4.8 Article

Universal scaling laws rule explosive growth in human cancers

Journal

NATURE PHYSICS
Volume 16, Issue 12, Pages -

Publisher

NATURE RESEARCH
DOI: 10.1038/s41567-020-0978-6

Keywords

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Funding

  1. James S. McDonnell Foundation 21st Century Science Initiative in Mathematical and Complex Systems Approaches for Brain Cancer [220020560, 220020450]
  2. Ministerio de Economia y Competitividad/FEDER, Spain [MTM2015-71200-R]
  3. Junta de Comunidades de Castilla-La Mancha [SBPLY/17/180501/000154]
  4. MINECO grant MINECO-Retos [SAF2017-89643-R]
  5. Bristol-Myers Squibb Melanoma Research Alliance Young Investigator Award 2017 [498103]
  6. Beug Foundation's Prize for Metastasis Research 2017
  7. Fundacion Ramon Areces [CIVP19S8163]
  8. Worldwide Cancer Research [19-0177]
  9. H2020-FETOPEN [828972]
  10. Fundacio La Marato de tv3 [141]
  11. Clinic and Laboratory Integration Program CRI Award 2018 [54545]
  12. AECC Coordinated Translational Groups 2017 [GCTRA16015SEOA]
  13. LAB AECC 2019 [LABAE19002VALI]
  14. La Caixa INPhINIT Fellowship [LCF/BQ/IN17/11620028]
  15. La Caixa-Severo Ochoa International PhD Program Fellowship [LCF/BQ/SO16/52270014]
  16. European Molecular Biology Organization Young Investigators programme [4053]

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Most physical and other natural systems are complex entities that are composed of a large number of interacting individual elements. It is a surprising fact that they often obey the so-called scaling laws that relate an observable quantity to a measure of the size of the system. Here, we describe the discovery of universal superlinear metabolic scaling laws in human cancers. This dependence underpins increasing tumour aggressiveness, owing to evolutionary dynamics, that leads to an explosive growth as the disease progresses. We validated this dynamic using longitudinal volumetric data of different histologies from large cohorts of patients with cancer. To explain our observations we tested complex, biologically inspired mathematical models that describe the key processes that govern tumour growth. Our models predict that the emergence of superlinear allometric scaling laws is an inherently three-dimensional phenomenon. Moreover, the scaling laws that we identified allowed us to define a set of metabolic metrics with prognostic value, which adds clinical utility to our findings. The authors investigate the relationship between the volume of malignant tumours and their metabolic processes using a large dataset of patients with cancer. They find that cancers follow a superlinear metabolic scaling law, which implies that the proliferation of cancer cells accelerates with increasing volume.

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