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Mutagenicity and Carcinogenicity01:25

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Genes usually encode proteins necessary for the proper functioning of a healthy cell. Mutations can often cause changes to the gene expression pattern, thereby altering the phenotype.
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Cancer cells accumulate genetic changes at an abnormally rapid rate due to the defects in the DNA repair mechanisms. From an evolutionary perspective, such genetic instability is advantageous for cancer development. Mutant cell lines accumulate a series of beneficial mutations that contribute to their progression into cancer.
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Updated: Mar 31, 2026

Chemical-Induced Skin Carcinogenesis Model Using Dimethylbenz[a]Anthracene and 12-O-Tetradecanoyl Phorbol-13-Acetate DMBA-TPA
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Invariant Characteristics of Carcinogenesis.

Simon Sherman1, Nirosha Rathnayake1, Tengiz Mdzinarishvili2

  • 1Eppley Institute for Research in Cancer, University of Nebraska Medical Center, Omaha, Nebraska, United States of America; College of Public Health, University of Nebraska Medical Center, Omaha, Nebraska, United States of America.

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|October 15, 2015
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Summary

Cancer modeling reveals distinct, inherent patterns in cancer presentation and resistance rates across gastrointestinal subtypes. These findings are consistent regardless of location, offering potential for improved cancer prediction and prevention strategies.

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Area of Science:

  • Epidemiology
  • Biostatistics
  • Mathematical Biology

Background:

  • Cancer development is complex, influenced by aging and individual susceptibility.
  • Understanding cancer progression requires robust mathematical and statistical models.
  • Previous models often overlook population heterogeneity in cancer risk.

Purpose of the Study:

  • To develop and apply a carcinogenic model differentiating between cancer-susceptible and cancer-resistant individuals.
  • To analyze age, time period, and birth cohort effects on cancer development.
  • To estimate individual cancer presentation and resistance rates for specific gastrointestinal cancers.

Main Methods:

  • Utilized conditional survival analyses for cancer-susceptible individuals.
  • Employed computational experiments with SEER registry data (1975-2009) for multiple gastrointestinal cancers.
  • Estimated population hazard rates, individual cancer presentation rates, and individual cancer resistance rates.

Main Results:

  • Identified intrinsic, cancer-subtype-specific patterns for age effects, presentation, and resistance rates.
  • Demonstrated invariability of these patterns across different living locations.
  • Showed that these patterns are well-adjusted for modifiable variables averaged over time.

Conclusions:

  • The specificity and invariability of carcinogenic characteristics suggest their utility in predictive studies.
  • These findings can inform the development of novel cancer prevention strategies.
  • The model provides a framework for understanding cancer development in aging populations.