Nature Communications · 2017 · 1.1K citations · 49 references
Life SciencesMolecular BiologyOncologyGene ExpressionMolecular OncologyPathway AnalysisCancer Cell SignalingCancer GenomicsCancer TranscriptomicsMutational SignaturesOncogenic Signaling PathwaysSignal Transduction In CancerCellular Pathway PerturbationDifferential Pathway ActivityOncogenic Driver MutationsPathway Activity ProfilingPathway Activity Signature DerivationPathway MappingPerturbation ResponseTumor Suppressor Pathways
Aberrant cell signaling can cause cancer and other diseases and is a focal point of drug research. A common approach is to infer signaling activity of pathways from gene expression. However, mapping gene expression to pathway components disregards the effect of post-translational modifications, and downstream signatures represent very specific experimental conditions. Here we present PROGENy, a method that overcomes both limitations by leveraging a large compendium of publicly available perturbation experiments to yield a common core of Pathway RespOnsive GENes. Unlike pathway mapping methods, PROGENy can (i) recover the effect of known driver mutations, (ii) provide or improve strong markers for drug indications, and (iii) distinguish between oncogenic and tumor suppressor pathways for patient survival. Collectively, these results show that PROGENy accurately infers pathway activity from gene expression in a wide range of conditions.
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STAR: ultrafast universal RNA-seq aligner
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