Darwinian Evolution of Tumours

Abstract

Tumours as a human disease have been studied mostly from a mechanistic perspective in the past decades. It is now increasingly clear that tumourigenesis as an evolving process can be fully understood only in the light of evolution. Recent studies highlight the necessity of connecting the microevolution of a tumour with the macroevolution from unicellular life to metazoan multicellularity, which occurred ∼600 million years ago. With this background in mind, we discuss here the diverse, sometimes conflicting, views with regard to the driving forces of tumour evolution. Specifically, we show how mutation, selection, drift, migration, gain of function versus loss of function, genetic factors versus non‐genetic factors and deterministic forces versus stochasticity may affect the trajectory of a tumour evolution as well as our understanding.

Key Concepts

  • Tumourigenesis is a by‐product of the macroevolutionary event from unicellular life to metazoan multicellularity that occurred ∼600 million years ago.
  • Tumour progression is a microevolutionary process of the asexual tumour cell population, driven in part by forces typical to organismal evolution.
  • Unlike long‐term organismal evolution, which is driven exclusively by genetic forces, the short‐term tumour evolution can be affected heavily by epigenetic alterations. As a result, the decoupling between genetic divergence and expression divergence is expected.
  • Tumour evolution represents a reversal of the macroevolution from unicellularity to multicellularity, by erasing the constraints evolved for the maintenance of multicellularity. As a result, loss of function plays a more important role than gain of function.
  • Regardless of the external tissue environments, nearly all tumours evolve towards a predetermined cellular destination with properties typical to unicellular life.
  • Tumour evolution is driven by both deterministic factors and stochastic factors. Recognition of this helps reconcile development and evolution, two distinct languages in the cancer research community, with the former spoken mostly by cell biologists who advocate fixed cellular programmes as driving forces and the latter spoken by geneticists who appreciate the apparent stochasticity of driver gene mutations.

Keywords: Darwinian evolution; reverse evolution; multicellularity; unicellularity; cancer; tumour

Figure 1. The birth rate of cancer drivers peaks on the deepest branch of metazoans. (a) The phylogenetic relationships of humans and other 13 major clades. Emergence of the four early metazoan clades, Ctenophora, Porifera, Placozoa and Cnidaria, was extremely compressed in time ∼600 million years ago. The number of born genes is shown in parentheses behind each branch, and the number of genomes used for analysis is shown behind each clade. (b) The birth rate of cancer drivers and pseudo‐cancer drivers (y‐axis), randomly selected genes with evolutionary rates comparable to cancer drivers, on each of the 13 branches (x‐axis). Red triangles represent cancer drivers, and box plots represent pseudo‐cancer drivers, with horizontal lines showing the median rates and black dots showing the 10th or the 12 990th rates of a branch out of 13 000 simulations. Reproduced with permission from Figure 3 in Chen et al. 2015.
Figure 2. The model of reverse evolution from multicellularity to unicellularity explains the convergence towards ESC for tumours of different tissues/organs. Reproduced with permission from Figure 5 in Chen and He 2016.
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Further Readings

Greaves M and Maley CC (2012) Clonal evolution in cancer. Nature 481: 306–313. DOI: 10.1038/nature10762.

Wu CI, Wang HY, Ling SP and Lu XM (2016) The ecology and evolution of cancer: the ultra‐microevolutionary process. Annual Review of Genetics 50 (50): 347–369. DOI: 10.1146/annurev-genet-112414-054842.

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How to Cite close
He, Xionglei, and Chen, Han(May 2017) Darwinian Evolution of Tumours. In: eLS. John Wiley & Sons Ltd, Chichester. http://www.els.net [doi: 10.1002/9780470015902.a0026709]