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Real-Time Cell Cycle Imaging in a 3D Cell Culture Model of Melanoma, Quantitative Analysis, Optical Clearing, and Mathematical Modeling

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3D Cell Culture

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2764))

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Abstract

Aberrant cell cycle progression is a hallmark of solid tumors. Therefore, cell cycle analysis is an invaluable technique to study cancer cell biology. However, cell cycle progression has been most commonly assessed by methods that are limited to temporal snapshots or that lack spatial information. In this chapter, we describe a technique that allows spatiotemporal real-time tracking of cell cycle progression of individual cells in a multicellular context. The power of this system lies in the use of 3D melanoma spheroids generated from melanoma cells engineered with the fluorescent ubiquitination-based cell cycle indicator (FUCCI). This technique, combined with mathematical modeling, allows us to gain further and more detailed insight into several relevant aspects of solid cancer cell biology, such as tumor growth, proliferation, invasion, and drug sensitivity.

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Acknowledgments

We thank Prof Meenhard Herlyn, The Wistar Institute, Philadelphia, PA; Prof Keiran Smalley, Moffitt Cancer Center, Tampa, FL; Prof Wolfgang Weninger & Dr. Ben Roediger, Centenary Institute, Sydney, NSW; Dr. Crystal Tonnessen, Frazer Institute, Brisbane, QLD; and the imaging facilities of the Centenary Institute (Sydney) and the Translational Research Institute (Brisbane) for their contribution to optimizing this protocol over the years. We thank Prof Matthew Simpson, Mathematical Sciences, Queensland University of Technology, Brisbane, QLD, for the fantastic collaboration linking 3D culture model analysis with mathematical modeling. We thank Prof Atsushi Miyawaki, RIKEN, Wako-city, Japan, for providing the FUCCI constructs. N.K.H. is a Cameron fellow of the Melanoma and Skin Cancer Research Institute, Australia. K.A.B. is a fellow of Cancer Institute New South Wales (13/ECF/1-39). The work leading to this protocol was supported by project grants RG 09-08 and RG 13-06 (Cancer Council New South Wales), 570778 and 1051996 (Priority-driven collaborative cancer research scheme/Cancer Australia/Cure Cancer Australia Foundation), 08/RFG/1-27 (Cancer Institute New South Wales), APP1003637, and APP1084893 (National Health and Medical Research Council).

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Authors and Affiliations

  1. Frazer Institute, The University of Queensland, Brisbane, QLD, Australia

    Loredana Spoerri, Gency Gunasingh & Nikolas K. Haass

  2. The Centenary Institute, Sydney, NSW, Australia

    Kimberley A. Beaumont, Andrea Anfosso & Nikolas K. Haass

  3. Uniquest, The University of Queensland, Brisbane, QLD, Australia

    Kimberley A. Beaumont

  4. Mathematical Sciences, Queensland University of Technology, Brisbane, QLD, Australia

    Ryan J. Murphy & Alexander P. Browning

Authors
  1. Loredana Spoerri
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  2. Kimberley A. Beaumont
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  3. Andrea Anfosso
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  4. Ryan J. Murphy
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  6. Gency Gunasingh
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  7. Nikolas K. Haass
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Correspondence to Nikolas K. Haass .

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Editors and Affiliations

  1. Department of Histology and Embryology, Faculty of Medicine, Masaryk University, Brno, Czech Republic

    Zuzana Sumbalova Koledova

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Spoerri, L. et al. (2024). Real-Time Cell Cycle Imaging in a 3D Cell Culture Model of Melanoma, Quantitative Analysis, Optical Clearing, and Mathematical Modeling. In: Sumbalova Koledova, Z. (eds) 3D Cell Culture. Methods in Molecular Biology, vol 2764. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-3674-9_19

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  • DOI: https://doi.org/10.1007/978-1-0716-3674-9_19

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-3673-2

  • Online ISBN: 978-1-0716-3674-9

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