AI-based precision prognostics and therapy personalization for childhood brain tumors

Accurate prediction of patient outcomes remains a critical challenge in oncology, in particular for childhood brain tumors, in which treatment decisions need to carefully balance risk of tumor recurrence and death against severe therapy-induced sequelae. Here, we developed MANTIS (methylation profiling and artificial neural networks for time-dependent individualized survival predictions), a precision artificial intelligence (AI) tool for medulloblastoma and ependymoma outcome prediction built on genome-wide DNA methylation array data from 2,786 patients. MANTIS generates individualized survival probabilities over a 10-year period and achieves concordance indices as high as 0.80 ± 0.07, significantly exceeding the predictive accuracy of current clinical indicators. Extending MANTIS to estimate individualized treatment effects identifies ~60% of patients with average-risk medulloblastoma without a significant survival disadvantage (P = 0.683) when treated with less intensive craniospinal irradiation doses, which is associated with improved neurocognitive outcomes. In conclusion, our study establishes a foundation for AI-based precision prognostics and therapy personalization in childhood brain tumors and offers a blueprint for similar initiatives in other cancer types. Stefan et al. present MANTIS, an AI model to predict individualized survival in childhood brain tumors from routine DNA methylation profiling. MANTIS may help identify patients who benefit from less intense treatment to reduce lifelong side effects.