Probability Distributions of p53 Mutations and Their Corresponding Shannon Entropies in Different Cancer Cell Types

S. A. Moghadam, S. I. Omar and J. A. Tuszynski ()
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S. A. Moghadam: University of Alberta, Department of Physics
S. I. Omar: University of Alberta, Department of Oncology
J. A. Tuszynski: University of Alberta, Department of Physics

A chapter in Trends in Biomathematics: Stability and Oscillations in Environmental, Social, and Biological Models, 2022, pp 37-77 from Springer

Abstract: Abstract Due to the vital role of the p53 protein mutations in about 50% of the human cancers, in this paper we investigate the probability distributions of different mutations in p53 across various human cancer cells. Using the p53 database (IARC TP53), we employed statistical analysis to determine the frequency of occurrence of amino acid mutations across various cancer types. We show that amino acid hotspot mutations of p53 are highly frequent in cancers regardless of their codon location in the sequence, and at least one of the hotspot mutations has the highest probability in various cancers. We also calculated the associated Shannon entropy values for all the possible mutations in a number of cancer types and compared them to the five-year survival rate for various cancer types. We have found no evidence of correlation between mutation entropy and 5-year survival probability values.

Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-031-12515-7_3

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DOI: 10.1007/978-3-031-12515-7_3

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