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A survey of optimal strategy for signature-based drug repositioning and an application to liver cancer

Pharmacologic perturbation projects, such as Connectivity Map (CMap) and Library of Integrated Network-based Cellular Signatures (LINCS), have produced many perturbed expression data, providing enormous opportunities for computational therapeutic discovery. However, there is no consensus on which me...

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Autores principales: Yang, Chen, Zhang, Hailin, Chen, Mengnuo, Wang, Siying, Qian, Ruolan, Zhang, Linmeng, Huang, Xiaowen, Wang, Jun, Liu, Zhicheng, Qin, Wenxin, Wang, Cun, Hang, Hualian, Wang, Hui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: eLife Sciences Publications, Ltd 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8893721/
https://www.ncbi.nlm.nih.gov/pubmed/35191375
http://dx.doi.org/10.7554/eLife.71880
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author Yang, Chen
Zhang, Hailin
Chen, Mengnuo
Wang, Siying
Qian, Ruolan
Zhang, Linmeng
Huang, Xiaowen
Wang, Jun
Liu, Zhicheng
Qin, Wenxin
Wang, Cun
Hang, Hualian
Wang, Hui
author_facet Yang, Chen
Zhang, Hailin
Chen, Mengnuo
Wang, Siying
Qian, Ruolan
Zhang, Linmeng
Huang, Xiaowen
Wang, Jun
Liu, Zhicheng
Qin, Wenxin
Wang, Cun
Hang, Hualian
Wang, Hui
author_sort Yang, Chen
collection PubMed
description Pharmacologic perturbation projects, such as Connectivity Map (CMap) and Library of Integrated Network-based Cellular Signatures (LINCS), have produced many perturbed expression data, providing enormous opportunities for computational therapeutic discovery. However, there is no consensus on which methodologies and parameters are the most optimal to conduct such analysis. Aiming to fill this gap, new benchmarking standards were developed to quantitatively evaluate drug retrieval performance. Investigations of potential factors influencing drug retrieval were conducted based on these standards. As a result, we determined an optimal approach for LINCS data-based therapeutic discovery. With this approach, homoharringtonine (HHT) was identified to be a candidate agent with potential therapeutic and preventive effects on liver cancer. The antitumor and antifibrotic activity of HHT was validated experimentally using subcutaneous xenograft tumor model and carbon tetrachloride (CCL(4))-induced liver fibrosis model, demonstrating the reliability of the prediction results. In summary, our findings will not only impact the future applications of LINCS data but also offer new opportunities for therapeutic intervention of liver cancer.
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spelling pubmed-88937212022-03-04 A survey of optimal strategy for signature-based drug repositioning and an application to liver cancer Yang, Chen Zhang, Hailin Chen, Mengnuo Wang, Siying Qian, Ruolan Zhang, Linmeng Huang, Xiaowen Wang, Jun Liu, Zhicheng Qin, Wenxin Wang, Cun Hang, Hualian Wang, Hui eLife Cancer Biology Pharmacologic perturbation projects, such as Connectivity Map (CMap) and Library of Integrated Network-based Cellular Signatures (LINCS), have produced many perturbed expression data, providing enormous opportunities for computational therapeutic discovery. However, there is no consensus on which methodologies and parameters are the most optimal to conduct such analysis. Aiming to fill this gap, new benchmarking standards were developed to quantitatively evaluate drug retrieval performance. Investigations of potential factors influencing drug retrieval were conducted based on these standards. As a result, we determined an optimal approach for LINCS data-based therapeutic discovery. With this approach, homoharringtonine (HHT) was identified to be a candidate agent with potential therapeutic and preventive effects on liver cancer. The antitumor and antifibrotic activity of HHT was validated experimentally using subcutaneous xenograft tumor model and carbon tetrachloride (CCL(4))-induced liver fibrosis model, demonstrating the reliability of the prediction results. In summary, our findings will not only impact the future applications of LINCS data but also offer new opportunities for therapeutic intervention of liver cancer. eLife Sciences Publications, Ltd 2022-02-22 /pmc/articles/PMC8893721/ /pubmed/35191375 http://dx.doi.org/10.7554/eLife.71880 Text en © 2022, Yang et al https://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited.
spellingShingle Cancer Biology
Yang, Chen
Zhang, Hailin
Chen, Mengnuo
Wang, Siying
Qian, Ruolan
Zhang, Linmeng
Huang, Xiaowen
Wang, Jun
Liu, Zhicheng
Qin, Wenxin
Wang, Cun
Hang, Hualian
Wang, Hui
A survey of optimal strategy for signature-based drug repositioning and an application to liver cancer
title A survey of optimal strategy for signature-based drug repositioning and an application to liver cancer
title_full A survey of optimal strategy for signature-based drug repositioning and an application to liver cancer
title_fullStr A survey of optimal strategy for signature-based drug repositioning and an application to liver cancer
title_full_unstemmed A survey of optimal strategy for signature-based drug repositioning and an application to liver cancer
title_short A survey of optimal strategy for signature-based drug repositioning and an application to liver cancer
title_sort survey of optimal strategy for signature-based drug repositioning and an application to liver cancer
topic Cancer Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8893721/
https://www.ncbi.nlm.nih.gov/pubmed/35191375
http://dx.doi.org/10.7554/eLife.71880
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