Limited uptake of essential amino acid is effective for cancer therapy in metabolic networks of integrated constraint-based models

Nam models are context-specific genome-scale metabolic models for nine types of cancer and corresponding normal cells reconstructed from RECON 2, genetic mutation information, and expression profile data. In this study, computational experiments were conducted using Nam models to find effective ratios of uptake reactions such that cancer cells do not grow while normal cells grow. The original Nam models were extended to consider interactions between cancer and normal cells using an approach developed for representing host-microbe interactions. When uptake ratio of only single reaction was allowed to change at a time, the results of computational experiments showed that every essential amino acid had effective ranges for almost all nine types of cancer, while the other uptake reactions rarely had such effective ranges.