Multi-omics “upstream analysis” of regulatory genomic regions helps identifying targets against methotrexate resistance of colon cancer

We present an “upstream analysis” strategy for causal analysis of multiple “-omics” data. It analyzes promoters using the TRANSFAC database, combines it with an analysis of the upstream signal transduction pathways and identifies master regulators as potential drug targets for a pathological process...

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Detalles Bibliográficos
Autores principales: Kel, Alexander E., Stegmaier, Philip, Valeev, Tagir, Koschmann, Jeannette, Poroikov, Vladimir, Kel-Margoulis, Olga V., Wingender, Edgar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2016
Materias:
Special Section: Contributions from PATHPROT, the Annual International Forum for Pathway Analysis in Proteomics (Oeiras, Portugal)
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5988513/
https://www.ncbi.nlm.nih.gov/pubmed/29900117
http://dx.doi.org/10.1016/j.euprot.2016.09.002
Descripción
Sumario:We present an “upstream analysis” strategy for causal analysis of multiple “-omics” data. It analyzes promoters using the TRANSFAC database, combines it with an analysis of the upstream signal transduction pathways and identifies master regulators as potential drug targets for a pathological process. We applied this approach to a complex multi-omics data set that contains transcriptomics, proteomics and epigenomics data. We identified the following potential drug targets against induced resistance of cancer cells towards chemotherapy by methotrexate (MTX): TGFalpha, IGFBP7, alpha9-integrin, and the following chemical compounds: zardaverine and divalproex as well as human metabolites such as nicotinamide N-oxide.

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