51 research outputs found
Neurogenesis from Sox2 expressing cells in the adult cerebellar cortex
We identified a rare undifferentiated cell population that is intermingled with the Bergmann glia of the adult murine cerebellar cortex, expresses the stem cell markers Sox2 and Nestin, and lacks markers of glial or neuronal differentiation. Interestingly, such Sox2(+) S100(-) cells of the adult cerebellum expanded after adequate physiological stimuli in mice (exercise), and Sox2(+) precursors acquired positivity for the neuronal marker NeuN over time and integrated into cellular networks. In human patients, SOX2(+) S100(-) cells similarly increased in number after relevant pathological insults (infarcts), suggesting a similar expansion of cells that lack terminal glial differentiation
Rapid detection of 2-hydroxyglutarate in frozen sections of IDH mutant tumors by MALDI-TOF mass spectrometry
All isocitrate dehydrogenase (IDH) mutant solid neoplasms exhibit highly elevated levels of D-2-hydroxyglutarate (D-2HG). Detection of 2HG in tumor tissues currently is performed by gas or liquid chromatography-mass spectrometry (GC- or LC-MS) or biochemical detection. While these methods are highly accurate, a considerable amount of time for tissue preparation and a relatively high amount of tissue is required for testing. We here present a rapid approach to detect 2HG in brain tumor tissue based on matrix-assisted laser desorption ionization - time of flight mass spectrometry (MALDI-TOF). We analyzed 26 brain tumor samples with known IDH1 or IDH2 mutation and compared readouts to those from 28 brain tumor samples of wildtype IDH status. IDH mutant samples exhibited a clear positive signal for 2HG which was not observed in any of the IDH wildtype tumors. Our analytical pipeline allowed for 2HG detection in less than 5 min. Data were validated by determining 2HG levels in all tissues with a biochemical assay. In conclusion, we developed a protocol for rapid detection of 2HG levels and illustrate the possibility to use MALDI-TOF for the detection of metabolites on frozen tissue sections in a diagnostic setting
Accurate calling of KIAA1549‐BRAF fusions from DNA of human brain tumours using methylation array‐based copy number and gene panel sequencing data
A prognostic neural epigenetic signature in high-grade glioma
Neural-tumor interactions drive glioma growth as evidenced in preclinical models, but clinical validation is limited. We present an epigenetically defined neural signature of glioblastoma that independently predicts patients' survival. We use reference signatures of neural cells to deconvolve tumor DNA and classify samples into low- or high-neural tumors. High-neural glioblastomas exhibit hypomethylated CpG sites and upregulation of genes associated with synaptic integration. Single-cell transcriptomic analysis reveals a high abundance of malignant stemcell-like cells in high-neural glioblastoma, primarily of the neural lineage. These cells are further classified as neural-progenitor-cell-like, astrocyte-like and oligodendrocyte-progenitor-like, alongside oligodendrocytes and excitatory neurons. In line with these findings, high-neural glioblastoma cells engender neuron-to-glioma synapse formation in vitro and in vivo and show an unfavorable survival after xenografting. In patients, a high-neural signature is associated with decreased overall and progression-free survival. High-neural tumors also exhibit increased functional connectivity in magnetencephalography and resting-state magnet resonance imaging and can be detected via DNA analytes and brain-derived neurotrophic factor in patients' plasma. The prognostic importance of the neural signature was further validated in patients diagnosed with diffuse midline glioma. Our study presents an epigenetically defined malignant neural signature in high-grade gliomas that is prognostically relevant. High-neural gliomas likely require a maximized surgical resection approach for improved outcomes
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DNA methylation-based classification of central nervous system tumours.
