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Mutation hotspots at CTCF binding sites coupled to chromosomal instability in gastrointestinal cancers

Author

Listed:
  • Yu Amanda Guo

    (Genome Institute of Singapore)

  • Mei Mei Chang

    (Genome Institute of Singapore)

  • Weitai Huang

    (Genome Institute of Singapore
    National University of Singapore)

  • Wen Fong Ooi

    (Genome Institute of Singapore)

  • Manjie Xing

    (Genome Institute of Singapore
    Duke-NUS Medical School)

  • Patrick Tan

    (Duke-NUS Medical School
    National University of Singapore)

  • Anders Jacobsen Skanderup

    (Genome Institute of Singapore)

Abstract

Tissue-specific driver mutations in non-coding genomic regions remain undefined for most cancer types. Here, we unbiasedly analyze 212 gastric cancer (GC) whole genomes to identify recurrently mutated non-coding regions in GC. Applying comprehensive statistical approaches to accurately model background mutational processes, we observe significant enrichment of non-coding indels (insertions/deletions) in three gastric lineage-specific genes. We further identify 34 mutation hotspots, of which 11 overlap CTCF binding sites (CBSs). These CBS hotspots remain significant even after controlling for a genome-wide elevated mutation rate at CBSs. In 3 out of 4 tested CBS hotspots, mutations are nominally associated with expression change of neighboring genes. CBS hotspot mutations are enriched in tumors showing chromosomal instability, co-occur with neighboring chromosomal aberrations, and are common in gastric (25%) and colorectal (19%) tumors but rare in other cancer types. Mutational disruption of specific CBSs may thus represent a tissue-specific mechanism of tumorigenesis conserved across gastrointestinal cancers.

Suggested Citation

  • Yu Amanda Guo & Mei Mei Chang & Weitai Huang & Wen Fong Ooi & Manjie Xing & Patrick Tan & Anders Jacobsen Skanderup, 2018. "Mutation hotspots at CTCF binding sites coupled to chromosomal instability in gastrointestinal cancers," Nature Communications, Nature, vol. 9(1), pages 1-14, December.
    • Handle: RePEc:nat:natcom:v:9:y:2018:i:1:d:10.1038_s41467-018-03828-2
    DOI: 10.1038/s41467-018-03828-2
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    Cited by:

    1. Kiran Krishnamachari & Dylan Lu & Alexander Swift-Scott & Anuar Yeraliyev & Kayla Lee & Weitai Huang & Sim Ngak Leng & Anders Jacobsen Skanderup, 2022. "Accurate somatic variant detection using weakly supervised deep learning," Nature Communications, Nature, vol. 13(1), pages 1-8, December.
    2. Kseniia Cheloshkina & Maria Poptsova, 2021. "Comprehensive analysis of cancer breakpoints reveals signatures of genetic and epigenetic contribution to cancer genome rearrangements," PLOS Computational Biology, Public Library of Science, vol. 17(3), pages 1-23, March.

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