Introduction

The evolution of cancer genomes within a single tumor creates mixed cell populations with divergent somatic mutational landscapes. Inference of tumor subpopulations has been disproportionately focused on the assessment of somatic point mutations, whereas computational methods targeting evolutionary dynamics of copy number alterations (CNA) and loss of heterozygosity (LOH) in whole-genome sequencing data remain underdeveloped. We present a novel probabilistic model, TITAN, to infer CNA and LOH events while accounting for mixtures of cell populations, thereby estimating the proportion of cells harboring each event. We evaluate TITAN on idealized mixtures, simulating clonal populations from whole-genome sequences taken from genomically heterogeneous ovarian tumor sites collected from the same patient. In addition, we show in 23 whole genomes of breast tumors that the inference of CNA and LOH using TITAN critically informs population structure and the nature of the evolving cancer genome. Finally, we experimentally validated subclonal predictions using fluorescence in situ hybridization (FISH) and single-cell sequencing from an ovarian cancer patient sample, thereby recapitulating the key modeling assumptions of TITAN.

Publications

  1. TITAN: inference of copy number architectures in clonal cell populations from tumor whole-genome sequence data.
    Cite this
    Ha G, Roth A, Khattra J, Ho J, Yap D, Prentice LM, Melnyk N, McPherson A, Bashashati A, Laks E, Biele J, Ding J, Le A, Rosner J, Shumansky K, Marra MA, Gilks CB, Huntsman DG, McAlpine JN, Aparicio S, Shah SP, 2014-11-01 - Genome research

Credits

  1. Gavin Ha
    Developer

    Department of Molecular Oncology, British Columbia Cancer Agency, Canada

  2. Andrew Roth
    Developer

    Department of Molecular Oncology, British Columbia Cancer Agency, Canada

  3. Jaswinder Khattra
    Developer

    Department of Molecular Oncology, British Columbia Cancer Agency, Canada

  4. Julie Ho
    Developer

    Centre for Translational and Applied Genomics, Vancouver

  5. Damian Yap
    Developer

    Department of Molecular Oncology, British Columbia Cancer Agency, Canada

  6. Leah M Prentice
    Developer

    Centre for Translational and Applied Genomics, Vancouver

  7. Nataliya Melnyk
    Developer

    Centre for Translational and Applied Genomics, Vancouver

  8. Andrew McPherson
    Developer

    Department of Molecular Oncology, British Columbia Cancer Agency, Canada

  9. Ali Bashashati
    Developer

    Department of Molecular Oncology, British Columbia Cancer Agency, Canada

  10. Emma Laks
    Developer

    Department of Molecular Oncology, British Columbia Cancer Agency, Canada

  11. Justina Biele
    Developer

    Department of Molecular Oncology, British Columbia Cancer Agency, Canada

  12. Jiarui Ding
    Developer

    Department of Molecular Oncology, British Columbia Cancer Agency, Canada

  13. Alan Le
    Developer

    Department of Molecular Oncology, British Columbia Cancer Agency, Canada

  14. Jamie Rosner
    Developer

    Department of Molecular Oncology, British Columbia Cancer Agency, Canada

  15. Karey Shumansky
    Developer

    Department of Molecular Oncology, British Columbia Cancer Agency, Canada

  16. Marco A Marra
    Developer

    Genome Sciences Centre, British Columbia Cancer Agency

  17. C Blake Gilks
    Developer

    Genetic Pathology Evaluation Centre, Vancouver General Hospital

  18. David G Huntsman
    Developer

    Centre for Translational and Applied Genomics, Vancouver

  19. Jessica N McAlpine
    Developer

    Department of Gynecology and Obstetrics, University of British Columbia, Canada

  20. Samuel Aparicio
    Developer

    Department of Molecular Oncology, British Columbia Cancer Agency, Canada

  21. Sohrab P Shah
    Investigator

    Department of Molecular Oncology, British Columbia Cancer Agency, Canada

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Summary
AccessionBT001594
Tool TypeApplication
Category
PlatformsLinux/Unix
TechnologiesR
User InterfaceTerminal Command Line
Download Count0
Submitted BySohrab P Shah