A tumour is a population of cells that mutate, compete and are selected, exactly as species are, and treatment is one more selective pressure. Peter Nowell proposed this in 1976; it explains why tumours are mixtures of clones, why resistance to almost any single drug appears, and why some researchers now try to steer a tumour's evolution rather than eradicate it.
The claim. Cancer proceeds by Darwinian evolution within the body: heritable variation (mutations, epigenetic states, chromosome changes) arises in a founding clone, natural selection in the tissue favours variants that grow or survive better, and the tumour diversifies into subclones. The ecological extension (Merlo, Maley, Gatenby) adds that cells compete for space, oxygen and nutrients, cooperate through shared growth factors and face predators in the immune system, so a tumour is an ecosystem and therapy is a perturbation of it.
Who and when. Nowell's 1976 Science paper The clonal evolution of tumor cell populations stated the theory and predicted that each patient's tumour would be genetically unique and that therapy would select resistant variants. Cairns (1975) argued that tissue architecture limits somatic evolution. Merlo, Pepper, Reid and Maley (2006) set out cancer as an evolutionary and ecological process; Greaves and Maley reviewed the evidence in 2012; Gerlinger and Swanton's 2012 multi-region sequencing of kidney cancer showed branched evolution directly; Gatenby proposed adaptive therapy in 2009 and Zhang and colleagues reported a pilot in prostate cancer in 2017; Sottoriva and Graham proposed the Big Bang model of colorectal tumour growth in 2015.
Evidence for. Multi-region and single-cell sequencing show every tumour as a tree of related clones with a truncal set of early mutations and branches that differ between regions and metastases. Resistance arises by selection of pre-existing or newly mutated clones (EGFR T790M and C797S in lung cancer, KRAS clones under EGFR antibodies in colorectal cancer, BCR::ABL1 T315I in chronic myeloid leukaemia), and circulating tumour DNA tracks their rise and fall in real time. Intratumour heterogeneity predicts worse outcome. Mel Greaves' studies of childhood leukaemia in twins showed the founding clone can form in the womb years before diagnosis.
Evidence against and limits. Some tumours evolve neutrally after an early burst rather than by continuous selection (the Big Bang model), and some change by punctuated catastrophe (chromothripsis, whole-genome doubling) rather than gradual accumulation. Evolution is hard to predict for an individual patient, and the theory does not by itself say what starts the process. Randomised evidence that evolution-informed dosing beats standard dosing is still awaited.
Predictions that held or failed. Held: acquired resistance to any single targeted drug is close to inevitable; combinations and sequential monitoring delay it; rechallenge with an EGFR antibody works after resistant clones recede (CHRONOS). Failed: the Goldie-Coldman prediction that alternating non-cross-resistant regimens would improve outcomes was not borne out in trials; efforts to model a tumour's trajectory precisely enough to time therapy remain experimental.
Therapies that came from it. Combination therapy as a principle, minimal residual disease monitoring, liquid biopsy surveillance for resistance mutations, adaptive and intermittent dosing (adaptive therapy in prostate cancer), evolutionary herding and collateral sensitivity, and the mathematical oncology programme that models these dynamics. It is the theory the driver and passenger model feeds into, the ageing tissue view builds on (aged tissue changes what is selected), and the immunoediting theory applies to the immune system as predator.
Status: established. Tumours evolve, and the clinic already acts on it through monitoring and combinations; the ecological programme of steering evolution rather than eradicating the tumour is partly confirmed and awaits randomised trials.
Showing the technology this term belongs to: MRD / molecular residual disease testing.
The glossary entry explains the word; the readout page carries the scoring rule, the thresholds approvals use, the companion diagnostics and the tests.
One technology page, one pathway page and one term page on OnCo cite this paper by its DOI; this record gives the citation a page of its own so a reader can follow it without leaving OnCo. Read the abstract above alongside the citing pages listed under Related; the record was created automatically from the Europe PMC entry and its figures have not been checked by hand.
One term page on OnCo cites this paper by its DOI; this record gives the citation a page of its own so a reader can follow it without leaving OnCo. Read the abstract above alongside the citing page listed under Related; the record was created automatically from the Europe PMC entry and its figures have not been checked by hand.
One pathway page and one term page on OnCo cite this paper by its DOI; this record gives the citation a page of its own so a reader can follow it without leaving OnCo. Read the abstract above alongside the citing pages listed under Related; the record was created automatically from the Europe PMC entry and its figures have not been checked by hand.
A single biopsy is an incomplete picture of a patient's cancer. Truncal mutations shared by all cells (in kidney cancer, VHL) are the most reliable drug targets, whereas mutations in only some branches predict resistance. This is why liquid biopsy and multi-region sampling matter.
One technology page and one term page on OnCo cite this paper by its DOI; this record gives the citation a page of its own so a reader can follow it without leaving OnCo. Read the abstract above alongside the citing pages listed under Related; the record was created automatically from the Europe PMC entry and its figures have not been checked by hand.
One term page on OnCo cites this paper by its DOI; this record gives the citation a page of its own so a reader can follow it without leaving OnCo. Read the abstract above alongside the citing page listed under Related; the record was created automatically from the Europe PMC entry and its figures have not been checked by hand.
One technology page and one term page on OnCo cite this paper by its DOI; this record gives the citation a page of its own so a reader can follow it without leaving OnCo. Read the abstract above alongside the citing pages listed under Related; the record was created automatically from the Europe PMC entry and its figures have not been checked by hand.
Shares Ageing tissue and clonal fields: cancer as a disease of old tissue, Cancer stem cell theory and phenotypic plasticity, Drug-tolerant persister cells, Hallmarks of cancer as a synthesis of the theories and the tag theory.
Shares Seed and soil hypothesis of metastasis (Paget), Ageing tissue and clonal fields: cancer as a disease of old tissue, Hallmarks of cancer as a synthesis of the theories, Immune surveillance and cancer immunoediting and the tag theory.
Shares Atavistic theory: cancer as a reversion to an ancient programme, Hallmarks of cancer as a synthesis of the theories, Theories of cancer: how the ideas connect, Somatic mutation theory of cancer and the tag theory.
Shares Hallmarks of cancer as a synthesis of the theories, Theories of cancer: how the ideas connect, Somatic mutation theory of cancer and the tag theory.
Shares Theories of cancer: how the ideas connect, Somatic mutation theory of cancer and the tag theory.
Shares Mathematical models of cancer (mathematical oncology), Theories of cancer: how the ideas connect and the tag theory.
Shares Tumour evolution (somatic evolution), Evolutionary game theory in cancer, Clonal evolution and branching models, Adaptive therapy (evolution-based dosing).
Shares Ageing tissue and clonal fields: cancer as a disease of old tissue, Driver and passenger mutations: the refined somatic mutation theory, Field cancerisation, Somatic mutation theory of cancer.