Accurate pathological diagnosis is crucial for optimal management of patients with cancer. For the approximately 100 known tumour types of the central nervous system, standardization of the diagnostic process has been shown to be particularly challenging-with substantial inter-observer variability in the histopathological diagnosis of many tumour types. Here we present a comprehensive approach for the DNA methylation-based classification of central nervous system tumours across all entities and age groups, and demonstrate its application in a routine diagnostic setting. We show that the availability of this method may have a substantial impact on diagnostic precision compared to standard methods, resulting in a change of diagnosis in up to 12% of prospective cases. For broader accessibility, we have designed a free online classifier tool, the use of which does not require any additional onsite data processing. Our results provide a blueprint for the generation of machine-learning-based tumour classifiers across other cancer entities, with the potential to fundamentally transform tumour pathology
Sarcoma classification by DNA methylation profiling
Sarcomas are malignant soft tissue and bone tumours affecting adults, adolescents and children. They represent a morphologically heterogeneous class of tumours and some entities lack defining histopathological features. Therefore, the diagnosis of sarcomas is burdened with a high inter-observer variability and misclassification rate. Here, we demonstrate classification of soft tissue and bone tumours using a machine learning classifier algorithm based on array-generated DNA methylation data. This sarcoma classifier is trained using a dataset of 1077 methylation profiles from comprehensively pre-characterized cases comprising 62 tumour methylation classes constituting a broad range of soft tissue and bone sarcoma subtypes across the entire age spectrum. The performance is validated in a cohort of 428 sarcomatous tumours, of which 322 cases were classified by the sarcoma classifier. Our results demonstrate the potential of the DNA methylation-based sarcoma classification for research and future diagnostic applications
DNA methylation-based classification and grading system for meningioma:a multicentre, retrospective analysis
Two Pituitary Neuroendocrine Tumors (PitNETs) with Very High Proliferation and TP53 Mutation — High-Grade PitNET or PitNEC?
We report two pituitary neuroendocrine tumors (PitNETs) with very high Ki67 labeling indices, many mitoses and TP53 mutation (nearly all tumor cell nuclei were positive for p53). One of the tumors had bone and liver metastases. One was a corticotroph cell tumor; the other was a lactotroph tumor. The classification of these tumors is the subject of this discussion. Traditionally, pituitary carcinomas are only diagnosed by demonstration of metastases according to the 2017 WHO classification. In contrast, neuroendocrine neoplasms of the gastrointestinal tract and pancreas are classified as either well differentiated NETs that are graded as G1, G2, and G3 based on proliferation as determined by Ki67 indices of ≤ 3, 3-20 and > 20%, and/or < 2, 2-20, and > 20 mitoses per 10 high-power field respectively, or as neuroendocrine carcinomas (NECs) that are poorly differentiated neoplasms with mitoses > 20/HPF and/or a Ki67 index > 20%. With the reclassificiation of PitNETs, in our opinion, the adequate term for the well-differentiated corticotroph tumor that we report is a PitNET G3, whereas the undifferentiated prolactin tumor should be classified as PitNEC. This report expands the spectrum of pituitary neuroendocrine neoplasms
Canonical Wnt Signaling Drives Tumor-Like Lesions from Sox2-Positive Precursors of the Murine Olfactory Epithelium.
Canonical Wnt signaling is known to promote proliferation of olfactory stem cells. In order to investigate the effects of a constitutive activation of Wnt signaling in Sox2-positive precursor cells of the olfactory epithelium, we used transgenic mice that allowed an inducible deletion of exon 3 of the Ctnnb1 gene, which is responsible for the phosphorylation and degradation of Ctnnb1 protein. After induction of aberrant Wnt activation by Ctnnb1 deletion at embryonic day 14, such mice developed tumor-like lesions in upper parts of the nasal cavity. We still observed areas of epithelial hyperplasia within the olfactory epithelium following early postnatal Wnt activation, but the olfactory epithelial architecture remained unaffected in most parts when Wnt was activated at postnatal day 21 or later. In summary, our results suggest an age-dependent tumorigenic potential of aberrant Wnt signaling in the olfactory epithelium of mice
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