A Model of Tumor Development

tumorigenesis

Tumors develop in two distinct stages: (1) Initiation to Last-Common-Ancestor(LCA) where 6-8 “driver-mutations” occur sequentially over 10-50 years and (2) LCA to Metastasis where mutations occur more rapidly in parallel. In the first phase, mutations occur slowly and pierce 6-8 barriers to unrestrained growth by “hot-wiring” pro-growth pathways and then “shorting-out” pro-death pathways . In the second phase, genomic instability creates a large-heterogeneous-population that is well-equipped to compete against bigger-picture-limitations such as oxygen-availability, tissue-size, attacking immune cells and chemotherapies.

In the graphic above, we try to combine 3 common visualizations for tumor development into one unified-conceptual image. This graphic can be thought of as conceptual-model of Chapter 11 of Weinberg’s Biology of Cancer.1 The top-graphic on the step-wise nature of early-tumor growth was inspired by a article in Nature Reviews Cancer and some early models of tumor growth kinetics.2-5 The middle and bottom graphics attempt to capture parallel “internal” changes in tumor heterogeneity (middle) and morphology (bottom) by color-coding different clones within the famous “Vogelgram.” The middle-graphic was inspired by the mathematical modeling of Martin Nowak along with phylogenetic work by several groups on several cancers.6-9

 

REFERENCES:

  1. Weinberg, R.A. The Biology of Cancer (2nd ed.), 2014, Garland Science.
  2. Aktipis, C.A. et al. Life history trade-offs in cancer evolution. Nat. Rev. Cancer, 2013, 13, 883.
  3. Laird, A.K. Dynamics of Tumor Growth Br. J. Cancer, 1964, 18, 490.
  4. Kendel, W.S. Gompertzian growth as a consequence of tumor heterogeneity. 1985, 73, 103.
  5. Byrne, H.M. Dissecting cancer through mathematics: from the cell to the animal model. Nat. Rev. Cancer, 2010, 10, 221.
  6. Michor, F.; Iwasa, Y.; Nowak, M.A. Dynamics of cancer progression. Nat. Rev. Cancer, 2004, 4, 197.
  7. Yates, Y.R.; Campbell, P.J. Evolution of the cancer genome. Nat. Rev. Genetics, 2012, 13, 795.
  8. Luebeck, E.G. Genome evolution of metastasis. Nature, 2010, 467, 1053.
  9. Caravagna, G.et al. Algorithmic methods to infer the evolutionary trajectories in cancer progression. PNAS, 2016, 113, E4025

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