Abstract
Despite advances in artificial intelligence (AI) within cancer research, its application toward realizing differentiation therapy in solid tumors remains limited. Using colorectal cancer (CRC) as a model, we developed a machine learning (ML) framework, CANDiT ( Cancer Associated Nodes for Differentiation Targeting ), to selectively induce differentiation and death of cancer stem cells (CSCs)-a key obstacle to durable response. Centering on one node, CDX2 , a master differentiation factor lost in high-risk, poorly differentiated CRCs, we built a transcriptomic network to identify therapeutic strategies for CDX2 restoration. Network-based prioritization identified PRKAB1 , a stress polarity sensor, as a top target. A clinical-grade PRKAB1 agonist reprogrammed transcriptional networks, induced crypt differentiation, and selectively eliminated CDX2-low CSCs in CRC cell lines, xenografts and patient-derived organoids (PDOs). Multivariate analyses in PDOs revealed a strong therapeutic index, linking efficacy (IC₅₀) to the biomarker-defined CDX2-low state. A 50-gene response signature-derived from an integrated analyses of all three models and trained across multiple datasets-revealed that CDX2 restoration therapy may translate into a ∼50% reduction in recurrence and mortality risk. Mechanistically, treatment activated a differentiation-associated stress polarity signaling axis while dismantling Wnt and YAP-driven stemness programs essential to CSC survival. Thus, CANDiT offers a scalable path to CSC-directed therapy in solid tumors by translating transcriptomic vulnerabilities into precision treatments. ONE SENTENCE SUMMARY: In this work, Sinha et al. introduce a machine learning-guided framework to identify and target transcriptomic vulnerabilities in colorectal cancer, demonstrating that differentiation therapy selectively eliminates cancer stem cells and reduces recurrence risk. HIGHLIGHTS: An ML framework ( CANDiT ) identifies target for differentiation therapy for CRCs Therapy induces crypt differentiation and CSC-specific cytotoxicityCDX2-low state predicts therapeutic response; restoration improves prognosisTherapy dismantles stemness via reactivation of stress polarity signaling.