TumorOriginPredictor: A Clinically Validated and Cloud-Deployed AI Platform for Tissue-of-Origin Identification in Cancer of Unknown Primary Using Somatic Mutation Profiles.

Cancer of Unknown Primary (CUP) remains one of the deadliest diagnostic challenges in oncology, accounting for 3-5% of all cancer diagnoses in the United States. Tumor origin is essential for guiding treatment; however, histological methods often fail in metastatic cases due to an inconclusive origin, leading to toxic and ineffective empirical therapies. Somatic mutations offer a promising alternative for accurate diagnosis via genomic alterations. We developed TumorOriginPredictor, a machine learning platform trained on 10,945 MSK-IMPACT mutation profiles. Five models generate the top three predicted tumor origins with rank-ordered probabilities, ensuring interpretability and clinical trust. Evaluated as a single platform, TumorOriginPredictor achieved over 72% top-3 accuracy across 12 cancer types and exceeded 80% for prevalent cancers. Clinically validated with 770 real-world profiles and deployed on Azure cloud, it provides real-time predictions, promoting individualized treatment by eliminating empirical therapies, reducing costs and time, and improving survival through a scalable, trustworthy AI platform.