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An integrated network platform for contextual prioritization of drugs and pathways.

ABSTRACT: Repurposing of drugs to novel disease indications has promise for faster clinical translation. However, identifying the best drugs for a given pathological context is not trivial. We developed an integrated random walk-based network framework that combines functional biomolecular relationships and known drug-target interactions as a platform for contextual prioritization of drugs, genes and pathways. We show that the use of gene-centric or drug-centric data, such as gene expression data or a phenotypic drug screen, respectively, within this network platform can effectively prioritize drugs and pathways, respectively, to the studied biological context. We demonstrate that various genomic data can be used as contextual cues to effectively prioritize drugs to the studied context, while similarly, phenotypic drug screen data can be used to effectively prioritize genes and pathways to the studied phenotypic context. As a proof-of-principle, we showcase the use of our platform to identify known and novel drug indications against different subsets of breast cancers through contextual prioritization based on genome-wide gene expression, shRNA and drug screen and clinical survival data. The integrated network and associated methods are incorporated into the NetWalker suite for functional genomics analysis ().

SUBMITTER: Segura-Cabrera A

PROVIDER: S-EPMC4814269 | biostudies-literature | 2015 Nov

REPOSITORIES: biostudies-literature

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An integrated network platform for contextual prioritization of drugs and pathways.

Segura-Cabrera Aldo A Singh Navneet N Komurov Kakajan K

Molecular bioSystems 20151101 11

Repurposing of drugs to novel disease indications has promise for faster clinical translation. However, identifying the best drugs for a given pathological context is not trivial. We developed an integrated random walk-based network framework that combines functional biomolecular relationships and known drug-target interactions as a platform for contextual prioritization of drugs, genes and pathways. We show that the use of gene-centric or drug-centric data, such as gene expression data or a phe ...[more]

PMID: 26315485

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Project description:Systems characterization of immune landscapes in health, disease and clinical intervention cases is a priority in modern medicine. High-throughput transcriptomes accumulated from gene-knockout (KO) experiments are crucial for deciphering target KO signaling pathways that are impaired by KO genes at the systems-level. There is a demand for integrative platforms. This article describes the PathwayKO platform, which has integrated state-of-the-art methods of pathway enrichment analysis, statistics analysis, and visualizing analysis to conduct cutting-edge integrative pathway analysis in a pipeline fashion and decipher target KO signaling pathways at the systems-level. We focus on describing the methodology, principles and application features of PathwayKO. First, we demonstrate that the PathwayKO platform can be utilized to comprehensively analyze real-world mouse KO transcriptomes (GSE22873 and GSE24327), which reveal systemic mechanisms underlying the innate immune responses triggered by non-infectious extensive hepatectomy (2 hours after 85% liver resection surgery) and infectious CASP-model sepsis (12 hours after CASP-model surgery). Strikingly, our results indicate that both cases hit the same core set of 21 KO MyD88-associated signaling pathways, including the Toll-like receptor signaling pathway, the NFκB signaling pathway, the MAPK signaling pathway, and the PD-L1 expression and PD-1 checkpoint pathway in cancer, alongside the pathways of bacterial, viral and parasitic infections. These findings suggest common fundamental mechanisms between these immune responses and offer informative cues that warrant future experimental validation. Such mechanisms in mice may serve as models for humans and ultimately guide formulating the research paradigms and composite strategies to reduce the high mortality rates of patients in intensive care units who have undergone successful traumatic surgical treatments. Second, we demonstrate that the PathwayKO platform model-based assessments can effectively evaluate the performance difference of pathway analysis methods when benchmarked with a collection of proper transcriptomes. Together, such advances in methods for deciphering biological insights at the systems-level may benefit the fields of bioinformatics, systems immunology and beyond.

Dataset Information

An integrated network platform for contextual prioritization of drugs and pathways.

Publications

An integrated network platform for contextual prioritization of drugs and pathways.

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