EpiDiP/NanoDiP: a versatile unsupervised machine learning edge computing platform for epigenomic tumour diagnostics.

DNA methylation analysis based on supervised machine learning algorithms with static reference data, allowing diagnostic tumour typing with unprecedented precision, has quickly become a new standard of care. Whereas genome-wide diagnostic methylation profiling is mostly performed on microarrays, an increasing number of institutions additionally employ nanopore sequencing as a faster alternative. In addition, methylation-specific parallel sequencing can generate methylation and genomic copy number data. Given these diverse approaches to methylation profiling, to date, there is no single tool that allows (1) classification and interpretation of microarray, nanopore and parallel sequencing data, (2) direct control of nanopore sequencers, and (3) the integration of microarray-based methylation reference data. Furthermore, no software capable of entirely running in routine diagnostic laboratory environments lacking high-performance computing and network infrastructure exists. To overcome these shortcomings, we present EpiDiP/NanoDiP as an open-source DNA methylation and copy number profiling suite, which has been benchmarked against an established supervised machine learning approach using in-house routine diagnostics data obtained between 2019 and 2021. Running locally on portable, cost- and energy-saving system-on-chip as well as gpGPU-augmented edge computing devices, NanoDiP works in offline mode, ensuring data privacy. It does not require the rigid training data annotation of supervised approaches. Furthermore, NanoDiP is the core of our public, free-of-charge EpiDiP web service which enables comparative methylation data analysis against an extensive reference data collection. We envision this versatile platform as a useful resource not only for neuropathologists and surgical pathologists but also for the tumour epigenetics research community. In daily diagnostic routine, analysis of native, unfixed biopsies by NanoDiP delivers molecular tumour classification in an intraoperative time frame.

Classification of Brain Tumors by Nanopore Sequencing of Cell-Free DNA from Cerebrospinal Fluid.

BACKGROUND: Molecular brain tumor diagnosis is usually dependent on tissue biopsies or resections. This can pose several risks associated with anesthesia or neurosurgery, especially for lesions in the brain stem or other difficult-to-reach anatomical sites. Apart from initial diagnosis, tumor progression, recurrence, or the acquisition of novel genetic alterations can only be proven by re-biopsies. METHODS: We employed Nanopore sequencing on cell-free DNA (cfDNA) from cerebrospinal fluid (CSF) and analyzed copy number variations (CNV) and global DNA methylation using a random forest classifier. We sequenced 129 samples with sufficient DNA. These samples came from 99 patients and encompassed 22 entities. Results were compared to clinical diagnosis and molecular analysis of tumor tissue, if available. RESULTS: 110/129 samples were technically successful, and 50 of these contained detectable circulating tumor DNA (ctDNA) by CNV or methylation profiling. ctDNA was detected in samples from patients with progressive disease but also from patients without known residual disease. CNV plots showed diagnostic and prognostic alterations, such as C19MC amplifications in embryonal tumors with multilayered rosettes or Chr.1q gains and Chr.6q losses in posterior fossa group A ependymoma, respectively. Most CNV profiles mirrored the profiles of the respective tumor tissue. DNA methylation allowed exact classification of the tumor in 22/110 cases and led to incorrect classification in 2/110 cases. Only 5/50 samples with detected ctDNA contained tumor cells detectable through microscopy. CONCLUSIONS: Our results suggest that Nanopore sequencing data of cfDNA from CSF samples may be a promising approach for initial brain tumor diagnostics and an important tool for disease monitoring.

Molecular refinement of pilocytic astrocytoma in adult patients.

AIM: Pilocytic astrocytomas (PA) in adults are rare and may be challenging to identify based only on histomorphology. Compared to their paediatric counterparts, they are reportedly molecularly more diverse and associated with a worse prognosis. We aimed to describe the characteristics of adult PAs more precisely by comprehensively profiling a series of 79 histologically diagnosed adult cases (≥18 years). METHODS: We performed global DNA methylation profiling and DNA and RNA panel sequencing, and integrated the results with clinical data. We further compared the molecular characteristics of adult and paediatric PAs that had a significant match to one of the established PA methylation classes in the Heidelberg brain tumour classifier. RESULTS: The mean age in our cohort was 33 years, and 43% of the tumours were located supratentorially. Based on methylation profiling, only 39% of the cases received a significant match to a PA methylation class. Sixteen per cent matched a different tumour type and 45% had a Heidelberg classifier score <0.9 with an affiliation to diverse established methylation classes in t-SNE analyses. Although the KIAA1549::BRAF fusion was found in 98% of paediatric PAs, this was true for only 27% of histologically defined and 55% of adult PAs defined by methylation profiling. CONCLUSIONS: A particularly high fraction of adult tumours with histological features of PA do not match current PA methylation classes, indicating ambiguous histology and an urgent need for molecular profiling. Moreover, even in adult PAs with a match to a PA methylation class, the distribution of genetic drivers differs significantly from their paediatric counterparts (p<0.01).

Glioneuronal tumor with ATRX alteration, kinase fusion and anaplastic features (GTAKA): a molecularly distinct brain tumor type with recurrent NTRK gene fusions.

