Introduction

Local concentrations of mutations are well known in human cancers. However, their three-dimensional spatial relationships in the encoded protein have yet to be systematically explored. We developed a computational tool, HotSpot3D, to identify such spatial hotspots (clusters) and to interpret the potential function of variants within them. We applied HotSpot3D to >4,400 TCGA tumors across 19 cancer types, discovering >6,000 intra- and intermolecular clusters, some of which showed tumor and/or tissue specificity. In addition, we identified 369 rare mutations in genes including TP53, PTEN, VHL, EGFR, and FBXW7 and 99 medium-recurrence mutations in genes such as RUNX1, MTOR, CA3, PI3, and PTPN11, all mapping within clusters having potential functional implications. As a proof of concept, we validated our predictions in EGFR using high-throughput phosphorylation data and cell-line-based experimental evaluation. Finally, mutation-drug cluster and network analysis predicted over 800 promising candidates for druggable mutations, raising new possibilities for designing personalized treatments for patients carrying specific mutations.

Publications

  1. Protein-structure-guided discovery of functional mutations across 19 cancer types.
    Cite this
    Niu B, Scott AD, Sengupta S, Bailey MH, Batra P, Ning J, Wyczalkowski MA, Liang WW, Zhang Q, McLellan MD, Sun SQ, Tripathi P, Lou C, Ye K, Mashl RJ, Wallis J, Wendl MC, Chen F, Ding L, 2016-08-01 - Nature genetics

Credits

  1. Beifang Niu
    Developer

    McDonnell Genome Institute, Washington University, United States of America

  2. Adam D Scott
    Developer

    Division of Oncology, Department of Medicine, United States of America

  3. Sohini Sengupta
    Developer

    Division of Oncology, Department of Medicine, United States of America

  4. Matthew H Bailey
    Developer

    Division of Oncology, Department of Medicine, United States of America

  5. Prag Batra
    Developer

    McDonnell Genome Institute, Washington University, United States of America

  6. Jie Ning
    Developer

    Division of Nephrology, Department of Medicine, United States of America

  7. Matthew A Wyczalkowski
    Developer

    Division of Oncology, Department of Medicine, United States of America

  8. Wen-Wei Liang
    Developer

    Division of Oncology, Department of Medicine, United States of America

  9. Qunyuan Zhang
    Developer

    Department of Genetics, Washington University, United States of America

  10. Michael D McLellan
    Developer

    McDonnell Genome Institute, Washington University, United States of America

  11. Sam Q Sun
    Developer

    Division of Oncology, Department of Medicine, United States of America

  12. Piyush Tripathi
    Developer

    Division of Nephrology, Department of Medicine, United States of America

  13. Carolyn Lou
    Developer

    Division of Oncology, Department of Medicine, United States of America

  14. Kai Ye
    Developer

    Department of Genetics, Washington University, United States of America

  15. R Jay Mashl
    Developer

    Division of Oncology, Department of Medicine, United States of America

  16. John Wallis
    Developer

    McDonnell Genome Institute, Washington University, United States of America

  17. Michael C Wendl
    Developer

    Department of Mathematics, Washington University, United States of America

  18. Feng Chen
    Developer

    Department of Cell Biology and Physiology, Washington University, United States of America

  19. Li Ding
    Investigator

    Siteman Cancer Center, Washington University, United States of America

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Summary
AccessionBT006716
Tool TypeApplication
Category
PlatformsLinux/Unix
TechnologiesPerl
User InterfaceTerminal Command Line
Download Count0
Country/RegionUnited States of America
Submitted ByLi Ding