title: Cancer phenotype as the outcome of an evolutionary game between normal and malignant cells.
abstract: BACKGROUND
  There is variability in the cancer phenotype across individuals: two patients with the same tumour may experience different disease life histories, resulting from genetic variation within the tumour and from the interaction between tumour and host. Until now, phenotypic variability has precluded a clear-cut identification of the fundamental characteristics of a given tumour type.
  
  
  METHODS
  Using multiple myeloma as an example, we apply the principles of evolutionary game theory to determine the fundamental characteristics that define the phenotypic variability of a tumour.
  
  
  RESULTS
  Tumour dynamics is determined by the frequency-dependent fitness of different cell populations, resulting from the benefits and costs accrued by each cell type in the presence of others. Our study shows how the phenotypic variability in multiple myeloma bone disease can be understood through the theoretical approach of a game that allows the identification of key genotypic features in a tumour and provides a natural explanation for phenotypic variability. This analysis also illustrates how complex biochemical signals can be translated into cell fitness that determines disease dynamics.
  
  
  CONCLUSIONS
  The present paradigm is general and extends well beyond multiple myeloma, and even to non-neoplastic disorders. Furthermore, it provides a new perspective in dealing with cancer eradication. Instead of trying to kill all cancer cells, therapies should aim at reducing the fitness of malignant cells compared with normal cells, allowing natural selection to eradicate the tumour.
authors.affiliation: Division of Hematology, College of Medicine, Mayo Clinic, Rochester, MN 55905, USA. dingli.david@mayo.edu
authors.forename: D
authors.initials: D
authors.lastname: Dingli
authors.forename: F A C C
authors.initials: FA
authors.lastname: Chalub
authors.forename: F C
authors.initials: FC
authors.lastname: Santos
authors.forename: S
authors.initials: S
authors.lastname: Van Segbroeck
authors.forename: J M
authors.initials: JM
authors.lastname: Pacheco
mesh_terms: D005716:Game Theory; D006801:Humans; D009101:Multiple Myeloma / Q000473:pathology / Q000628:therapy*; D010641:Phenotype; D012641:Selection, Genetic