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Inferring Copy Number from Triple-Negative Breast Cancer Patient Derived Xenograft scRNAseq Data Using scCNA

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Mapping Genetic Interactions

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2381))

Abstract

Cancer can develop from an accumulation of alterations, some of which cause a nonmalignant cell to transform to a malignant state exhibiting increased rate of cell growth and evasion of growth suppressive mechanisms, eventually leading to tissue invasion and metastatic disease. Triple-negative breast cancers (TNBC) are heterogeneous and are clinically characterized by the lack of expression of hormone receptors and human epidermal growth factor receptor 2 (HER2), which limits its treatment options. Since tumor evolution is driven by diverse cancer cell populations and their microenvironment, it is imperative to map TNBC at single-cell resolution. Here, we describe an experimental procedure for isolating a single-cell suspension from a TNBC patient-derived xenograft, subjecting it to single-cell RNA sequencing using droplet-based technology from 10× Genomics and analyzing the transcriptomic data at single-cell resolution to obtain inferred copy number aberration profiles, using scCNA. Data obtained using this single-cell RNA sequencing experimental and analytical methodology should enhance our understanding of intratumor heterogeneity which is key for identifying genetic vulnerabilities and developing effective therapies.

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Acknowledgments

The scRNAseq protocol was developed for and tested at the “Wellcome Trust Advanced Course in RNA transcriptomics.”

Author information

Author notes

  1. Jean Monlong

    Present address: UC Santa Cruz Genomics Institute, University of California, Santa Cruz, CA, USA

Authors and Affiliations

  1. Goodman Cancer Research Centre, McGill University, Montreal, QC, Canada

    Elena Kuzmin, Constanza Martinez, Hellen Kuasne & Morag Park

  2. Department of Biochemistry, McGill University, Montreal, QC, Canada

    Elena Kuzmin, Hellen Kuasne & Morag Park

  3. McGill Genome Centre, McGill University, Montreal, QC, Canada

    Jean Monlong, Jiannis Ragoussis & Guillaume Bourque

  4. Department of Human Genetics, McGill University, Montreal, QC, Canada

    Jean Monlong, Claudia L. Kleinman, Jiannis Ragoussis & Guillaume Bourque

  5. Department of Pathology, McGill University, Montreal, QC, Canada

    Constanza Martinez

  6. Lady Davis Institute for Medical Research, Montreal, QC, Canada

    Claudia L. Kleinman

  7. Department of Oncology, McGill University, Montreal, QC, Canada

    Morag Park

Authors
  1. Elena Kuzmin
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  2. Jean Monlong
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  3. Constanza Martinez
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  4. Hellen Kuasne
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  5. Claudia L. Kleinman
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  6. Jiannis Ragoussis
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  7. Guillaume Bourque
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  8. Morag Park
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Corresponding authors

Correspondence to Jean Monlong , Guillaume Bourque or Morag Park .

Editor information

Editors and Affiliations

  1. University of Saskatchewan, Saskatoon, SK, Canada

    Franco Joseph Vizeacoumar

  2. University of Saskatchewan, Saskatoon, SK, Canada

    Andrew Freywald

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© 2021 The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature

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Kuzmin, E. et al. (2021). Inferring Copy Number from Triple-Negative Breast Cancer Patient Derived Xenograft scRNAseq Data Using scCNA. In: Vizeacoumar, F.J., Freywald, A. (eds) Mapping Genetic Interactions. Methods in Molecular Biology, vol 2381. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-1740-3_16

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  • DOI: https://doi.org/10.1007/978-1-0716-1740-3_16

  • Published:

  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-1739-7

  • Online ISBN: 978-1-0716-1740-3

  • eBook Packages: Springer Protocols

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