Oct 29, 2018

Signatures of cell death and proliferation in perturbation transcriptomics data - from confounding factor to effective prediction

BioRxiv : the Preprint Server for Biology
Bence SzalaiJulio Saez-Rodriguez

Abstract

Transcriptomics perturbation signatures are valuable data sources for functional genomic studies. They can be effectively used to identify mechanism of action for new compounds and to infer functional activity of different cellular processes. Linking perturbation signatures to phenotypic studies opens up the possibility to model selected cellular phenotypes from gene expression data and to predict drugs interfering with the phenotype. At the same time, close association of transcriptomics changes with phenotypes can potentially mask the compound specific signatures. By linking perturbation transcriptomics data from the LINCS-L1000 project with cell viability phenotypic information upon genetic (from Achilles project) and chemical (from CTRP screen) perturbations for more than 90,000 signature - cell viability pairs, we show here that a cell death signature is a major factor behind perturbation signatures. We use this relationship to effectively predict cell viability from transcriptomics signatures, and identify compounds that induce either cell death or proliferation. We also show that cellular toxicity can lead to an unexpected similarity of toxic compound signatures confounding the mechanism of action discovery. Consensus co...Continue Reading

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Mentioned in this Paper

Study
Antineoplastic Agents
Cellular Process
Genome
Projections and Predictions
Gene Expression
Cell Proliferation
Genomics
Pharmacologic Substance
Not Measured Tumor Identification

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