Information dynamics in carcinogenesis and tumor growth

Area of Science:

• Biophysics
• Cancer Biology
• Information Theory

Background:

• Cellular information storage and transmission are crucial for normal and cancerous cell functions.
• Carcinogenesis involves genomic mutations that alter cellular information processing.
• Understanding information dynamics in cancer is key to explaining tumor development.

Purpose of the Study:

• To analyze the role of information in carcinogenesis using information theory and Monte Carlo methods.
• To investigate how genomic mutations affect intracellular information during cancer evolution.
• To model tumor growth dynamics based on information degradation principles.

Main Methods:

• Application of information theory and Monte Carlo simulations.
• Analysis of genomic mutation accumulation and its impact on cellular information.
• Development of Extreme Physical Information (EPI) theory to model tumor growth.

Main Results:

• Genomic mutations during carcinogenesis degrade intracellular information, particularly in tumor suppressor genes.
• Tumor cells approach a minimum information state, characterized by dedifferentiation and proliferation.
• EPI theory predicts power law tumor growth (exponent ~1.62), consistent with empirical data (exponent ~1.72).
• Monte Carlo simulations confirm power law growth and reveal significant early-stage cell death (~40%).

Conclusions:

• Carcinogenesis is a process of constrained information degradation, leading to minimum information cancer systems.
• Information dynamics are fundamentally linked to tumor development, growth, and clinical manifestation.
• The information degradation model and its predictions offer insights into tumor age estimation and screening efficacy limitations.