Assessing The Role Of Environmental Pollutants And Nutritional Components In Modulating Carcinogenesis in Aquatic Life Using Carcinogenmodnet

Abstract

Carcinogenesis in aquatic organisms is an important environmental and ecological issue, arising from exposure to a variety of contaminants and influenced by nutritional factors. This study seeks to evaluate the influence of environmental contaminants and nutritional elements on carcinogenesis in aquatic species using a new computational model, CarcinogenModNet. The model integrates multi-dimensional data on exposure profiles of pollutants, nutritional status, and molecular biomarkers to quantify DNA damage and the risk of cancer in selected aquatic species of interest. CarcinogenModNet predicts the interaction between carcinogenic pollutants (e.g., heavy metals, polycyclic aromatic hydrocarbons, pesticides) and either protective nutritional elements, components that may enhance risk, or promote both. CarcinogenModNet is designed as a prediction model to understand the dynamics of the carcinogenic process associated with exposure to carcinogenic pollutants in various aquatic environments. An important aspect of the study was evaluating the aspects of the nutritional data concerning non-carcinogenic and carcinogenic processes of the aquatic species; thus generalizing the scientific knowledge within CarcinogenModNet as it relates to cancer pathways, DNA damage levels, evaluating the impact of protective nutritional elements, and the potential to mitigate the level of DNA damage. Predictive conclusions from this model also apply to ecological risk assessments and risk to human food safety considerations through the consumption of fish and aquatic organisms. The integrated model is a new advance on traditional toxicological studies and incorporates the environmental and nutritional components of a systems biology approach. The findings highlight the two-fold importance of pollutant exposure and nutritional status or intake in managing carcinogenic risks relevant to aquatic environments. The model can function as a pathway for updates and improvements of CarcinogenModNet using more direct and population-level considerations. Future applications of CarcinogenModNet will focus on expanding species coverage and integrating molecular docking analyses to refine predictive accuracy and support targeted mitigation strategies.