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Peer-reviewedCC BY 4.0NPJ Precision Oncology

Moving beyond the neutral-Darwinian dichotomy to inform precision oncology

  • Amit Sud1,2,3,4
  • Richard S. Houlston5
5 affiliations
  1. 1Centre for Immuno-Oncology, Nuffield Department of Medicine, University of Oxford, Oxford, UK
  2. 2Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA USA
  3. 3Broad Institute of MIT and Harvard, Cambridge, MA USA
  4. 4Harvard Medical School, Boston, MA USA
  5. 5Division of Genetics and Epidemiology, The Institute of Cancer Research, London, UK
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Abstract

Current methods for distinguishing neutral from selection-driven tumour evolution rely on assumptions frequently violated in clinical samples. We argue that tumour evolution is not a binary state, but a dynamic continuum shaped by genetic and non-genetic heterogeneity, spatial constraints, microenvironmental pressures and therapeutic bottlenecks. Refining evolutionary inference through integrative, longitudinal and spatially resolved analyses will be essential to align these models with therapeutic decision-making in precision oncology.

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Cite

BibTeXRIS
BibTeX
@article{sud2026moving,
  title = {{Moving beyond the neutral-Darwinian dichotomy to inform precision oncology}},
  author = {Amit Sud and Richard S. Houlston},
  journal = {NPJ Precision Oncology},
  year = {2026},
  month = jul,
  doi = {10.1038/s41698-026-01606-8},
  url = {https://doi.org/10.1038/s41698-026-01606-8},
  note = {CC BY 4.0},
}
RIS
TY  - JOUR
TI  - Moving beyond the neutral-Darwinian dichotomy to inform precision oncology
AU  - Amit Sud
AU  - Richard S. Houlston
PY  - 2026
DA  - 2026/07/10
JO  - NPJ Precision Oncology
DO  - 10.1038/s41698-026-01606-8
UR  - https://doi.org/10.1038/s41698-026-01606-8
AB  - Current methods for distinguishing neutral from selection-driven tumour evolution rely on assumptions frequently violated in clinical samples. We argue that tumour evolution is not a binary state, but a dynamic continuum shaped by genetic and non-genetic heterogeneity, spatial constraints, microenvironmental pressures and therapeutic bottlenecks. Refining evolutionary inference through integrative, longitudinal and spatially resolved analyses will be essential to align these models with therapeutic decision-making in precision oncology.
SN  - 2397-768X
ER  -