Developing Nutritional Engineering Approaches for Cancer Prevention in Marine Organisms Using The Nutricarcinogennet Algorithm

Abstract

In marine ecosystems, accumulating environmental pollutants, dietary exposure to mutagenic compounds, and bioaccumulation of toxicants throughout food webs are leading to increasing carcinogenic exposures. These exposures impair not only the health of marine organisms but also create secondary threats to human populations who rely on seafood products. To combat this issue, we submit the NutriCarcinogenNet Algorithm, which is a new computational tool for nutritional engineering and cancer-risk estimation in marine species. The NutriCarcinogenNet Algorithm can synthesize multi-tiered datasets, for example, nutritional profile, pollutant profile, metabolic biomarkers, and specific molecular interactions of carcinogens and their target pathways to quantify species-specific susceptibility and develop targeted preventive dietary strategies. Its mechanistic framework maps the relevant nutrient-carcinogen interactions to critical tumorigenic pathways, implementing predictive modelling techniques to develop interventions by weighted optimization of nutrient features. Preliminary, hypothetical analyses suggest that the NutriCarcinogenNet could reasonably predict nutrient profiles that would significantly protect against oxidative stress and thus, potentially promote a level of cancer-genicity through modulation of oncogenic signalling, sensu additional contaminant detoxification capacity in high cancer likelihood marine species. The implications of NutriCarcinogenNet go beyond individual species health; the tool could be a scalable approach to sustainable aquaculture, targeted marine conservation, and human-consumed seafood safety. In summary, the NutriCarcinogenNet Algorithm, by combining carcinogenesis biology and nutritional bioinformatics, is recommended as an advancement for the serious consideration and possible mitigation of cancer risk in all marine ecosystems.