Artificial Intelligence-Guided Cancer Engineering for Tumor Normalization Executed by Tumor Lysosomal-Triggered...

Cancer engineering for tumor normalization offers a promising therapeutic strategy to reverse malignant cells and their supportive tumor microenvironment into a more benign state. Herein, an artificial intelligence (AI) approach was developed using mRNA data from patients with lung adenocarcinoma to facilitate the identification of aberrant signaling pathways, specifically focusing on PD-L1, Wnt, and macropinocytosis. Targeting these characteristics, we have developed a supramolecular construct called cancer corrector (CCtor) with the aim of harnessing the enhanced macropinocytosis observed in cancer cells. Undergoing cleavage and subsequent drug release triggered by the lysosomal protease in cancer cells, CCtor rectifies the aberrant hyperactivity of both Wnt and PD-L1 signaling pathways. This dual-action therapeutic strategy not only restores normalcy to cancer cells but also exerts an exceptionally robust therapeutic effect. This work exemplifies a future direction for cancer therapies by combining AI with molecular engineering to significantly improve patient outcomes through tumor behavior normalization.