Grant: Project Grant

Medulloblastoma (MB) is the most common malignant brain tumor in children, accounting for a high number of pediatric cancer-related deaths. This aggressive tumor originates in the cerebellum, the part of the brain responsible for coordinating movement and balance. MB is highly heterogeneous, meaning it varies greatly at the molecular level, and can be classified into four distinct subgroups: WNT, SHH, Group 3, and Group 4. Each subgroup has unique biological characteristics, genetic profiles, and clinical outcomes. Currently, diagnosing and classifying MB relies on analyzing tumor samples obtained during surgery. This approach limits the ability to determine the molecular subgroup before surgery, which is crucial for planning personalized treatment strategies. Most patients undergo extensive surgical resection, followed by craniospinal irradiation and high-dose chemotherapy. Despite these aggressive treatments, MB often recurs, and monitoring for relapse is challenging with existing methods like MRI and cerebrospinal fluid (CSF) cytology, which lack the sensitivity to detect microscopic disease. Improving diagnostic and monitoring techniques for MB is essential to enhance patient outcomes, reduce treatment-related complications, and provide more targeted therapies. This proposal aims to address these challenges by developing a non-invasive diagnostic platform that can accurately classify MB subgroups and monitor disease progression using blood samples.