系的基因突变相似性进行映射,来估计药物对个体患者的有效性。我们在兼顾疗效和毒性的情况下,预测了美国食品药品监督管理局(FDA)推荐药物的疗效,并得到了一致的结果。我们还提供了一个直观且易于使用的网络服务器,名为DBPOM(http://www.dbpom.net/,一个用于癌症精准医学的药物基因组学综合数据库),它不仅整合了上述方法,还提供了一万多种小分子化合物和药物的计算结果。作为一个一站式网络服务器,临床医生和药物研究人员还可以分析一种药物或药物组合对癌症患者的总体效果以及它们所靶向的生物学功能。DBPOM现已公开,无需登录即可免费使用,并且包含所有数据和代码。药物在精准治疗中的正负效应对于药物的实际应用都至关重要。基于这两种效应的DBPOM将成为药物开发、药物作用机制研究和新疗法发现的重要资源和分析平台。