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Published on: February 22, 2015
Longitudinal Evolution and Cellular Plasticity in Meningioma: Insights From Single-Cell Transcriptomics
Ji Yoon Lee1,2, Jason K Sa1,3, Harim Koo4
1Department of Biomedical Informatics, Korea University College of Medicine, Seoul, Korea.
Abstract:
Meningiomas are the most common primary intracranial tumors and exhibit a broad spectrum of clinical behavior, ranging from indolent growth to repeated recurrence and aggressive progression. Over the past decade, genomic, epigenomic, bulk transcriptomic, and single-cell studies have refined meningioma classification and identified molecular features associated with recurrence risk. However, recurrence is increasingly recognized as a dynamic process shaped by tumor-intrinsic plasticity, subtype redistribution, treatment-related selection, and remodeling of the tumor microenvironment. Recent longitudinal single-nucleus RNA sequencing of matched primary and recurrent meningiomas has extended this framework by demonstrating enrichment of proliferative, DNA repair, and extracellular matrix programs in recurrent disease, together with multidirectional transcriptional trajectories rather than simple linear progression. These findings complement earlier methylation- and transcriptome-based risk models, as well as cross-sectional single-cell studies that have highlighted neoplastic heterogeneity, macrophage interactions, and immune-state diversity across meningioma grades. Among recurrence-associated genes, COL6A3 has emerged as a clinically relevant extracellular matrix marker linked to aggressive tumor states and poor relapse-free survival. Nevertheless, the proposed COL6A3-macrophage interaction should be interpreted cautiously because current evidence remains largely correlative and may be influenced by intervening treatment between primary and recurrent sampling. This review synthesizes current evidence on longitudinal evolution, cellular plasticity, molecular subtype shifts, and microenvironmental remodeling in recurrent meningioma, while outlining key limitations and future directions for clinically actionable longitudinal profiling.
