Targeted gene expression profiling predicts meningioma outcomes and radiotherapy responses

Area of Science:

• Neuro-oncology
• Genomics
• Cancer Biomarkers

Background:

• Meningioma, the most common primary intracranial tumor, requires improved risk stratification beyond current standards.
• Postoperative radiotherapy indications for meningioma remain controversial, highlighting the need for better prognostic tools.

Approach:

• Developed and validated a 34-gene expression biomarker and risk score for predicting meningioma clinical outcomes.
• Compared the biomarker's performance against nine other classification systems in a large, multi-institutional cohort (N=1856).

Key Points:

• The gene expression biomarker significantly improved prediction of local recurrence (AUC 0.81) and overall survival (AUC 0.80) compared to existing methods.
• It identified meningiomas likely to benefit from postoperative radiotherapy, with a hazard ratio of 0.54.
• The biomarker re-classified a substantial proportion of meningiomas (up to 52.0%), suggesting refined postoperative management for nearly 30% of patients.

Conclusions:

• A targeted gene expression biomarker offers superior discrimination of meningioma outcomes.
• This biomarker accurately predicts response to postoperative radiotherapy, enabling more personalized treatment strategies.