Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

CANCER GENOMICS & COMPUTATIONAL BIOLOGY

Finding cancer drivers in the UPS system

Nature Cancer volume 1, pages 20–21 (2020)Cite this article

Subjects

Identifying cancer driver mutations is essential to understand disease biology and devise effective therapies, but remains a complex endeavor. A focused analytical approach is now presented that defines driver mutations affecting ubiquitin-mediated proteolysis through machine learning and mining of cancer multi-omics data.

In the post-genomic era, patients’ tumor DNA is routinely sequenced to guide the selection of treatment options. An urgent gap between cancer genomics and precision cancer medicine is the identification of driver somatic mutations1. Driver mutations are typically defined as somatic variants that have critical functional effects that confer selective advantages to cells during clonal evolution and are likely to have roles in cancer progression or treatment responses2. In contrast, most somatic mutations observed in tumors are ‘passenger’ mutations, which have no biological effects and are therefore neutral during cancer evolution. Although many computational algorithms have been developed to distinguish driver from passenger mutations3, the predictive power of these algorithms is generally limited4, not only because the number of driver mutations is very low but more importantly because the diverse biological effects of driver mutations make them difficult to capture in a general algorithm. Therefore, an approach focusing on a specific biological process with well-defined characteristics may be more effective. In an elegant example of such a focused approach, in this issue of Nature Cancer, Martínez-Jiménez et al. present a systematic pan-cancer analysis of cancer somatic mutations in the ubiquitin-mediated proteolysis system (UPS)5.

This is a preview of subscription content, access via your institution

Access options

Rent or buy this article

Get just this article for as long as you need it

$39.95

Learn more

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: The effects of mutations in E3 ligases and degrons on the target proteins in cancer cells.

References

  1. Cheng, F., Liang, H., Butte, A. J., Eng, C. & Nussinov, R. Pharmacol. Rev. 71, 1–19 (2019).

    Article  CAS  Google Scholar 

  2. Martincorena, I. & Campbell, P. J. Science 349, 1483–1489 (2015).

    Article  CAS  Google Scholar 

  3. Bailey, M. H. et al. Cell 173, 371–385.e18 (2018).

    Article  CAS  Google Scholar 

  4. Ng, P. K. et al. Cancer Cell 33, 450–462.e10 (2018).

    Article  CAS  Google Scholar 

  5. Martínez-Jiménez, F., Muiños, F., López-Arribillaga, E., Lopez-Bigas, N. & Gonzalez-Perez, A. Nat. Cancer https://doi.org/10.1038/s43018-019-0001-2 (2019).

  6. Laney, J. D. & Hochstrasser, M. Cell 97, 427–430 (1999).

    Article  CAS  Google Scholar 

  7. Meszaros, B., Kumar, M., Gibson, T. J., Uyar, B. & Dosztanyi, Z. Sci. Signal. 10, eaak9982 (2017).

    Article  Google Scholar 

  8. Li, J. et al. Nat. Methods 10, 1046–1047 (2013).

    Article  CAS  Google Scholar 

  9. Ge, Z. et al. Cell Rep. 23, 213–226.e3 (2018).

    Article  CAS  Google Scholar 

  10. Dinkel, H. et al. Nucleic Acids Res. 44, D294–D300 (2016).

    Article  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Bioinformatics and Computational Biology and Department of Systems Biology, University of Texas MD Anderson Cancer Center, Houston, TX, USA

    Han Liang

Authors
  1. Han Liang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Han Liang.

Ethics declarations

Competing interests

The author declares no competing interests.

Rights and permissions

Reprints and Permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Liang, H. Finding cancer drivers in the UPS system. Nat Cancer 1, 20–21 (2020). https://doi.org/10.1038/s43018-019-0013-y

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s43018-019-0013-y

Search

Advanced search

Quick links

Nature Briefing: Cancer

Sign up for the Nature Briefing: Cancer newsletter — what matters in cancer research, free to your inbox weekly.

Get what matters in cancer research, free to your inbox weekly. Sign up for Nature Briefing: Cancer