EPCO-12. MENINGIOMA COPY NUMBER ANALYSIS IDENTIFIES OPTIMIZED SIZE THRESHOLDS AND CO-OCCURRENCE MODELS FOR INDIVIDUALIZED RISK-STRATIFICATION

Abstract

Abstract Arm-level copy number alterations (CNAs) are common in meningiomas and are useful for risk-stratification, but there is no consensus regarding the optimal size threshold to define CNAs for prognostic models. Moreover, the prognostic importance of co-occurring CNA pairs and overall CNA burden in meningiomas remains incompletely understood. To address this, CNAs were analyzed in 691 retrospective meningiomas with clinical data and DNA methylation profiles from 3 international institutions. Arm-level CNAs were defined from DNA methylation profiles using iterative size thresholds ranging from 1-99% of each chromosome arm. The area under the curve (AUC) for 5-year local freedom from recurrence (LFFR) or overall survival (OS) was calculated using CNAs across size thresholds, and AUC standard deviation across thresholds was used as a measure of size-dependence. LASSO and Elastic Net Cox regressions were used to generate multi-CNA models for LFFR or OS and to identify prognostic co-occurring CNA pairs. These analyses identified 13 size-dependent prognostic CNAs in meningiomas, including loss of 1p, 3q, 4p, 4q, 6p, 6q, 9p, 10q, 12q, 14q,18q, and 22q, and gain of 1q. Regression models restricted to size-dependent CNAs improved risk stratification within strata of previously published models (Integrated score, Integrated grade), and identified prognostic CNAs not included in previous models, such as 1q gain, 7p loss, and 12q loss. Ontology analysis of genes in focal prognostic CNAs identified dysregulated STAT signaling and decreased expression of interferon-related genes from matched paired RNA sequencing. Models of size-dependent, prognostic, co-occurring CNA pairs identified 1p/22q codeletion, 1q gain/22q loss, and 9p/18q codeletion as significant predictors of LFFR. Increased CNA burden correlated with higher tumor grade and was significantly associated with worse LFFR and OS. In summary, chromosome-specific size thresholds identify prognostic arm-level CNAs and co-occurring CNA pairs in meningiomas. Thus, granular copy number analysis may improve risk stratification models for meningioma.