Application of the Transcriptional Disease Signature (TDSs) to Screen Melanoma-Effective Compounds in a Small Fish Model

Date

2019-01

Authors

Lu, Yuan
Boswell, William T.
Boswell, Mikki
Klotz, Barbara
Kneitz, Susanne
Regneri, Janine
Savage, Markita G.
Mendoza, Cristina
Postlethwait, John
Warren, Wesley C.

Journal Title

Journal ISSN

Volume Title

Publisher

Nature Publishing Group

Abstract

Cell culture and protein target-based compound screening strategies, though broadly utilized in selecting candidate compounds, often fail to eliminate candidate compounds with non-target effects and/or safety concerns until late in the drug developmental process. Phenotype screening using intact research animals is attractive because it can help identify small molecule candidate compounds that have a high probability of proceeding to clinical use. Most FDA approved, first-in-class small molecules were identified from phenotypic screening. However, phenotypic screening using rodent models is labor intensive, low-throughput, and very expensive. As a novel alternative for small molecule screening, we have been developing gene expression disease profiles, termed the Transcriptional Disease Signature (TDS), as readout of small molecule screens for therapeutic molecules. In this concept, compounds that can reverse, or otherwise affect known disease-associated gene expression patterns in whole animals may be rapidly identified for more detailed downstream direct testing of their efficacy and mode of action. To establish proof of concept for this screening strategy, we employed a transgenic strain of a small aquarium fish, medaka (Oryzias latipes), that overexpresses the malignant melanoma driver gene xmrk, a mutant egfr gene, that is driven by a pigment cell-specific mitf promoter. In this model, melanoma develops with 100% penetrance. Using the transgenic medaka malignant melanoma model, we established a screening system that employs the NanoString nCounter platform to quantify gene expression within custom sets of TDS gene targets that we had previously shown to exhibit differential transcription among xmrk-transgenic and wild-type medaka. Compound-modulated gene expression was identified using an internet-accessible custom-built data processing pipeline. The effect of a given drug on the entire TDS profile was estimated by comparing compound-modulated genes in the TDS using an activation Z-score and Kolmogorov-Smirnov statistics. TDS gene probes were designed that target common signaling pathways that include proliferation, development, toxicity, immune function, metabolism and detoxification. These pathways may be utilized to evaluate candidate compounds for potential favorable, or unfavorable, effects on melanoma-associated gene expression. Here we present the logistics of using medaka to screen compounds, as well as, the development of a user-friendly NanoString data analysis pipeline to support feasibility of this novel TDS drug-screening strategy.

Description

Keywords

transcriptional disease signatures, melanoma-effective compounds, small fish model, Chemistry and Biochemistry

Citation

Lu, Y., Boswell, W., Boswell, M., Klotz, B., Kneitz, S. Regneri, J., Savage, M., Mendoza, C., Postlethwait, J., Warren, W. C., Schartl, M., Walter, R. B. (2019). Application of the Transcriptional Disease Signature (TDSs) to Screen Melanoma-Effective Compounds in a Small Fish Model. Scientific Reports, 9(530).

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© 2019 The Author(s).

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This work is licensed under a Creative Commons Attribution 4.0 International License.

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