Patel, Akash J.

Abstract Targeted gene expression profiling improves risk stratification for meningiomas, but the utility of this approach for low grade meningiomas is incompletely understood. To address this, 466 meningiomas that were initially used to validate a 34-gene expression biomarker were combined with 270 previously unpublished samples for an analysis of biomarker performance in newly diagnosed (n=691) or recurrent (n=45) WHO grade 1 meningiomas treated with gross total (GTR) or subtotal resection (STR), and newly diagnosed WHO grade 2 meningiomas treated with GTR. Prediction of local freedom from recurrence (LFFR) or overall survival (OS) was measured using Cox proportional hazards models and the Kaplan-Meier method. The cohort included 736 patients, 69.4% female, with a median age at diagnosis of 58 years. There were 635 WHO grade 1 meningiomas, 498 with GTR and 133 with STR, and 101 WHO grade 2 meningiomas with GTR. The median follow-up was 4.6 years, the local recurrence rate was 12.0% and the rate of death was 8.4%. The biomarker classified 51.5% of meningiomas as intermediate risk and 9.6% as high risk. Combining the biomarker with extent of resection identified 19.7% as unfavorable (intermediate molecular risk with STR or high molecular risk), including 7.4% of newly diagnosed WHO grade 1 meningiomas with GTR. The risk score was prognostic for LFFR overall (hazard ratio per 0.1 increase in risk score 1.89, 95% confidence interval 1.58-2.25) and across WHO grades, extents of resection, and newly diagnosed or recurrent settings. Gene expression risk groups were prognostic for LFFR, with improved outcomes among low molecular risk compared to intermediate molecular risk (Log-rank, p=0.0002) and high molecular risk meningiomas (Log-rank, p<0.0001). These data suggest that a targeted gene expression biomarker can identify low grade meningiomas that are more likely to recur after surgery, possibly changing management for approximately one-fifth of cases.

Abstract Background Surgery is the mainstay of treatment for meningioma, the most common primary intracranial tumor, but improvements in meningioma risk stratification are needed and current indications for postoperative radiotherapy are controversial. Recent studies have proposed prognostic meningioma classification systems using DNA methylation profiling, copy number variants, DNA sequencing, RNA sequencing, histology, or integrated models based on multiple combined features. Targeted gene expression profiling has generated robust biomarkers integrating multiple molecular features for other cancers, but is understudied for meningiomas. Methods Targeted gene expression profiling was performed on 173 meningiomas and an optimized gene expression biomarker (34 genes) and risk score (0 to 1) was developed to predict clinical outcomes. Clinical and analytical validation was performed on independent meningiomas from 12 institutions across 3 continents (N = 1856), including 103 meningiomas from a prospective clinical trial. Gene expression biomarker performance was compared to 9 other classification systems. Results The gene expression biomarker improved discrimination of postoperative meningioma outcomes compared to all other classification systems tested in the independent clinical validation cohort for local recurrence (5-year area under the curve [AUC] 0.81) and overall survival (5-year AUC 0.80). The increase in area under the curve compared to the current standard of care, World Health Organization 2021 grade, was 0.11 for local recurrence (95% confidence interval [CI] 0.07–0.17, P < 0.001). The gene expression biomarker identified meningiomas benefiting from postoperative radiotherapy (hazard ratio 0.54, 95% CI 0.37–0.78, P = 0.0001) and re-classified up to 52.0% meningiomas compared to conventional clinical criteria, suggesting postoperative management could be refined for 29.8% of patients. Conclusions A targeted gene expression biomarker improves discrimination of meningioma outcomes compared to recent classification systems and predicts postoperative radiotherapy responses.