Dr.Nod: computational framework for discovery of regulatory non-coding drivers in tissue-matched distal regulatory elements

• Published in: Nucleic acids research 2023-02, Vol.51 (4), p.e23-e23
• Main Authors: Tomkova, Marketa, Tomek, Jakub, Chow, Julie, McPherson, John D, Segal, David J, Hormozdiari, Fereydoun
• Format: Article
• Language: English
• Subjects: Humans; Methods Online; Mutation; Neoplasms - genetics; Oncogenes; Regulatory Sequences, Nucleic Acid
• ISSN: 0305-1048; 1362-4962
• DOI: 10.1093/nar/gkac1251

The discovery of cancer driver mutations is a fundamental goal in cancer research. While many cancer driver mutations have been discovered in the protein-coding genome, research into potential cancer drivers in the non-coding regions showed limited success so far. Here, we present a novel comprehensive framework Dr.Nod for detection of non-coding cis-regulatory candidate driver mutations that are associated with dysregulated gene expression using tissue-matched enhancer-gene annotations. Applying the framework to data from over 1500 tumours across eight tissues revealed a 4.4-fold enrichment of candidate driver mutations in regulatory regions of known cancer driver genes. An overarching conclusion that emerges is that the non-coding driver mutations contribute to cancer by significantly altering transcription factor binding sites, leading to upregulation of tissue-matched oncogenes and down-regulation of tumour-suppressor genes. Interestingly, more than half of the detected cancer-promoting non-coding regulatory driver mutations are over 20 kb distant from the cancer-associated genes they regulate. Our results show the importance of tissue-matched enhancer-gene maps, functional impact of mutations, and complex background mutagenesis model for the prediction of non-coding regulatory drivers. In conclusion, our study demonstrates that non-coding mutations in enhancers play a previously underappreciated role in cancer and dysregulation of clinically relevant target genes.