ASGARD 是一个单细胞指导管道，用于帮助药物的再利用。

ASGARD is A Single-cell Guided Pipeline to Aid Repurposing of Drugs.

机构信息

Department of Computational Medicine and Bioinformatics, Medical School, University of Michigan, Ann Arbor, MI, USA.

Department of Statistics, College of Literature, Science, and the Arts, University of Michigan, Ann Arbor, MI, USA.

出版信息

Nat Commun. 2023 Feb 22;14(1):993. doi: 10.1038/s41467-023-36637-3.

Single-cell RNA sequencing technology has enabled in-depth analysis of intercellular heterogeneity in various diseases. However, its full potential for precision medicine has yet to be reached. Towards this, we propose A Single-cell Guided Pipeline to Aid Repurposing of Drugs (ASGARD) that defines a drug score to recommend drugs by considering all cell clusters to address the intercellular heterogeneity within each patient. ASGARD shows significantly better average accuracy on single-drug therapy compared to two bulk-cell-based drug repurposing methods. We also demonstrated that it performs considerably better than other cell cluster-level predicting methods. In addition, we validate ASGARD using the drug response prediction method TRANSACT with Triple-Negative-Breast-Cancer patient samples. We find that many top-ranked drugs are either approved by the Food and Drug Administration or in clinical trials treating corresponding diseases. In conclusion, ASGARD is a promising drug repurposing recommendation tool guided by single-cell RNA-seq for personalized medicine. ASGARD is free for educational use at https://github.com/lanagarmire/ASGARD .

单细胞 RNA 测序技术使我们能够深入分析各种疾病中的细胞间异质性。然而，它在精准医疗方面的全部潜力尚未得到充分发挥。为此，我们提出了一种单细胞指导药物再利用的管道（ASGARD），该方法通过考虑所有细胞簇来定义药物评分，以解决每个患者内部的细胞间异质性。与两种基于批量细胞的药物再利用方法相比，ASGARD 在单药治疗方面的平均准确性显著提高。我们还证明，它的性能明显优于其他细胞簇水平的预测方法。此外，我们使用三阴性乳腺癌患者样本的药物反应预测方法 TRANSACT 对 ASGARD 进行了验证。我们发现，排名靠前的许多药物要么已经获得美国食品和药物管理局的批准，要么正在临床试验中用于治疗相应的疾病。总之，ASGARD 是一种有前途的基于单细胞 RNA-seq 的个性化医疗药物再利用推荐工具。ASGARD 可在 https://github.com/lanagarmire/ASGARD 上免费用于教育用途。