Abstract Interactions of neural cells with glioma cells drive tumor growth. In this study, we identified an epigenetically-defined, malignant neural signature of IDH-wildtype glioblastoma (GBM) that significantly influenced patients’ outcome. We used DNA methylation-based reference signatures of neural cells to deconvolve 1.058 primary patient GBM samples. Samples were classified based on the neural reference signature and annotated as low or high neural GBM. A high neural GBM was linked to hypomethylation of CpG sites associated with invasiveness, neuron-to-glioma-interactions, and transsynaptic signaling. Through spatially resolved, single cell transcriptomic and proteomic profiling, we discovered a correlation between the high neural signature and the upregulation of early development programs in OPC and NPC-like cells. These traits were accompanied by diminished immune infiltration and immunological response, further highlighting the distinctive neural-like nature of GBM. High neural GBM demonstrated increased connectivity as evidenced by magnetoencephalography and resting state magnet resonance imaging. Spatiotemporal tumor sampling showed a homogeneous and stable neural signature in newly diagnosed and recurrent GBM. In newly diagnosed GBM, a high neural signature correlated with decreased survival in 306 patients (median OS 15.0 versus 20.0 months, p< 0.001). Patient-derived xenograft models corroborated the aggressive nature of high neural GBM, showing a significantly reduced median OS of 58 days compared to 73 days (p< 0.01). These high neural GBM xenografts also exhibited an elevated tumor burden and an increase in neuron-glioma synapse formation. Consideration of the extent of resection showed a dependency on the neural subgroup as high neural GBM had an increased benefit from a complete contrast enhancing tumor removal when compared to low neural GBM. As a preoperative biomarker, the concentration of BDNF was increased in serum of high neural GBM patients (p < 0.01). Overall, we present an epigenetically-defined malignant neural signature in GBM that is associated with an unfavorable patient survival.
Abstract Pituitary neuroendocrine tumors (PitNETs) are classified according to cell lineage, which requires immunohistochemistry for adenohypophyseal hormones and the transcription factors (TFs) PIT1, SF1, and TPIT. According to the current WHO 2022 classification, PitNETs with co-expression of multiple TFs are termed “plurihormonal”. Previously, PIT1/SF1 co-expression was prevailingly reported in PitNETs, which otherwise correspond to the somatotroph lineage. However, little is known about such tumors and the WHO classification has not recognized their significance. We compiled an in-house case series of 100 tumors, previously diagnosed as somatotroph PitNETs. Following TF staining, histopathological features associated with PIT1/SF1 co-expression were assessed. Integration of in-house and publicly available sample data allowed for a meta-analysis of SF1-associated clinicopathological and molecular features across a total of 270 somatotroph PitNETs. The majority (74%, 52/70) of our densely granulated somatotroph PitNETs (DGST) unequivocally co-expressed PIT1 and SF1 (DGST-PIT1/SF1). None (0%, 0/30) of our sparsely granulated somatotroph PitNETs (SGST) stained positive for SF1 (SGST-PIT1). Among DGST, PIT1/SF1 co-expression was significantly associated with scarce FSH/LH expression and fewer fibrous bodies compared to DGST-PIT1. Integrated molecular analyses including publicly available samples confirmed that DGST-PIT1/SF1, DGST-PIT1 and SGST-PIT1 represent distinct tumor subtypes. Clinicopathological meta-analyses indicated that DGST-PIT1 respond more favorably towards treatment with somatostatin analogs compared to DGST-PIT1/SF1, while both these subtypes show an overall less aggressive clinical course than SGST-PIT1. In this study, we spotlight that DGST with co-expression of PIT1 and SF1 represent a common, yet underrecognized, distinct PitNET subtype. Our study questions the rationale of generally classifying such tumors as “plurihormonal”, and calls for a refinement of the WHO classification. We propose the term “somatogonadotroph PitNET”.
