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Updated: Feb 25, 2026
Discovery of Driver Genes in Colorectal HT29-derived Cancer Stem-Like Tumorspheres
Published on: July 22, 2020
Identification of novel prostate cancer drivers using RegNetDriver: a framework for integration of genetic and
Priyanka Dhingra1,2, Alexander Martinez-Fundichely1,2, Adeline Berger3
1Department of Physiology and Biophysics, Weill Cornell Medical College, New York, New York, 10065, USA.
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.
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