A clinically applicable integrative molecular classification of meningiomas

Area of Science:

• Neuro-oncology
• Genomics
• Proteomics

Background:

• Meningiomas are the most common primary intracranial tumors in adults.
• Current treatment relies on surgery, lacking effective medical therapies.
• Existing classification systems do not fully predict meningioma behavior or guide treatment.

Purpose of the Study:

• To develop a molecular classification for meningioma that accurately predicts clinical outcomes.
• To identify distinct biological subtypes of meningioma.
• To uncover novel therapeutic targets for meningioma.

Main Methods:

• Integrated analysis of DNA copy-number aberrations, point mutations, methylation, and mRNA abundance.
• Proteogenomic characterization including immunohistochemistry.
• Single-cell RNA sequencing.

Main Results:

• Four consensus molecular groups of meningioma were identified.
• These molecular groups demonstrated superior prediction of clinical outcomes compared to existing schemes.
• Distinct biological profiles (immunogenic, benign NF2 wild-type, hypermetabolic, proliferative) were associated with each group.
• Group-specific protein targets were identified and validated.

Conclusions:

• The new molecular classification provides a more accurate framework for understanding meningioma behavior.
• Distinct molecular and biological characteristics inform potential therapeutic strategies.
• This classification advances personalized medicine approaches for meningioma treatment.