Abstract Based on DNA‐methylation, ependymomas growing in the spinal cord comprise two major molecular types termed spinal (SP‐EPN) and myxopapillary ependymomas (MPE(‐A/B)), which differ with respect to their clinical features and prognosis. Due to the existing discrepancy between histomorphogical diagnoses and classification using methylation data, we asked whether deep neural networks can predict the DNA methylation class of spinal cord ependymomas from hematoxylin and eosin stained whole‐slide images. Using explainable AI, we further aimed to prospectively improve the consistency of histology‐based diagnoses with DNA methylation profiling by identifying and quantifying distinct morphological patterns of these molecular ependymoma types. We assembled a case series of 139 molecularly characterized spinal cord ependymomas ( n MPE = 84, n SP‐EPN = 55). Self‐supervised and weakly‐supervised neural networks were used for classification. We employed attention analysis and supervised machine‐learning methods for the discovery and quantification of morphological features and their correlation to the diagnoses of experienced neuropathologists. Our best performing model predicted the DNA methylation class with 98% test accuracy and used self‐supervised learning to outperform pretrained encoder‐networks (86% test accuracy). In contrast, the diagnoses of neuropathologists matched the DNA methylation class in only 83% of cases. Domain‐adaptation techniques improved model generalization to an external validation cohort by up to 22%. Statistically significant morphological features were identified per molecular type and quantitatively correlated to human diagnoses. The approach was extended to recently defined subtypes of myxopapillary ependymomas (MPE‐(A/B), 80% test accuracy). In summary, we demonstrated the accurate prediction of the DNA methylation class of spinal cord ependymomas (SP‐EPN, MPE(‐A/B)) using hematoxylin and eosin stained whole‐slide images. Our approach may prospectively serve as a supplementary resource for integrated diagnostics and may even help to establish a standardized, high‐quality level of histology‐based diagnostics across institutions—in particular in low‐income countries, where expensive DNA‐methylation analyses may not be readily available.
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Abstract Multiple recent publications have described a highly aggressive subgroup of pediatric glioblastoma, which is clearly separable from other pediatric and adult glioblastoma based on its DNA methylation profile (GBM MYCN). These tumors almost exclusively occur in children and have a median overall survival of only 14 months. Many tumors in this group are driven by MYCN amplifications and harbor TP53 mutations. Otherwise, information about these tumors are still sparse and treatment is ineffective and causes severe side effects in many cases. In order to further investigate the biology and treatment options of these tumors, preclinical models are urgently needed. Here, we describe the generation of hGFAP-cre::TP53Fl/Fl::lsl-MYCN mice, which carry a loss of TP53 and show aberrant MYCN expression in neural precursors of the central nervous system. These animals develop large forebrain tumors within the first 80 days of life with 100 % penetrance. These tumors resemble human GBM MYCN tumors by histology, global gene expression, and DNA methylation. In order to understand the developmental biology and intratumoral heterogeneity, we employed single cell RNA sequencing (scRNAseq) to the murine tumors with first results indicating a resemblance of tumor cells to committed oligodendrocyte precursors. We further show that both murine and human tumor cells are sensitive to AURKA inhibition in vitro, suggesting a potential new therapeutic option for improved patient care. We believe that further characterization and utilization of the model will pave the way to improved treatment strategies for patients with these highly aggressive tumors.
Experimental studies were made with continuous hemofiltration treatment for bilaterally nephrectomized rats and initial observations regarding the effects of such treatment on leukocyte and thrombocyte counts are reported. Hemofiltration of unanesthetized rats able to move freely within their cage could be continued for up to 30 h using a pump-driven ECC system. Blood parameters recorded during this treatment indicate that the detoxification was effective. In another series of experiments the water and electrolyte reabsorption capacity of the colon ascendens of healthy rats was tested by continuously supplying NaCl solution into the colon via a fistula. A large proportion, if not all, of the hemofiltrate can be discharged into the colon without diarrhoea. A final series of experiments showed that the three-stage operation (implantation of permanent catheters, connection of a permanent intestinal fistula and bilateral nephrectomy) is possible with the rat.
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.
