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Realizing the promise of cancer predisposition genes

Author

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  • Nazneen Rahman

    (Institute of Cancer Research
    Cancer Genetics Unit, Royal Marsden Hospital Foundation Trust)

Abstract

Genes in which germline mutations confer highly or moderately increased risks of cancer are called cancer predisposition genes. More than 100 of these genes have been identified, providing important scientific insights in many areas, particularly the mechanisms of cancer causation. Moreover, clinical utilization of cancer predisposition genes has had a substantial impact on diagnosis, optimized management and prevention of cancer. The recent transformative advances in DNA sequencing hold the promise of many more cancer predisposition gene discoveries, and greater and broader clinical applications. However, there is also considerable potential for incorrect inferences and inappropriate clinical applications. Realizing the promise of cancer predisposition genes for science and medicine will thus require careful navigation.

Suggested Citation

  • Nazneen Rahman, 2014. "Realizing the promise of cancer predisposition genes," Nature, Nature, vol. 505(7483), pages 302-308, January.
    • Handle: RePEc:nat:nature:v:505:y:2014:i:7483:d:10.1038_nature12981
    DOI: 10.1038/nature12981
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    Cited by:

    1. Ulrik Kristoffer Stoltze & Jon Foss-Skiftesvik & Thomas van Overeem Hansen & Simon Rasmussen & Konrad J. Karczewski & Karin A. W. Wadt & Kjeld Schmiegelow, 2024. "The evolutionary impact of childhood cancer on the human gene pool," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
    2. Mischan Vali-Pour & Solip Park & Jose Espinosa-Carrasco & Daniel Ortiz-Martínez & Ben Lehner & Fran Supek, 2022. "The impact of rare germline variants on human somatic mutation processes," Nature Communications, Nature, vol. 13(1), pages 1-21, December.
    3. Yuichi Shiraishi & Ai Okada & Kenichi Chiba & Asuka Kawachi & Ikuko Omori & Raúl Nicolás Mateos & Naoko Iida & Hirofumi Yamauchi & Kenjiro Kosaki & Akihide Yoshimi, 2022. "Systematic identification of intron retention associated variants from massive publicly available transcriptome sequencing data," Nature Communications, Nature, vol. 13(1), pages 1-13, December.

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