A framework for using DNA methylation-based modelling for the clinical management of cranial meningioma

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.