Metabolomics-based phenotypic screens for evaluation of drug synergy via direct-infusion mass spectrometry.
Metabolomics-based phenotypic screens for evaluation of drug synergy via direct-infusion mass spectrometry.
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DOI：
10.1016/j.isci.2022.104221
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发表时间：
2022-05-20
期刊：
影响因子：
5.8
通讯作者：
Tiziani S
中科院分区：
文献类型：
--
作者：
Lu X;Hackman GL;Saha A;Rathore AS;Collins M;Friedman C;Yi SS;Matsuda F;DiGiovanni J;Lodi A;Tiziani S
药物联合使用可以发挥协同作用，提高疗效、降低毒性、防止耐药性。虽然依赖单变量数据的传统高通量筛选对于识别有前途的候选药物非常有价值，但表型筛选方法可能有助于深入了解药物组合的分子反应，并有可能改善临床结果。我们开发了一个高内涵代谢组学药物筛选平台，使用稳定同位素示踪剂直接输注质谱法，为从多变量表组数据确定协同作用的算法提供信息。使用癌症药物库，我们在一组前列腺细胞系上验证了药物筛选，整合了富含同位素的代谢组学数据和计算数据挖掘，并在体外（三维模型）和体内验证了 CB-839 和多西紫杉醇之间的协同作用。所提出的无偏代谢组学筛选平台可用于快速生成表型信息数据集并量化组合药物发现的协同作用。开发了具有稳定同位素示踪剂的高内涵代谢组学筛选平台 该平台允许分配到不同的库筛选和体外模型 新算法非常强大，可应用于药物协同评估的组学数据集 在体内发现并验证了治疗前列腺癌的新药物组合；代谢组学；组学；药物信息学
Drugs used in combination can synergize to increase efficacy, decrease toxicity, and prevent drug resistance. While conventional high-throughput screens that rely on univariate data are incredibly valuable to identify promising drug candidates, phenotypic screening methodologies could be beneficial to provide deep insight into the molecular response of drug combination with a likelihood of improved clinical outcomes. We developed a high-content metabolomics drug screening platform using stable isotope-tracer direct-infusion mass spectrometry that informs an algorithm to determine synergy from multivariate phenomics data. Using a cancer drug library, we validated the drug screening, integrating isotope-enriched metabolomics data and computational data mining, on a panel of prostate cell lines and verified the synergy between CB-839 and docetaxel both in vitro (three-dimensional model) and in vivo. The proposed unbiased metabolomics screening platform can be used to rapidly generate phenotype-informed datasets and quantify synergy for combinatorial drug discovery. High-content metabolomics screening platform with stable isotope tracers was developed The platform allows for assignment to different library screens and in vitro models New algorithm is robust to apply on omics datasets for drug synergy evaluation Novel drug combination to treat prostate cancer was discovered and validated in vivo Bioinformatics; Metabolomics; Omics; Pharmacoinformatics
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影响因子：
46.9
作者：
Guijas C;Montenegro-Burke JR;Warth B;Spilker ME;Siuzdak G
通讯作者：
Siuzdak G
大规模代谢组分析确定了出现冠心病的新生物标志物。
影响因子：
4.5
作者：
Ganna A;Salihovic S;Sundström J;Broeckling CD;Hedman AK;Magnusson PK;Pedersen NL;Larsson A;Siegbahn A;Zilmer M;Prenni J;Arnlöv J;Lind L;Fall T;Ingelsson E
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16
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Zampieri, Mattia
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Foucquier, Julie;Guedj, Mickael
通讯作者：
Guedj, Mickael
影响因子：
3.6
作者：
Ganna, Andrea;Fall, Tove;Ingelsson, Erik
通讯作者：
Ingelsson, Erik