Abstract Background DNA methylation profiling can be used to robustly predict postsurgical outcomes and response to radiotherapy (RT) for meningioma patients. To allow for seamless integration of these complementary models into clinical practice, a practical framework is needed. Methods We leveraged a cohort of nearly 2000 surgically-treated meningiomas with DNA methylation profiling and clinical outcomes data. Existing methylation-based prediction models were dichotomized to yield four risk groups: low and high recurrent risk, each with RT sensitive and resistant subgroups. Risk groups were correlated with progression-free survival in the context of existing biomarkers including extent of resection and WHO grade. Results We first demonstrated that all risk groups benefit from gross total resection. All “high-risk, RT sensitive” tumors (n = 306, 15.7%) also benefited from adjuvant RT: after GTR, median PFS increased from 4.68 (4.13-9.48) years to not reached (P = .003); after subtotal resection (STR), from 2.12 (1.59-3.02) to 4.09 (3.41-not reached) years (P = .004). “Low-risk, RT sensitive cases” (n = 1207, 61.8%) also benefited from RT after STR (median PFS 7.39 (6.66-12.8) vs. 16.53 (10.35-not reached) years, P = .03), suggesting that RT be considered in these patients. Neither “low-risk RT resistant” (n = 84, 4.3%) nor “high-risk RT resistant” (n = 356, 18.2%) cases benefited from RT, and the latter group was associated with universally poor outcomes. Conclusions We identify methylation-defined risk groups of meningioma for which additional benefit is gained from adjuvant RT, leading to a clinical decision-making framework for straightforward integration of molecular models into clinical practice.
Targeted gene expression profiling predicts meningioma outcomes and radiotherapy responses
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.
ATRT-08. SMARCB1- and SMARCA4-deficient malignant brain tumors with complex copy number alterations andTP53 mutations may represent the first clinical manifestation of Li-Fraumeni syndrome
Abstract Atypical teratoid/rhabdoid tumor (AT/RT) is a malignant central nervous system tumor predominantly affecting infants. Mutations of SMARCB1 or (rarely) SMARCA4 causing loss of nuclear SMARCB1 or SMARCA4 protein expression are characteristic features, but further recurrent genetic alterations are lacking. Most AT/RTs occur de novo, but secondary AT/RTs arising in other central nervous system tumors have been reported. Malignant gliomas, IDH-wildtype, arising in patients with Li-Fraumeni syndrome typically show somatic mutations of TP53 as well as complex copy number alterations, but little is known about loss of SMARCB1 or SMARCA4 protein expression in this context. Here we report two children, in whom malignant supratentorial brain tumors with SMARCB1-deficiency, complex copy number alterations and somatic TP53 mutations lead to the discovery of pathogenic/likely pathogenic TP53 variants in the germ line. Screening of the molecularneuropathology.org data set for cases with similar genetic and epigenetic alterations yielded another case with SMARCA4-deficiency in a young adult with Li-Fraumeni syndrome. In conclusion, SMARCB1- or SMARCA4-deficient malignant brain tumors with complex copy number alterations and somatic TP53 mutations in children and young adults may represent the first clinical manifestation of Li-Fraumeni syndrome and should prompt genetic counseling and investigation for TP53 germline status.
Imaging and diagnostic advances for intracranial meningiomas