{"id":538,"date":"2022-04-27T19:02:37","date_gmt":"2022-04-27T19:02:37","guid":{"rendered":"https:\/\/terrabioappdev.wpenginepowered.com\/paper-spotlight-discovering-the-anticancer-potential-of-non-oncology-drugs\/"},"modified":"2023-12-27T04:55:23","modified_gmt":"2023-12-27T04:55:23","slug":"paper-spotlight-discovering-the-anticancer-potential-of-non-oncology-drugs","status":"publish","type":"post","link":"https:\/\/terra.bio\/paper-spotlight-discovering-the-anticancer-potential-of-non-oncology-drugs\/","title":{"rendered":"Paper Spotlight: Discovering the anticancer potential of non-oncology drugs by systematic viability profiling"},"content":{"rendered":"

This blog is part of our Paper Spotlight series, which features peer-reviewed research publications involving work done in Terra and highlights how the analysis methods were applied.\u00a0<\/span><\/i><\/p>\n

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Discovering the anticancer potential of non-oncology drugs by systematic viability profiling<\/b><\/p>\n

By Steven M. Corsello, Rohith T. Nagari, Todd R. Golub et al., 2020<\/span><\/i><\/p>\n

Nature Cancer, <\/span>1, pages 235\u2013248 (2020)<\/span> https:\/\/doi.org\/10.1038\/s43018-019-0018-6<\/span><\/a>\u00a0<\/span><\/p>\n

Abstract:<\/b> Anticancer uses of non-oncology drugs have occasionally been found, but such discoveries have been serendipitous. We sought to create a public resource containing the growth-inhibitory activity of 4,518 drugs tested across 578 human cancer cell lines. We used PRISM (profiling relative inhibition simultaneously in mixtures), a molecular barcoding method, to screen drugs against cell lines in pools. An unexpectedly large number of non-oncology drugs selectively inhibited subsets of cancer cell lines in a manner predictable from the molecular features of the cell lines. Our findings include compounds that killed by inducing phosphodiesterase 3A-Schlafen 12 complex formation, vanadium-containing compounds whose killing depended on the sulfate transporter SLC26A2, the alcohol dependence drug disulfiram, which killed cells with low expression of metallothioneins, and the anti-inflammatory drug tepoxalin, which killed via the multidrug resistance protein ATP-binding cassette subfamily B member 1 (ABCB1). The PRISM drug repurposing resource (<\/span>https:\/\/depmap.org\/repurposing<\/span><\/a>) is a starting point to develop new oncology therapeutics, and more rarely, for potential direct clinical translation.<\/span><\/p>\n

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What part of the work was done in Terra?<\/span><\/h3>\n

Excerpts from the paper’s Methods section:<\/span><\/p>\n

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\u00a0<\/span>Transcriptional profiling by RNA-seq\u00a0<\/b><\/p>\n

[…] Nucleic acid was sequenced using an Illumina NextSeq 500 PE75 instrument. Gene-level expression values were obtained from RNA-seq using the TOPMed RNA-seq pipeline (version 1). RSEM (version 1.3.0) was used to generate transcripts per million gene-level expression quantifications. These tools were run using the FireCloud and Terra platforms. Differential gene expression was calculated using the DESeq2 package (version 1.22.2).<\/span><\/p>\n

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Note: <\/i><\/b>FireCloud is a project powered by the Terra platform and supported by the National Cancer Institute. It is one of the three <\/span><\/i>Cloud Resources<\/span><\/i><\/a> that provide access to cloud compute capabilities as part of the NCI’s <\/span><\/i>Cancer Research Data Commons<\/span><\/i><\/a> program. The <\/span><\/i>FireCloud portal<\/span><\/i><\/a> provides full access to Terra’s data and analysis capabilities.<\/span><\/i><\/p>\n

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How did they do it?<\/span><\/h3>\n

The authors used analysis workflows<\/span> originally developed by the Genotype-Tissue Expression (GTEx) consortium as part of a <\/span>seminal project<\/span><\/a> to characterize variation in gene expression levels across individuals and diverse tissues of the human body. These workflows were since reimplemented in the <\/span>Workflow Description Language (WDL)<\/span><\/a> and shared in the <\/span>Broad Methods Repository<\/span><\/a>.\u00a0<\/span><\/p>\n

Terra also supports <\/span><\/i>importing workflows<\/span><\/i><\/a> from <\/span><\/i>Dockstore<\/span><\/i><\/a>, a free and open source platform for sharing reusable and scalable analytical tools and workflows.\u00a0<\/span><\/i><\/p>\n

The authors ran the workflows at scale using<\/span> Terra’s workflow execution service<\/span><\/a>.\u00a0<\/span><\/p>\n

To try your hand at running a workflow in Terra, check out this <\/span>Quickstart Tutorial Workspace<\/span><\/a>.\u00a0<\/span><\/p>\n

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Appendix: Data and code availability<\/span><\/h3>\n