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Fabry disease is a rare monogenetic, X-linked lysosomal storage disorder with neuropathic pain as one characteristic symptom. Impairment of the enzyme alpha-galactosidase A leads to an accumulation of globotriaosylceramide in the dorsal root ganglia. Here, we investigate novel dorsal root ganglia MR imaging biomarkers and their association with Fabry genotype and pain phenotype. In this prospective study, 89 Fabry patients were examined using a standardized 3â T MRI protocol of the dorsal root ganglia. Fabry pain was assessed through a validated Fabry pain questionnaire. The genotype was determined by diagnostic sequencing of the alpha-galactosidase A gene. MR imaging end-points were dorsal root ganglia volume by voxel-wise morphometric analysis and dorsal root ganglia T2 signal. Reference groups included 55 healthy subjects and Fabry patients of different genotype categories without Fabry pain. In patients with Fabry pain, T2 signal of the dorsal root ganglia was increased by +39.2% compared to healthy controls (P = 0.001) and by +29.4% compared to painless Fabry disease (P = 0.017). This effect was pronounced in hemizygous males (+40.7% compared to healthy; P = 0.008 and +29.1% compared to painless; P = 0.032) and was consistently observed across the genotype spectrum of nonsense (+38.1% compared to healthy, P < 0.001) and missense mutations (+39.2% compared to healthy; P = 0.009). T2 signal of dorsal root ganglia and globotriaosylsphingosine levels were the only independent predictors of Fabry pain (P = 0.047; P = 0.002). Volume of dorsal root ganglia was enlarged by +46.0% in Fabry males in the nonsense compared to missense genotype category (P = 0.005) and by +34.5% compared to healthy controls (P = 0.034). In painful Fabry disease, MRI T2 signal of dorsal root ganglia is increased across different genotypes. Dorsal root ganglion MRI T2 signal as a novel in vivo imaging biomarker may help to better understand whether Fabry pain is modulated or even caused by dorsal root ganglion pathology.
RESUMO
An amendment to this paper has been published and can be accessed via a link at the top of the paper.
RESUMO
Many cellular models aimed at elucidating cancer biology do not recapitulate pathobiology including tumor heterogeneity, an inherent feature of cancer that underlies treatment resistance. Here we introduce a cancer modeling paradigm using genetically engineered human pluripotent stem cells (hiPSCs) that captures authentic cancer pathobiology. Orthotopic engraftment of the neural progenitor cells derived from hiPSCs that have been genome-edited to contain tumor-associated genetic driver mutations revealed by The Cancer Genome Atlas project for glioblastoma (GBM) results in formation of high-grade gliomas. Similar to patient-derived GBM, these models harbor inter-tumor heterogeneity resembling different GBM molecular subtypes, intra-tumor heterogeneity, and extrachromosomal DNA amplification. Re-engraftment of these primary tumor neurospheres generates secondary tumors with features characteristic of patient samples and present mutation-dependent patterns of tumor evolution. These cancer avatar models provide a platform for comprehensive longitudinal assessment of human tumor development as governed by molecular subtype mutations and lineage-restricted differentiation.
