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

Marketa TomkovaJakub TomekJulie C ChowJohn D McPhersonDavid J SegalFereydoun Hormozdiari
Published in: Nucleic acids research (2023)
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.
Keyphrases
  • lymph node metastasis
  • papillary thyroid
  • squamous cell carcinoma
  • transcription factor
  • gene expression
  • genome wide identification
  • squamous cell
  • risk assessment
  • binding protein
  • human health
  • artificial intelligence