Purpose Maas et al. recently showed that a microenvironment-determined risk continuum, driven by the shift from microglia-like to myeloid-derived macrophage-like tumor-associated macrophages (TAMs), independently predicts meningioma progression beyond WHO grade. Whether this gradient is recoverable from bulk RNA-seq has not been tested.

Methods We computed a microglia-to-macrophage ssGSEA ratio using expanded gene sets (15 microglia, 17 macrophage) anchored to Maas core markers across 968 meningiomas from 5 GEO datasets, validated it against pseudo-bulk profiles from the Maas snRNA-seq cohort (n=25), and tested recurrence-free survival (RFS) association by Cox regression in a 101-patient subset (73 events, median follow-up 110.2 months).

Results The ratio correlated with single-cell microglia proportion (overlap-controlled r=0.70, 95% CI 0.42-0.86) and discriminated WHO grades and transcriptomic clusters, confirming biological recoverability. The ratio did not predict RFS (HR 0.92, 95% CI 0.72-1.16, p=0.46). A quantitative attenuation analysis predicts the Maas IHC HR of 2.00 attenuates to HR 1.24-1.40 after proxy measurement error (r2=0.22-0.49) and NF2-wildtype dilution (30-45%), yielding only 15-40% power at 73 events. An exploratory NF2-expression proxy subgroup (uncorrected p=0.056) showed a trend in NF2-low tumors (HR 0.68, 95% CI 0.46-1.01) absent in NF2-high tumors (HR 0.98, p=0.89). The Chen 34-gene tumor-intrinsic panel also reached near-chance discrimination (C-index 0.552).

Conclusion Single-cell-anchored ssGSEA recovers the Maas gradient in bulk RNA-seq but attenuates it below detectability in moderate-sized, NF2-unselected cohorts. The prognostic component is bounded by power and NF2 stratification, not an intrinsic modality failure; NF2-annotated cohorts with approximately 480 events are required for definitive testing.

The authors have declared no competing interest.

This study did not receive any funding.

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We aggregated meningioma RNA-seq data from five GEO datasets (GSE212666, GSE252291, GSE183653, GSE136661, GSE101638). For single-cell validation, the Maas et al. snRNA-seq Seurat object (44,266 nuclei, 26 samples) was obtained from their Zenodo deposit (doi:10.5281/zenodo.17296825).

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Analysis code will be deposited on GitHub upon publication.