Kookmin University research team identifies new molecular subtype of pediatric brain tumor medulloblastoma

Researchers have identified a new molecular subtype of medulloblastoma, a notoriously difficult-to-treat pediatric brain tumor. The breakthrough, achieved by a collaborative team including Professor Kim Kyung-hee from Kookmin University's Department of Applied Chemistry and Bio-medicine, offers a more refined understanding of the disease and opens doors for personalized treatment strategies.

The study, part of a larger initiative on precision medicine based on cancer proteogenomics, involved a comprehensive analysis of genomic, transcriptomic, epigenomic, proteomic, and phosphoproteomic data from more than 100 medulloblastoma patients. This extensive proteogenomic research allowed the team to reclassify the four previously known molecular groups of medulloblastoma into seven distinct subtypes.

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By comprehensively analyzing cancer proteogenomic information that reflects the actual function of tumors, we have presented a new classification system that allows for a more precise understanding of the molecular diversity of medulloblastoma.

Specifically, the SHH group was divided into SHHα and SHHβ, and Group 4 was further segmented into G4α, G4β, and G4γ. This granular classification provides a more precise explanation of the tumors' biological behaviors and their clinical outcomes. The research found that SHHβ and G4γ subtypes exhibited more active neuronal differentiation and a relatively better prognosis. Conversely, SHHα, G4α, and G4β subtypes were associated with a higher risk of recurrence and disease progression.

Furthermore, the study identified specific protein signaling pathways activated within each subtype and pinpointed potential therapeutic targets, such as CDK1/2, PARP, CLK1, and MET. These discoveries hold significant promise for developing targeted therapies tailored to individual patient profiles. Professor Kim Kyung-hee expressed optimism, stating that the new classification system, based on integrated proteogenomic information reflecting tumor function, will serve as crucial foundational data for developing patient-specific treatment strategies and targeted drugs.

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It is expected to be utilized as important foundational data for the development of patient-tailored treatment strategies and targeted therapies in the future.