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Beyond Multilevel Selection in Cancer: Rethinking Metastasis Through Selection for Function.

Frédéric Thomas1, Antoine M Dujon1,2

  • 1CREEC/CANECEV, Mivegec (CREES) Department, University of Montpellier, CNRS, IRD, Montpellier, France.

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Metastasis, the spread of cancer, may not fit multilevel selection (MLS) models. A new framework suggests viewing metastatic sites as a system, focusing on selection for function rather than group reproduction for cancer evolution.

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Area of Science:

  • Evolutionary biology
  • Cancer research
  • Systems biology

Background:

  • Multilevel selection (MLS) theory offers a framework for cancer evolution, distinguishing MLS1 and MLS2.
  • Applying MLS2 to metastasis is challenging due to the nature of tumor site interactions.
  • Classical Darwinian models struggle to explain the coordinated persistence of multiple metastatic sites.

Purpose of the Study:

  • To propose an alternative framework for understanding cancer metastasis.
  • To explain the resilience and coordination of metastatic systems.
  • To complement existing multilevel selection (MLS) theory.

Main Methods:

  • Conceptual analysis of cancer evolution frameworks.
  • Comparison of multilevel selection (MLS) theory with selection for function.
  • Systems-level perspective on metastasis.

Main Results:

  • Metastatic tumor sites function as components of a distributed system, not isolated units.
  • Selection for function provides a framework for understanding trait maintenance in metastatic systems.
  • This perspective accounts for system-level persistence without requiring group reproduction.

Conclusions:

  • Cancer metastasis may be better understood through selection for function rather than solely MLS2.
  • The metastatic system's resilience arises from coordinated function of multiple sites.
  • This view aligns with metastasis reflecting ancient cellular programs in a non-reproductive context.