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Identification of novel prostate cancer drivers using RegNetDriver: a framework for integration of genetic and epigenetic alterations with tissue-specific regulatory network

We report a novel computational method, RegNetDriver, to identify tumorigenic drivers using the combined effects of coding and non-coding single nucleotide variants, structural variants, and DNA methylation changes in the DNase I hypersensitivity based regulatory network. Integration of multi-omics...

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Detalles Bibliográficos
Autores principales: Dhingra, Priyanka, Martinez-Fundichely, Alexander, Berger, Adeline, Huang, Franklin W., Forbes, Andre Neil, Liu, Eric Minwei, Liu, Deli, Sboner, Andrea, Tamayo, Pablo, Rickman, David S., Rubin, Mark A., Khurana, Ekta
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5530464/
https://www.ncbi.nlm.nih.gov/pubmed/28750683
http://dx.doi.org/10.1186/s13059-017-1266-3
Descripción
Sumario:We report a novel computational method, RegNetDriver, to identify tumorigenic drivers using the combined effects of coding and non-coding single nucleotide variants, structural variants, and DNA methylation changes in the DNase I hypersensitivity based regulatory network. Integration of multi-omics data from 521 prostate tumor samples indicated a stronger regulatory impact of structural variants, as they affect more transcription factor hubs in the tissue-specific network. Moreover, crosstalk between transcription factor hub expression modulated by structural variants and methylation levels likely leads to the differential expression of target genes. We report known prostate tumor regulatory drivers and nominate novel transcription factors (ERF, CREB3L1, and POU2F2), which are supported by functional validation. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13059-017-1266-3) contains supplementary material, which is available to authorized users.