2017
DOI: 10.1186/s13059-017-1266-3
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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

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 transcrip… Show more

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Cited by 31 publications
(25 citation statements)
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References 123 publications
(210 reference statements)
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“…In this context, while acknowledging that teratomas are a special tumor type, our data suggest that cancer cells might even be able to bypass RAS nullyzygosity through the inactivation of suppressors such as ERF. Interestingly, recurrent deletions and inactivating mutations of ERF have been found recently in prostate cancer (Bose et al 2017;Dhingra et al 2017;Huang et al 2017). However, the impact of these mutations is still not fully characterized.…”
Section: Discussionmentioning
confidence: 99%
“…In this context, while acknowledging that teratomas are a special tumor type, our data suggest that cancer cells might even be able to bypass RAS nullyzygosity through the inactivation of suppressors such as ERF. Interestingly, recurrent deletions and inactivating mutations of ERF have been found recently in prostate cancer (Bose et al 2017;Dhingra et al 2017;Huang et al 2017). However, the impact of these mutations is still not fully characterized.…”
Section: Discussionmentioning
confidence: 99%
“…Fifth, the algorithm SEPIRA, which was used to construct the tissue-specific regulatory network and estimation of TF binding activity, is of a general nature and could be applied to any tissue type present in the GTEX database. The ability to infer regulatory activity from a DNAm profile further opens up its application to EWAS and cancer epigenome studies, offering a complementary approach to other recent methods [ 76 ].…”
Section: Discussionmentioning
confidence: 99%
“…Current tools designed to identify non-coding drivers are based on mutation recurrence within regulatory elements (Juul, et al, 2017; Lochovsky, et al, 2015), predicted functional impact of somatic mutations (Mularoni, et al, 2016), or a combination of these approaches (Dhingra, et al, 2017; Hornshoj, et al, 2018). However, existing methods are designed to explore mutations within defined regulatory regions, such as promoters, enhancers or UTRs, therefore ignoring the rest of the non-coding genome.…”
Section: Introductionmentioning
confidence: 99%