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Widespread Immunity to Breast and Prostate Cancers is Predictedby a Novel Model that also Determines Sporadic and Hereditary Susceptible PopulationSizes

Published online by Cambridge University Press:  28 April 2010

I. Kramer
I. Kramer*
Affiliation:
Physics Department, University of Maryland Baltimore County
*
* E-mail: [email protected]
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Abstract

Natural immunity to breast and prostate cancers is predicted by a novel, saturatedordered mutation model fitted to USA (SEER) incidence data, a prediction consistent withthe latest ideas in immunosurveillance. For example, the prevalence of natural immunity tobreast cancer in the white female risk population is predicted to be 76.5%; this immunitymay be genetic and, therefore, inherited. The modeling also predicts that 6.9% of WhiteFemales are born with a mutation necessary to cause breast cancer (the hereditaryform) and, therefore, are at the highest risk of developing it. By contrast,16.6% of White Females are born without any such mutation but are nonetheless susceptibleto developing breast cancer (the sporadic form). The modeling determinesthe required number of ordered mutations for a cell to become cancerous as well as themean time between consecutive mutations for both the sporadic and hereditary forms of thedisease. The mean time between consecutive breast cancer mutations was found to varybetween 2.59 - 2.97 years, suggesting that such mutations are rare events and establishingan upper bound on the lifetime of a breast cell. The prevalence of immunity to breastcancer is predicted to be 79.7% in Blacks, 86.5% in Asians, and 85.8% in Indians.Similarly, the prevalence of immunity to prostate cancer is predicted to be 67.4% forWhites, 50.5% for Blacks, 77.7% for Asians, and 78.6% for Indians. It is of paramountimportance to delineate the mechanism underlying immunity to these cancers.

Keywords

cancer incidencemutation modelimmunitysporadichereditarypathwaysproto-oncogeneimmunosurveillancecell lifetime
Type
Research Article
Information
Mathematical Modelling of Natural Phenomena , Volume 5 , Issue 3: Mathematical modeling in the medical sciences , 2010 , pp. 134 - 164
Copyright
© EDP Sciences, 2010

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