Spatially resolved single-cell analyses of human meningioma identify novel cell states influencing tumor microenvironment and progression

Recent advances in our understanding of the molecular landscape of meningioma have generated new insights into the biology and heterogeneity of this disease, with demonstrated clinical value. However, there remains a need to understand tumor-intrinsic heterogeneity at single-cell resolution to inform potential therapeutic avenues. In this study, we examined the breadth of cell types and states in meningioma using a large cohort profiled with single-nuclear RNA sequencing and high-resolution spatial transcriptomics, as well as bulk DNA methylation and RNA sequencing (n = 712), bulk proteomics (n = 88) and plasma methylation (n = 59). We demonstrated that myeloid cell states differ across molecular groups of meningiomas and evolve meaningfully from dura to tumor. Myeloid cell states were also associated with unique myeloid–neoplastic interactions and neoplastic gene programs, suggesting a role in shaping the microenvironment. Finally, multiple non-neoplastic cell states refined outcome prediction beyond molecular group, suggesting a role in meningioma progression. This paper presents a sizeable single-cell multi-omic analysis of meningiomas comprising more than seven million cells. The results highlight tumor-intrinsic heterogeneity within both malignant and stromal compartments.

Authors

Institutions

Publication Details

Journal
Nature Genetics
Published
2026-06-09
DOI
https://doi.org/10.1038/s41588-026-02615-w
Primary Topic
Meningioma and schwannoma management
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Spatially resolved single-cell analyses of human meningioma identify novel cell states influencing tumor microenvironment and progression

Jeff Liu, Farshad Nassiri, J WANG, Derek S. Tsang et al.
Nature Genetics
Meningioma and schwannoma management
article

Spatially resolved single-cell analyses of human meningioma identify novel cell states influencing tumor microenvironment and progression

Jeff Liu, Farshad Nassiri, J WANG, Derek S. Tsang, Yosef Ellenbogen, Qingxia Wei, Sheila Mansouri, G Z Zadeh, O Singh, Andrew Ajisebutu, Andrew Gao, Chloe Gui, Kenneth Aldape, Aaron A. Cohen-Gadol, Leeor S. Yefet, Vikas Patil, Alexander P. Landry, Colleen Q. Ding
article en

Abstract

Recent advances in our understanding of the molecular landscape of meningioma have generated new insights into the biology and heterogeneity of this disease, with demonstrated clinical value. However, there remains a need to understand tumor-intrinsic heterogeneity at single-cell resolution to inform potential therapeutic avenues. In this study, we examined the breadth of cell types and states in meningioma using a large cohort profiled with single-nuclear RNA sequencing and high-resolution spatial transcriptomics, as well as bulk DNA methylation and RNA sequencing (n = 712), bulk proteomics (n = 88) and plasma methylation (n = 59). We demonstrated that myeloid cell states differ across molecular groups of meningiomas and evolve meaningfully from dura to tumor. Myeloid cell states were also associated with unique myeloid–neoplastic interactions and neoplastic gene programs, suggesting a role in shaping the microenvironment. Finally, multiple non-neoplastic cell states refined outcome prediction beyond molecular group, suggesting a role in meningioma progression. This paper presents a sizeable single-cell multi-omic analysis of meningiomas comprising more than seven million cells. The results highlight tumor-intrinsic heterogeneity within both malignant and stromal compartments.

Nature Genetics
Allen Institute for Brain Science (US), University Health Network (CA), Mayo Clinic (US), University of Toronto (CA), University of Utah (US), WinnMed (US), Princess Margaret Cancer Centre (CA), Mayo Clinic in Arizona (US), Mayo Clinic in Florida (US)
Brain Tumour Charity, Canadian Institutes of Health Research
Openalex Percentile: Top 7%
Meningioma and schwannoma management
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.