The Drug Repurposing Hub: a next-generation drug library and information resource

Corsello, Steven M.; Bittker, Joshua A.; Liu, Zihan; Gould, Joshua; McCarren, Patrick; Hirschman, Jodi E.; Johnston, Stephen; Vrcic, Anita; Wong, Bang; Khan, Mariya; Asiedu, Jacob K.; Narayan, Rajiv; Mader, Christopher C.; Subramanian, Aravind; Golub, Todd R.

doi:10.1038/nm.4306

Cited by 777 publications

(704 citation statements)

References 13 publications

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“…Nevertheless, we used multiple resources to associate 1,902 compounds to protein targets and associated pathway members profiled in the CMap. This led to 58,820 expected relationships that could plausibly be recovered in the CMap (see STAR Methods) (Corsello et al, 2017). We then sought to recover those relationships from among the approximately 160 million pairwise relationships (connections) that could be assessed across CMap.…”

Section: Resultsmentioning

confidence: 99%

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A Next Generation Connectivity Map: L1000 Platform and the First 1,000,000 Profiles

Subramanian

Narayan

Corsello

et al. 2017

Cell

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2,418

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Summary We previously piloted the concept of a Connectivity Map (CMap), whereby genes, drugs and disease states are connected by virtue of common gene-expression signatures. Here, we report more than a 1,000-fold scale-up of the CMap as part of the NIH LINCS Consortium, made possible by a new, low-cost, high throughput reduced representation expression profiling method that we term L1000. We show that L1000 is highly reproducible, comparable to RNA sequencing, and suitable for computational inference of the expression levels of 81% of non-measured transcripts. We further show that the expanded CMap can be used to discover mechanism of action of small molecules, functionally annotate genetic variants of disease genes, and inform clinical trials. The 1.3 million L1000 profiles described here, as well as tools for their analysis, are available at https://clue.io.

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Section: Resultsmentioning

confidence: 99%

“…For compounds, mechanism of action and gene target annotations were collated from multiple sources (Corsello et al, 2017). For genes, family and pathway annotations were obtained from HGNC as of July 2016.…”

Section: Quantification and Statistical Analysismentioning

confidence: 99%

A Next Generation Connectivity Map: L1000 Platform and the First 1,000,000 Profiles

Subramanian

Narayan

Corsello

et al. 2017

Cell

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2,418

2,332

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“…Computational and predictive modeling approaches to predict drug response or anticipate adverse drug reactions require both primary and secondary target information for a complete picture [15–19]. Drug repurposing, or finding alternate uses for existing drugs often makes use of secondary or so-called “off-target” binding, where a drug binds to a target other than the one it was designed for [20,21]. Lastly, designing combinatorial drug treatment for a patient based on multiple genetic variants requires knowledge of drugs interacting with targets affected by each of those genetic variants [22].…”

Section: Precision Oncology Requires Rigorous Drug Target Informationmentioning

confidence: 99%

Evidence-Based Precision Oncology with the Cancer Targetome

Blucher

Choonoo

Kulesz‐Martin

et al. 2017

Trends in Pharmacological Sciences

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A core tenet of precision oncology is the rational choice of drugs to interact with patient-specific biological targets of interest, but it is currently difficult for researchers to obtain consistent and well-supported target information for pharmaceutical drugs. We review current drug target interaction resources and critically assess how supporting evidence is handled. We introduce the concept of a unified Cancer Targetome to aggregate drug target interactions within an evidence-based framework. We discuss current unmet needs and the implications for evidence based-clinical omics. The focus of this review is precision oncology but the discussion is highly relevant to targeted therapies of any area.

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“…Pioneering efforts to produce small-molecule probes with novel mechanisms of action, such as those mobilized by the launch of the Molecular Libraries Program by the NIH in 2005, have expanded the repertoire of biologically active small molecules available for screening (Austin et al, 2004). In addition, new libraries have been assembled that include thousands of existing, approved drugs, with the potential to be repurposed for a new therapeutic indication (Huang et al, 2011; Corsello et al, 2017). Focused screening libraries may also include small-molecule probes that collectively cover a wide range of targets and cellular processes (Basu et al, 2013; Seashore-Ludlow et al, 2015; Yang et al, 2013).…”

Section: New Functional Screening Tools To Map Rare Cancer Dependenciesmentioning

confidence: 99%

Emerging Opportunities for Target Discovery in Rare Cancers

Sharifnia

Hong

Painter

et al. 2017

Cell Chemical Biology

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Rare cancers pose unique challenges to research due to their low incidence. Barriers include a scarcity of tissue and experimental models to enable basic research and insufficient patient accrual for clinical studies. Consequently, an understanding of the genetic and cellular features of many rare cancer types and their associated vulnerabilities has been lacking. However, new opportunities are emerging to facilitate discovery of therapeutic targets in rare cancers. Online platforms are allowing patients with rare cancers to organize on an unprecedented scale, tumor genome sequencing is now routinely performed in research and clinical settings, and the efficiency of patient-derived model generation has improved. New CRISPR/Cas9 and small-molecule libraries permit cancer dependency discovery in a rapid and systematic fashion. In parallel, large-scale studies of common cancers now provide reference datasets to help interpret rare cancer profiling data. Together, these advances motivate consideration of new research frameworks to accelerate rare cancer target discovery.

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The Drug Repurposing Hub: a next-generation drug library and information resource

Cited by 777 publications

References 13 publications

A Next Generation Connectivity Map: L1000 Platform and the First 1,000,000 Profiles

A Next Generation Connectivity Map: L1000 Platform and the First 1,000,000 Profiles

Evidence-Based Precision Oncology with the Cancer Targetome

Emerging Opportunities for Target Discovery in Rare Cancers

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