Multiplatform genomic profiling and magnetic resonance imaging identify mechanisms underlying intratumor heterogeneity in meningioma.
Stephen T MagillHarish N VasudevanKyounghee SeoJavier E Villanueva-MeyerAbrar ChoudhurySiyuan John LiuMelike PekmezciSarah FindaklyStephanie HilzSydney LastellaBenjamin DemareeSteve E BraunsteinNancy Ann Oberheim BushManish K AghiPhilip V TheodosopoulosPenny K SneedAdam R AbateMitchel S BergerMichael W McDermottDaniel A LimErik M UllianJoseph F CostelloDavid R RaleighPublished in: Nature communications (2020)
Meningiomas are the most common primary intracranial tumors, but the molecular drivers of meningioma tumorigenesis are poorly understood. We hypothesized that investigating intratumor heterogeneity in meningiomas would elucidate biologic drivers and reveal new targets for molecular therapy. To test this hypothesis, here we perform multiplatform molecular profiling of 86 spatially-distinct samples from 13 human meningiomas. Our data reveal that regional alterations in chromosome structure underlie clonal transcriptomic, epigenomic, and histopathologic signatures in meningioma. Stereotactic co-registration of sample coordinates to preoperative magnetic resonance images further suggest that high apparent diffusion coefficient (ADC) distinguishes meningioma regions with proliferating cells enriched for developmental gene expression programs. To understand the function of these genes in meningioma, we develop a human cerebral organoid model of meningioma and validate the high ADC marker genes CDH2 and PTPRZ1 as potential targets for meningioma therapy using live imaging, single cell RNA sequencing, CRISPR interference, and pharmacology.
Keyphrases
- single cell
- optic nerve
- rna seq
- genome wide
- gene expression
- magnetic resonance
- magnetic resonance imaging
- high throughput
- endothelial cells
- diffusion weighted imaging
- rheumatoid arthritis
- dna methylation
- optical coherence tomography
- public health
- induced apoptosis
- small cell lung cancer
- high resolution
- machine learning
- induced pluripotent stem cells
- mass spectrometry
- computed tomography
- contrast enhanced
- mesenchymal stem cells
- pluripotent stem cells
- climate change
- cell therapy
- big data
- cell proliferation
- cerebral ischemia
- cell death