Identification of novel prostate cancer drivers using RegNetDriver: a framework for integration of genetic and epigenetic alterations with tissue-specific regulatory network
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Author
Dhingra, Priyanka
Martinez-Fundichely, Alexander
Berger, Adeline
Forbes, Andre Neil
Liu, Eric Minwei
Liu, Deli
Sboner, Andrea
Tamayo, Pablo
Rickman, David S.
Rubin, Mark A.
Khurana, Ekta
Note: Order does not necessarily reflect citation order of authors.
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https://doi.org/10.1186/s13059-017-1266-3Metadata
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Dhingra, P., A. Martinez-Fundichely, A. Berger, F. W. Huang, A. N. Forbes, E. M. Liu, D. Liu, et al. 2017. “Identification of novel prostate cancer drivers using RegNetDriver: a framework for integration of genetic and epigenetic alterations with tissue-specific regulatory network.” Genome Biology 18 (1): 141. doi:10.1186/s13059-017-1266-3. http://dx.doi.org/10.1186/s13059-017-1266-3.Abstract
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.Other Sources
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5530464/pdf/Terms of Use
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