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Abstract

Novel Approaches in Cancer Study

Cancer, Quantum Computing and TP53 Tumor Suppressor Gene Mutations Prediction

  • Open or Close Jean-claude Perez*

    Retired Interdisciplinary Researcher (IBM), France

    *Corresponding author: Jean-claude Perez, Retired Interdisciplinary Researcher (IBM), 7 avenue de terre-rouge F33127 Martignas Bordeaux metropole, France

Submission: January 20, 2018; Published: February 21, 2018

DOI: 10.31031/NACS.2018.01.000507

ISSN:2637-773X
Volume1 Issue2

Abstract

Mutations in the TP53 gene are encountered in about one in every two cases of cancer. The locations and frequencies of these mutations are well known and listed. It is therefore on these mutations of TP53 that we validate here a theoretical method of prediction of the mutagenic regions of TP53. This method uses the Master Code of Biology, revealing a coupling and unification between the Genomics and Proteomics codes for any DNA sequence analyzed. The “score” of these couplings highlights the functional regions of genes, proteins, chromosomes and genomes. Of the 393 codons of TP53, and for the 61 possible values of these codons authorized by the genetic code (i.e., 393x61 genes simulated), we prioritize the corresponding Master Code scores. Codons with scores close to 1 correspond to conserved regions whereas codons with scores close to 61 reveal highly mutagenic regions. Our method is then validated and correlated with the real mutations observed experimentally on hundreds of cases. We then analyze the potential of this method in the context of future quantum computers.

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