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A Large-Scale Gene Expression Intensity-Based Similarity Metric for Drug Repositioning

60 Pages Posted: 6 Jun 2018 Sneak Peek Status: Published

See all articles by Chen-Tsung Huang

Chen-Tsung Huang

National Taiwan University - Graduate Institute of Biomedical Electronics and Bioinformatics

Chiao-Hui Hsieh

National Taiwan University - Institute of Molecular and Cellular Biology

Yen-Jen Oyang

National Taiwan University - Graduate Institute of Biomedical Electronics and Bioinformatics

Hsuan-Cheng Huang

National Yang-Ming University - Institute of Biomedical Informatics

Hsueh-Fen Juan

National Taiwan University - Graduate Institute of Biomedical Electronics and Bioinformatics; National Taiwan University - Institute of Molecular and Cellular Biology; National Taiwan University - Department of Life Science; National Yang-Ming University - Institute of Biomedical Informatics

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Abstract

Biological systems often respond to a specific environmental or genetic perturbation without pervasive gene ex pression changes. Such robustness to perturbations, however, is not re flected on the current computational strategies that utilize gene expression si milarity metrics for drug discovery and repositioning. Here we propos e a new expression intensity-based similarity metric that consistently achieved better performance than other state-of-the-art similarity metrics with respect to the gold-standard clustering of drugs with known mechanisms of action. The new metric directly emphasizes the genes ex hibiting the greatest changes in expression in response to a perturbation. Using the new framework to systematically compare 3,332 chemic al and 3,934 genetic perturbations across 10 cell types representing diverse cellular signatures, we identified thousands of recurrent and cell type- specific connections. We also experimentally validated two drugs (an anthelmintic and a loop diuretic) identified by the analysis as potential topoisomerase inhibitors. The new framework is a valuable resource for hypothesis generation, functional testing, and drug repositioning.

Suggested Citation

Huang, Chen-Tsung and Hsieh, Chiao-Hui and Oyang, Yen-Jen and Huang, Hsuan-Cheng and Juan, Hsueh-Fen, A Large-Scale Gene Expression Intensity-Based Similarity Metric for Drug Repositioning (2018). Available at SSRN: https://ssrn.com/abstract=3188408 or http://dx.doi.org/10.2139/ssrn.3188408
This is a paper under consideration at Cell Press and has not been peer-reviewed.

Chen-Tsung Huang

National Taiwan University - Graduate Institute of Biomedical Electronics and Bioinformatics

Taipei 106
Taiwan

Chiao-Hui Hsieh

National Taiwan University - Institute of Molecular and Cellular Biology

Taipei
Taiwan

Yen-Jen Oyang

National Taiwan University - Graduate Institute of Biomedical Electronics and Bioinformatics

Taipei 106
Taiwan

Hsuan-Cheng Huang (Contact Author)

National Yang-Ming University - Institute of Biomedical Informatics ( email )

Taiwan

Hsueh-Fen Juan

National Taiwan University - Graduate Institute of Biomedical Electronics and Bioinformatics ( email )

Taipei 106
Taiwan

National Taiwan University - Institute of Molecular and Cellular Biology ( email )

Taipei
Taiwan

National Taiwan University - Department of Life Science ( email )

Taipei
Taiwan

National Yang-Ming University - Institute of Biomedical Informatics ( email )

Taiwan

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