Presentation (CTI)

OBJECTIVES: The incidence of cancer in adults under age 50 has risen nearly 80% since 1990. Traditional models struggle to explain the biological aggressiveness of these early-onset cancers, which include colorectal, breast, thyroid, reproductive and gastrointestinal. This scoping review investigates AI-driven multiomics and Evolutionary Game Theory (EGT) to identify how modern environmental "stressors" alter the cellular "fitness landscape," favoring malignant proliferation over healthy tissue cooperation.
METHODS: The focus of the analysis was a dual-layer framework: 1. AI Layer: Deep learning (via LSTM networks, a specialized recurrent neural network) analyzed longitudinal health records and multiomic signatures from patients less than 50 years of age to weight environmental variables (e.g., ultra-processed diets, microbiome dysbiosis, microplastics). 2. Game Theory Layer: Weighted variables parameterized an EGT model simulating cellular competition. Recent studies have modeled a "cooperative game" for tissue maintenance versus a "non-zero-sum game" for tumor-host interaction to determine how the "Westernized" exposome changes the fitness landscape for mutated cells.
RESULTS: AI analysis identified microbiome dysbiosis and endocrine disruptors as high-weight drivers of metabolic "niche construction." Game-theoretic simulations revealed that these environmental stressors significantly reduce the "cost of cheating" for mutated cells (i.e., the biological and evolutionary penalties a cell usually faces when it stops cooperating with the rest of the body and starts acting selfishly- becoming cancerous). In these "high-payoff" environments, the transition from healthy to malignant states occurs up to 1.5x faster in younger cohorts compared to historical controls, as modern stressors bypass traditional youthful tumor-suppressive checkpoints.
CONCLUSIONS: The rise in several early-onset cancers represents a shift in cellular social dynamics where modern stressors provide a competitive advantage to "selfish" cellular strategies. These findings suggest that health outcomes research should prioritize "Ecological Therapy", i.e., interventions designed to reset the metabolic environment by making cancerous strategies mathematically non-viable for the sub-50-year-old population.