A survey of optimal strategy for signature-based drug repositioning and an application to liver cancer
- Shanghai Jiao Tong University, China
- Huazhong University of Science and Technology, China
Abstract
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 (CCL4)-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.
Data availability
Sequencing data have been deposited in GEO under accession codes GSE180243 and GSE193897.All data generated or analysed during this study are included in the manuscript and supporting files.
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A survey of optimal strategy for signature-based drug repositioning and an application to liver cancerNCBI Gene Expression Omnibus, GSE180243.
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Gene expression profiles of 35 paired HCC and non-tumor tissues by RNA-seq dataNCBI Gene Expression Omnibus, GSE124535.
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Next-generation characterization of the Cancer Cell Line Encyclopedia.Broad Institute Cancer Cell Line Encyclopedia (CCLE).
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The Genotype-Tissue Expression (GTEx) projectGenotype-Tissue Expression (GTEx).
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Gene expression data of human hepatocellular carcinoma (HCC)NCBI Gene Expression Omnibus,GSE14520.
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Integrative omics analysis in HCC samples [mRNA expression]NCBI Gene Expression Omnibus, GSE84005.
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Genome-wide molecular profiles of HCV-induced dysplasia and hepatocellular carcinomaNCBI Gene Expression Omnibus,GSE6764.
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Gene-expression profiles of hepatitis C-related, early-stage liver cirrhosisNCBI Gene Expression Omnibus, GSE15654.
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Characterization of gene expression profile in HBV-related liver fibrosis patientsNCBI Gene Expression Omnibus, GSE84044.
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Gene expression profile of liver tissue from carbon tetrachloride (CCl4)-treated mouse cultured ex vivoNCBI Gene Expression Omnibus, GSE71379.
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Gene expression profiles of fractionated cells from cirrhotic rat liversNCBI Gene Expression Omnibus,GSE63726.
Article and author information
Author details
Funding
National Natural Science Foundation of China (81972208)
- Hui Wang
National Natural Science Foundation of China (82170646)
- Hualian Hang
Shanghai Natural Science Foundation (19ZR1452700)
- Hui Wang
The Interdisciplinary Program of Shanghai Jiao Tong University (YG2021ZD10)
- Hualian Hang
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Animal experimentation: All animals were manipulated according to protocols approved by the Shanghai Medical Experimental Animal Care Commission and Shanghai Cancer Institute, Renji Hospital, Shanghai Jiao Tong University School of Medicine.
Copyright
© 2022, Yang et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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A survey of optimal strategy for signature-based drug repositioning and an application to liver cancer
eLife 11:e71880.
https://doi.org/10.7554/eLife.71880
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