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Application of high-throughput single-nucleus DNA sequencing in pancreatic cancer

Author

Listed:
  • Haochen Zhang

    (Memorial Sloan Kettering Cancer Center
    Memorial Sloan Kettering Cancer Center)

  • Elias-Ramzey Karnoub

    (Memorial Sloan Kettering Cancer Center
    Memorial Sloan Kettering Cancer Center)

  • Shigeaki Umeda

    (Memorial Sloan Kettering Cancer Center
    Memorial Sloan Kettering Cancer Center)

  • Ronan Chaligné

    (Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center)

  • Ignas Masilionis

    (Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center)

  • Caitlin A. McIntyre

    (Memorial Sloan Kettering)

  • Palash Sashittal

    (Princeton University)

  • Akimasa Hayashi

    (Memorial Sloan Kettering Cancer Center
    Memorial Sloan Kettering Cancer Center
    Kyorin University School of Medicine)

  • Amanda Zucker

    (Memorial Sloan Kettering Cancer Center
    Memorial Sloan Kettering Cancer Center
    Oregon Health and Science University)

  • Katelyn Mullen

    (Memorial Sloan Kettering Cancer Center
    Memorial Sloan Kettering Cancer Center)

  • Jungeui Hong

    (Memorial Sloan Kettering Cancer Center
    Memorial Sloan Kettering Cancer Center)

  • Alvin Makohon-Moore

    (Memorial Sloan Kettering Cancer Center
    Memorial Sloan Kettering Cancer Center
    Hackensack Meridian Health)

  • Christine A. Iacobuzio-Donahue

    (Memorial Sloan Kettering Cancer Center
    Memorial Sloan Kettering Cancer Center
    Memorial Sloan Kettering Cancer Center)

Abstract

Despite insights gained by bulk DNA sequencing of cancer it remains challenging to resolve the admixture of normal and tumor cells, and/or of distinct tumor subclones; high-throughput single-cell DNA sequencing circumvents these and brings cancer genomic studies to higher resolution. However, its application has been limited to liquid tumors or a small batch of solid tumors, mainly because of the lack of a scalable workflow to process solid tumor samples. Here we optimize a highly automated nuclei extraction workflow that achieves fast and reliable targeted single-nucleus DNA library preparation of 38 samples from 16 pancreatic ductal adenocarcinoma patients, with an average library yield per sample of 2867 single nuclei. We demonstrate that this workflow not only performs well using low cellularity or low tumor purity samples but reveals genomic evolution patterns of pancreatic ductal adenocarcinoma as well.

Suggested Citation

  • 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.
    • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-36344-z
    DOI: 10.1038/s41467-023-36344-z
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    References listed on IDEAS

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