Meningioma DNA methylation grouping reveals biologic drivers and therapeutic vulnerabilities (array)

Choudhury/Raleigh UCSF meningioma multi-omic cohort

This UCSF cohort (Choudhury, Magill, Raleigh et al., Nature Genetics 2022, PMID 35534562) is the most heavily cross-linked dataset in this registry: 565 meningiomas profiled by DNA methylation array, 185 of the same tumors additionally bulk RNA-sequenced, and a 10-sample subset (6 patients, 57,114 cells, including matched dura and brain-tumor-interface pieces) single-cell RNA-sequenced. The paper established the widely-used three-group DNA methylation classification of meningioma (Merlin-intact, immune-enriched, hypermitotic) that several later datasets in this registry explicitly reference or build on. Strengths: large methylation cohort, real multi-modal matching (methylation + bulk RNA-seq + scRNA-seq on overlapping samples, a rare combination), open access with processed data files available. Limitations: per-sample clinical fields are only partially extracted so far. The bulk RNA-seq set has a per-sample grade breakdown (86 grade 1, 74 grade 2, 25 grade 3) and per-sample age, and the scRNA-seq set has per-sample age and a brain-tumor-interface sample count, but sex distribution remains unreported for all three records, and the 565-sample methylation series itself has no per-sample clinical fields extracted yet. Five other publications are also linked to this GEO SuperSeries family, suggesting a productive, still-active dataset with secondary reuse.