Scientists stunned as new AI unlocks game-changing cancer treatment

UCLA researchers developed MAESTRO, an AI platform that uses large language models and biomedical knowledge to identify drug combinations that may overcome cancer treatment resistance. Detailed in Advanced Science, MAESTRO evaluates candidate therapies alongside an existing treatment, ranks them through repeated model runs, and produces proposed biological mechanisms for laboratory testing. The team used MAESTRO to screen 3,592 natural products as potential partners for enzalutamide, a drug used for advanced prostate cancer. Each candidate was evaluated more than 100 times, and 150 high-confidence compounds were selected for testing in 3D prostate-cancer spheroids. Of those, 23 produced significantly greater anti-cancer effects with enzalutamide than either treatment alone. Berberine, a naturally occurring plant compound, showed consistent synergy with enzalutamide across four prostate-cancer models with distinct resistance mechanisms. Laboratory tests found that the berberine-enzalutamide pairing increased AMPK activity and suppressed mTORC1 signaling, while increasing cellular stress and reducing DNA replication and cell-cycle progression. The researchers plan to test the combination in patient-derived tumor models and animal studies. They also plan to add biological data sources to MAESTRO and apply it to other cancer types and resistance mechanisms.