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

Intercellular heterogeneity is a major obstacle to successful precision medicine. Single-cell RNA sequencing (scRNA-seq) 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...

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Autores principales: He, Bing, Xiao, Yao, Liang, Haodong, Huang, Qianhui, Du, Yuheng, Li, Yijun, Garmire, David, Sun, Duxin, Garmire, Lana X.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cornell University 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8452105/
https://www.ncbi.nlm.nih.gov/pubmed/34545335
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author He, Bing
Xiao, Yao
Liang, Haodong
Huang, Qianhui
Du, Yuheng
Li, Yijun
Garmire, David
Sun, Duxin
Garmire, Lana X.
author_facet He, Bing
Xiao, Yao
Liang, Haodong
Huang, Qianhui
Du, Yuheng
Li, Yijun
Garmire, David
Sun, Duxin
Garmire, Lana X.
author_sort He, Bing
collection PubMed
description Intercellular heterogeneity is a major obstacle to successful precision medicine. Single-cell RNA sequencing (scRNA-seq) 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 new drug recommendation system called: A Single-cell Guided Pipeline to Aid Repurposing of Drugs (ASGARD). ASGARD defines a novel drug score predicting drugs by considering all cell clusters to address the intercellular heterogeneity within each patient. We tested ASGARD on multiple diseases, including breast cancer, acute lymphoblastic leukemia, and coronavirus disease 2019 (COVID-19). On single-drug therapy, ASGARD shows significantly better average accuracy (AUC of 0.92) compared to two other bulk-cell-based drug repurposing methods (AUC of 0.80 and 0.76). It is also considerably better (AUC of 0.82) than other cell cluster level predicting methods (AUC of 0.67 and 0.55). In addition, ASGARD is also validated by the drug response prediction method TRANSACT with Triple-Negative-Breast-Cancer patient samples. Many top-ranked drugs are either approved by FDA or in clinical trials treating corresponding diseases. In silico cell-type specific drop-out experiments using triple-negative breast cancers show the importance of T cells in the tumor microenvironment in affecting drug predictions. 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.
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spelling pubmed-84521052021-09-21 ASGARD: A Single-cell Guided Pipeline to Aid Repurposing of Drugs He, Bing Xiao, Yao Liang, Haodong Huang, Qianhui Du, Yuheng Li, Yijun Garmire, David Sun, Duxin Garmire, Lana X. ArXiv Article Intercellular heterogeneity is a major obstacle to successful precision medicine. Single-cell RNA sequencing (scRNA-seq) 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 new drug recommendation system called: A Single-cell Guided Pipeline to Aid Repurposing of Drugs (ASGARD). ASGARD defines a novel drug score predicting drugs by considering all cell clusters to address the intercellular heterogeneity within each patient. We tested ASGARD on multiple diseases, including breast cancer, acute lymphoblastic leukemia, and coronavirus disease 2019 (COVID-19). On single-drug therapy, ASGARD shows significantly better average accuracy (AUC of 0.92) compared to two other bulk-cell-based drug repurposing methods (AUC of 0.80 and 0.76). It is also considerably better (AUC of 0.82) than other cell cluster level predicting methods (AUC of 0.67 and 0.55). In addition, ASGARD is also validated by the drug response prediction method TRANSACT with Triple-Negative-Breast-Cancer patient samples. Many top-ranked drugs are either approved by FDA or in clinical trials treating corresponding diseases. In silico cell-type specific drop-out experiments using triple-negative breast cancers show the importance of T cells in the tumor microenvironment in affecting drug predictions. 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. Cornell University 2021-09-14 /pmc/articles/PMC8452105/ /pubmed/34545335 Text en https://creativecommons.org/licenses/by-nc-sa/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (https://creativecommons.org/licenses/by-nc-sa/4.0/) , which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format for noncommercial purposes only, and only so long as attribution is given to the creator. If you remix, adapt, or build upon the material, you must license the modified material under identical terms.
spellingShingle Article
He, Bing
Xiao, Yao
Liang, Haodong
Huang, Qianhui
Du, Yuheng
Li, Yijun
Garmire, David
Sun, Duxin
Garmire, Lana X.
ASGARD: A Single-cell Guided Pipeline to Aid Repurposing of Drugs
title ASGARD: A Single-cell Guided Pipeline to Aid Repurposing of Drugs
title_full ASGARD: A Single-cell Guided Pipeline to Aid Repurposing of Drugs
title_fullStr ASGARD: A Single-cell Guided Pipeline to Aid Repurposing of Drugs
title_full_unstemmed ASGARD: A Single-cell Guided Pipeline to Aid Repurposing of Drugs
title_short ASGARD: A Single-cell Guided Pipeline to Aid Repurposing of Drugs
title_sort asgard: a single-cell guided pipeline to aid repurposing of drugs
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8452105/
https://www.ncbi.nlm.nih.gov/pubmed/34545335
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