1. Cancer Biology
  2. Computational and Systems Biology

Quantitative analysis of tumour spheroid structure

  1. Alexander P Browning
  2. Jesse A Sharp
  3. Ryan J Murphy
  4. Gency Gunasingh
  5. Brodie Lawson
  6. Kevin Burrage
  7. Nikolas K Haass
  8. Matthew Simpson  Is a corresponding author
  1. Queensland University of Technology, Australia
  2. University of Queensland, Australia
https://doi.org/10.7554/eLife.73020
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  1. Alexander P Browning
  2. Jesse A Sharp
  3. Ryan J Murphy
  4. Gency Gunasingh
  5. Brodie Lawson
  6. Kevin Burrage
  7. Nikolas K Haass
  8. Matthew Simpson
(2021)
Quantitative analysis of tumour spheroid structure
eLife 10:e73020.
https://doi.org/10.7554/eLife.73020
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Abstract

Tumour spheroids are common in vitro experimental models of avascular tumour growth. Compared with traditional two-dimensional culture, tumour spheroids more closely mimic the avascular tumour microenvironment where spatial differences in nutrient availability strongly influence growth. We show that spheroids initiated using significantly different numbers of cells grow to similar limiting sizes, suggesting that avascular tumours have a limiting structure; in agreement with untested predictions of classical mathematical models of tumour spheroids. We develop a novel mathematical and statistical framework to study the structure of tumour spheroids seeded from cells transduced with fluorescent cell cycle indicators, enabling us to discriminate between arrested and cycling cells and identify an arrested region. Our analysis shows that transient spheroid structure is independent of initial spheroid size, and the limiting structure can be independent of seeding density. Standard experimental protocols compare spheroid size as a function of time; however, our analysis suggests that comparing spheroid structure as a function of overall size produces results that are relatively insensitive to variability in spheroid size. Our experimental observations are made using two melanoma cell lines, but our modelling framework applies across a wide range of spheroid culture conditions and cell lines.

Data availability

Code, data, and interactive figures are available as a Julia module on GitHub (https://github.com/ap-browning/Spheroids). Code used to process the experimental images is available on Zenodo (https://doi.org/10.5281/zenodo.5121093).

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Author details

  1. Alexander P Browning

    School of Mathematical Sciences, Queensland University of Technology, Brisbane, Australia
    Competing interests
    The authors declare that no competing interests exist.

  2. Jesse A Sharp

    School of Mathematical Sciences, Queensland University of Technology, Brisbane, Australia
    Competing interests
    The authors declare that no competing interests exist.

  3. Ryan J Murphy

    School of Mathematical Sciences, Queensland University of Technology, Brisbane, Australia
    Competing interests
    The authors declare that no competing interests exist.

  4. Gency Gunasingh

    The University of Queensland Diamantina Institute, University of Queensland, Brisbane, Australia
    Competing interests
    The authors declare that no competing interests exist.

  5. Brodie Lawson

    School of Mathematical Sciences, Queensland University of Technology, Brisbane, Australia
    Competing interests
    The authors declare that no competing interests exist.

  6. Kevin Burrage

    School of Mathematical Sciences, Queensland University of Technology, Brisbane, Australia
    Competing interests
    The authors declare that no competing interests exist.

  7. Nikolas K Haass

    4The University of Queensland Diamantina Institute, University of Queensland, Brisbane, Australia
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-3928-5360

  8. Matthew Simpson

    School of Mathematical Sciences, Queensland University of Technology, Brisbane, Australia
    For correspondence
    matthew.simpson@qut.edu.au
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-6254-313X

Funding

Australian Research Council (DP200100177)

  • Nikolas K Haass
  • Matthew Simpson

ARC Centre of Excellence for Mathematical and Statistical Frontiers (CE140100049)

  • Alexander P Browning
  • Jesse A Sharp

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. Jennifer Flegg, The University of Melbourne, Australia

Version history

  1. Received: August 13, 2021
  2. Accepted: November 26, 2021
  3. Accepted Manuscript published: November 29, 2021 (version 1)
  4. Version of Record published: January 7, 2022 (version 2)

Copyright

© 2021, Browning et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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  1. Alexander P Browning
  2. Jesse A Sharp
  3. Ryan J Murphy
  4. Gency Gunasingh
  5. Brodie Lawson
  6. Kevin Burrage
  7. Nikolas K Haass
  8. Matthew Simpson
(2021)
Quantitative analysis of tumour spheroid structure
eLife 10:e73020.
https://doi.org/10.7554/eLife.73020

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