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Reconstructing metastatic seeding patterns of human cancers

Author

Listed:
  • Johannes G. Reiter

    (Program for Evolutionary Dynamics, Harvard University
    IST (Institute of Science and Technology) Austria)

  • Alvin P. Makohon-Moore

    (The David M. Rubenstein Center for Pancreatic Cancer Research, Memorial Sloan Kettering Cancer Center
    Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center)

  • Jeffrey M. Gerold

    (Program for Evolutionary Dynamics, Harvard University)

  • Ivana Bozic

    (Program for Evolutionary Dynamics, Harvard University
    Harvard University)

  • Krishnendu Chatterjee

    (IST (Institute of Science and Technology) Austria)

  • Christine A. Iacobuzio-Donahue

    (The David M. Rubenstein Center for Pancreatic Cancer Research, Memorial Sloan Kettering Cancer Center
    Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center
    Memorial Sloan Kettering Cancer Center)

  • Bert Vogelstein

    (The Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins University School of Medicine
    The Ludwig Center and Howard Hughes Medical Institute at The Johns Hopkins University School of Medicine)

  • Martin A. Nowak

    (Program for Evolutionary Dynamics, Harvard University
    Harvard University
    Harvard University)

Abstract

Reconstructing the evolutionary history of metastases is critical for understanding their basic biological principles and has profound clinical implications. Genome-wide sequencing data has enabled modern phylogenomic methods to accurately dissect subclones and their phylogenies from noisy and impure bulk tumour samples at unprecedented depth. However, existing methods are not designed to infer metastatic seeding patterns. Here we develop a tool, called Treeomics, to reconstruct the phylogeny of metastases and map subclones to their anatomic locations. Treeomics infers comprehensive seeding patterns for pancreatic, ovarian, and prostate cancers. Moreover, Treeomics correctly disambiguates true seeding patterns from sequencing artifacts; 7% of variants were misclassified by conventional statistical methods. These artifacts can skew phylogenies by creating illusory tumour heterogeneity among distinct samples. In silico benchmarking on simulated tumour phylogenies across a wide range of sample purities (15–95%) and sequencing depths (25-800 × ) demonstrates the accuracy of Treeomics compared with existing methods.

Suggested Citation

  • Johannes G. Reiter & Alvin P. Makohon-Moore & Jeffrey M. Gerold & Ivana Bozic & Krishnendu Chatterjee & Christine A. Iacobuzio-Donahue & Bert Vogelstein & Martin A. Nowak, 2017. "Reconstructing metastatic seeding patterns of human cancers," Nature Communications, Nature, vol. 8(1), pages 1-10, April.
    • Handle: RePEc:nat:natcom:v:8:y:2017:i:1:d:10.1038_ncomms14114
    DOI: 10.1038/ncomms14114
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    Cited by:

    1. Zicheng Wang & Yunong Xia & Lauren Mills & Athanasios N. Nikolakopoulos & Nicole Maeser & Scott M. Dehm & Jason M. Sheltzer & Ruping Sun, 2024. "Evolving copy number gains promote tumor expansion and bolster mutational diversification," Nature Communications, Nature, vol. 15(1), pages 1-16, December.
    2. Haochen Zhang & Elias-Ramzey Karnoub & Shigeaki Umeda & Ronan Chaligné & Ignas Masilionis & Caitlin A. McIntyre & Palash Sashittal & Akimasa Hayashi & Amanda Zucker & Katelyn Mullen & Jungeui Hong & A, 2023. "Application of high-throughput single-nucleus DNA sequencing in pancreatic cancer," Nature Communications, Nature, vol. 14(1), pages 1-14, December.

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