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Barcoding reveals complex clonal behavior in patient-derived xenografts of metastatic triple negative breast cancer

Author

Listed:
  • D. Merino

    (The Walter and Eliza Hall Institute of Medical Research
    The University of Melbourne
    Olivia Newton-John Cancer Research Institute
    School of Cancer Medicine, La Trobe University)

  • T. S. Weber

    (The University of Melbourne
    The Walter and Eliza Hall Institute of Medical Research)

  • A. Serrano

    (The Walter and Eliza Hall Institute of Medical Research
    The University of Melbourne
    Olivia Newton-John Cancer Research Institute)

  • F. Vaillant

    (The Walter and Eliza Hall Institute of Medical Research
    The University of Melbourne)

  • K. Liu

    (The Walter and Eliza Hall Institute of Medical Research
    The University of Melbourne)

  • B. Pal

    (The Walter and Eliza Hall Institute of Medical Research
    The University of Melbourne)

  • L. Stefano

    (The Walter and Eliza Hall Institute of Medical Research)

  • J. Schreuder

    (The University of Melbourne
    The Walter and Eliza Hall Institute of Medical Research
    The Walter and Eliza Hall Institute of Medical Research)

  • D. Lin

    (The University of Melbourne
    The Walter and Eliza Hall Institute of Medical Research
    The Walter and Eliza Hall Institute of Medical Research)

  • Y. Chen

    (The University of Melbourne
    The Walter and Eliza Hall Institute of Medical Research)

  • M. L. Asselin-Labat

    (The Walter and Eliza Hall Institute of Medical Research
    The University of Melbourne)

  • T. N. Schumacher

    (Netherlands Cancer Institute)

  • D. Cameron

    (The Walter and Eliza Hall Institute of Medical Research)

  • G. K. Smyth

    (The Walter and Eliza Hall Institute of Medical Research
    The University of Melbourne)

  • A. T. Papenfuss

    (The University of Melbourne
    The Walter and Eliza Hall Institute of Medical Research
    The University of Melbourne
    Peter MacCallum Cancer Centre)

  • G. J. Lindeman

    (The Walter and Eliza Hall Institute of Medical Research
    The Peter MacCallum Cancer Centre
    The University of Melbourne
    The Royal Melbourne Hospital and Peter MacCallum Cancer Centre)

  • J. E. Visvader

    (The Walter and Eliza Hall Institute of Medical Research
    The University of Melbourne)

  • S. H. Naik

    (The University of Melbourne
    The Walter and Eliza Hall Institute of Medical Research
    The Walter and Eliza Hall Institute of Medical Research)

Abstract

Primary triple negative breast cancers (TNBC) are prone to dissemination but sub-clonal relationships between tumors and resulting metastases are poorly understood. Here we use cellular barcoding of two treatment-naïve TNBC patient-derived xenografts (PDXs) to track the spatio-temporal fate of thousands of barcoded clones in primary tumors, and their metastases. Tumor resection had a major impact on reducing clonal diversity in secondary sites, indicating that most disseminated tumor cells lacked the capacity to ‘seed’, hence originated from ‘shedders’ that did not persist. The few clones that continued to grow after resection i.e. ‘seeders’, did not correlate in frequency with their parental clones in primary tumors. Cisplatin treatment of one BRCA1-mutated PDX model to non-palpable levels had a surprisingly minor impact on clonal diversity in the relapsed tumor yet purged 50% of distal clones. Therefore, clonal features of shedding, seeding and drug resistance are important factors to consider for the design of therapeutic strategies.

Suggested Citation

  • D. Merino & T. S. Weber & A. Serrano & F. Vaillant & K. Liu & B. Pal & L. Stefano & J. Schreuder & D. Lin & Y. Chen & M. L. Asselin-Labat & T. N. Schumacher & D. Cameron & G. K. Smyth & A. T. Papenfus, 2019. "Barcoding reveals complex clonal behavior in patient-derived xenografts of metastatic triple negative breast cancer," Nature Communications, Nature, vol. 10(1), pages 1-12, December.
    • Handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-08595-2
    DOI: 10.1038/s41467-019-08595-2
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    Cited by:

    1. Humberto Contreras-Trujillo & Jiya Eerdeng & Samir Akre & Du Jiang & Jorge Contreras & Basia Gala & Mary C. Vergel-Rodriguez & Yeachan Lee & Aparna Jorapur & Areen Andreasian & Lisa Harton & Charles S, 2021. "Deciphering intratumoral heterogeneity using integrated clonal tracking and single-cell transcriptome analyses," Nature Communications, Nature, vol. 12(1), pages 1-14, December.
    2. Louise A. Baldwin & Nenad Bartonicek & Jessica Yang & Sunny Z. Wu & Niantao Deng & Daniel L. Roden & Chia-Ling Chan & Ghamdan Al-Eryani & Damien J. Zanker & Belinda S. Parker & Alexander Swarbrick & S, 2022. "DNA barcoding reveals ongoing immunoediting of clonal cancer populations during metastatic progression and immunotherapy response," Nature Communications, Nature, vol. 13(1), pages 1-18, December.
    3. Bing He & Yao Xiao & Haodong Liang & Qianhui Huang & Yuheng Du & Yijun Li & David Garmire & Duxin Sun & Lana X. Garmire, 2023. "ASGARD is A Single-cell Guided Pipeline to Aid Repurposing of Drugs," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    4. F. Nadalin & M. J. Marzi & M. Pirra Piscazzi & P. Fuentes-Bravo & S. Procaccia & M. Climent & P. Bonetti & C. Rubolino & B. Giuliani & I. Papatheodorou & J. C. Marioni & F. Nicassio, 2024. "Multi-omic lineage tracing predicts the transcriptional, epigenetic and genetic determinants of cancer evolution," Nature Communications, Nature, vol. 15(1), pages 1-23, December.
    5. Peter Eirew & Ciara O’Flanagan & Jerome Ting & Sohrab Salehi & Jazmine Brimhall & Beixi Wang & Justina Biele & Teresa Algara & So Ra Lee & Corey Hoang & Damian Yap & Steven McKinney & Cherie Bates & E, 2022. "Accurate determination of CRISPR-mediated gene fitness in transplantable tumours," Nature Communications, Nature, vol. 13(1), pages 1-19, December.
    6. Qiuchen Guo & Milos Spasic & Adam G. Maynard & Gregory J. Goreczny & Amanuel Bizuayehu & Jessica F. Olive & Peter Galen & Sandra S. McAllister, 2022. "Clonal barcoding with qPCR detection enables live cell functional analyses for cancer research," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
    7. Zhu, Guang & Lin, Zhenhua, 2021. "Commentary on statistical mechanical models of cancer," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 572(C).

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