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A computational model for the cancer field effect.

Karl Deutscher1, Thomas Hillen1, Jay Newby1

  • 1Department of Mathematical and Statistical Sciences, University of Alberta, Edmonton, AB, Canada.

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|July 20, 2023
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Summary

Understanding the cancer field effect is crucial for preventing recurrence. Simulations show that removing the pre-cancerous field alongside tumors significantly delays cancer regrowth, highlighting the importance of comprehensive treatment.

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Area of Science:

  • Oncology
  • Computational Biology
  • Carcinogenesis

Background:

  • The Cancer Field Effect describes pre-cancerous cell areas resulting from carcinogen exposure.
  • These cells have a high potential to develop into cancer.
  • Tumor removal alone may leave the cancer field, increasing recurrence risk.

Purpose of the Study:

  • To model the cancer field effect using a hybrid cellular automaton.
  • To investigate the impact of carcinogens like tobacco and alcohol on cancer fields.
  • To evaluate the efficacy of combined tumor and field removal on cancer recurrence.

Main Methods:

  • Developed a hybrid cellular automaton (CA) model.
  • Integrated a multi-layer perceptron (MLP) to simulate gene expression changes due to carcinogens.
  • Simulated carcinogen interactions from smoking and alcohol on tongue cancer fields.

Main Results:

  • Tobacco smoking is a potent carcinogen, amplified by alcohol.
  • Alcohol alone has a lesser effect than tobacco.
  • Combined tumor and field removal delays recurrence more than tumor excision alone.
  • Cancer fields typically develop as polyclonal, with dominant lineages emerging.
  • Tumor formation is rarely monoclonal.

Conclusions:

  • Tobacco and alcohol significantly contribute to the cancer field effect.
  • Comprehensive surgical removal of both tumor and field is superior for preventing recurrence.
  • Understanding field dynamics is key to improving cancer treatment strategies.