Mathematical Modeling of PM2.5 Exposure, COX-2 Enzyme Expression, and Aspirin Intervention in Lung Cancer Risk

Lung cancer remains one of the leading causes of cancer-related mortality worldwide.Epidemiological studies have established a significant correlation between exposure to fine particulate matter (PM2.5) and an increased risk of lung cancer.Notably, PM2.5 derived from wildfire smoke has been shown to exhibit greater toxicity than PM2.5 from other sources, due to its higher oxidative potential and pro-inflammatory composition.The COX-2 enzyme, a crucial mediator of inflammation, is known to be upregulated in response to PM2.5 exposure, promoting tumorigenesis.This study employs a mathematical modeling approach to describe COX-2 induction using a modified Michaelis-Menten equation, incorporating real-world clinical hazard ratios.Furthermore, the inhibitory effect of aspirin, a nonsteroidal anti-inflammatory drug (NSAID), is modeled to determine its potential role in mitigating lung cancer risk.Monte Carlo simulations are conducted to evaluate variability in exposureresponse relationships.Our results suggest a dose-dependent reduction in COX-2 levels with aspirin intake, which correlates with a significant decrease in estimated lung cancer risk.These findings provide a quantitative framework for understanding environmental risk mitigation and suggest potential pharmacological intervention strategies.