Glioneuronal tumors are a heterogenous group of CNS neoplasms that can be challenging to accurately diagnose. Molecular methods are highly useful in classifying these tumors-distinguishing precise classes from their histological mimics and identifying previously unrecognized types of tumors. Using an unsupervised visualization approach of DNA methylation data, we identified a novel group of tumors (n = 20) that formed a cluster separate from all established CNS tumor types. Molecular analyses revealed ATRX alterations (in 16/16 cases by DNA sequencing and/or immunohistochemistry) as well as potentially targetable gene fusions involving receptor tyrosine-kinases (RTK; mostly NTRK1-3) in all of these tumors (16/16; 100%). In addition, copy number profiling showed homozygous deletions of CDKN2A/B in 55% of cases. Histological and immunohistochemical investigations revealed glioneuronal tumors with isomorphic, round and often condensed nuclei, perinuclear clearing, high mitotic activity and microvascular proliferation. Tumors were mainly located supratentorially (84%) and occurred in patients with a median age of 19 years. Survival data were limited (n = 18) but point towards a more aggressive biology as compared to other glioneuronal tumors (median progression-free survival 12.5 months). Given their molecular characteristics in addition to anaplastic features, we suggest the term glioneuronal tumor with ATRX alteration, kinase fusion and anaplastic features (GTAKA) to describe these tumors. In summary, our findings highlight a novel type of glioneuronal tumor driven by different RTK fusions accompanied by recurrent alterations in ATRX and homozygous deletions of CDKN2A/B. Targeted approaches such as NTRK inhibition might represent a therapeutic option for patients suffering from these tumors.

Robust methylation-based classification of brain tumours using nanopore sequencing.

BACKGROUND: DNA methylation-based classification of cancer provides a comprehensive molecular approach to diagnose tumours. In fact, DNA methylation profiling of human brain tumours already profoundly impacts clinical neuro-oncology. However, current implementation using hybridisation microarrays is time consuming and costly. We recently reported on shallow nanopore whole-genome sequencing for rapid and cost-effective generation of genome-wide 5-methylcytosine profiles as input to supervised classification. Here, we demonstrate that this approach allows us to discriminate a wide spectrum of primary brain tumours. RESULTS: Using public reference data of 82 distinct tumour entities, we performed nanopore genome sequencing on 382 tissue samples covering 46 brain tumour (sub)types. Using bootstrap sampling in a cohort of 55 cases, we found that a minimum set of 1000 random CpG features is sufficient for high-confidence classification by ad hoc random forests. We implemented score recalibration as a confidence measure for interpretation in a clinical context and empirically determined a platform-specific threshold in a randomly sampled discovery cohort (N = 185). Applying this cut-off to an independent validation series (n = 184) yielded 148 classifiable cases (sensitivity 80.4%) and demonstrated 100% specificity. Cross-lab validation demonstrated robustness with concordant results across four laboratories in 10/11 (90.9%) cases. In a prospective benchmarking (N = 15), the median time to results was 21.1 h. CONCLUSIONS: In conclusion, nanopore sequencing allows robust and rapid methylation-based classification across the full spectrum of brain tumours. Platform-specific confidence scores facilitate clinical implementation for which prospective evaluation is warranted and ongoing.

DNA methylation-based classification of sinonasal tumors.

The diagnosis of sinonasal tumors is challenging due to a heterogeneous spectrum of various differential diagnoses as well as poorly defined, disputed entities such as sinonasal undifferentiated carcinomas (SNUCs). In this study, we apply a machine learning algorithm based on DNA methylation patterns to classify sinonasal tumors with clinical-grade reliability. We further show that sinonasal tumors with SNUC morphology are not as undifferentiated as their current terminology suggests but rather reassigned to four distinct molecular classes defined by epigenetic, mutational and proteomic profiles. This includes two classes with neuroendocrine differentiation, characterized by IDH2 or SMARCA4/ARID1A mutations with an overall favorable clinical course, one class composed of highly aggressive SMARCB1-deficient carcinomas and another class with tumors that represent potentially previously misclassified adenoid cystic carcinomas. Our findings can aid in improving the diagnostic classification of sinonasal tumors and could help to change the current perception of SNUCs.

Diagnostic DNA methylome profiling and the WHO 5th edition CNS tumor classification.

The long-awaited 5th edition of the WHO brain tumor classification has put considerable emphasis on the importance of diagnostic DNA methylation profiling. In this article, the authors comparatively discuss selected practical aspects as well as general advantages and limitations of array- versus nanopore sequencing-based approaches to methylome profiling.

High SOX9 Maintains Glioma Stem Cell Activity through a Regulatory Loop Involving STAT3 and PML.

Glioma stem cells (GSCs) are critical targets for glioma therapy. SOX9 is a transcription factor with critical roles during neurodevelopment, particularly within neural stem cells. Previous studies showed that high levels of SOX9 are associated with poor glioma patient survival. SOX9 knockdown impairs GSCs proliferation, confirming its potential as a target for glioma therapy. In this study, we characterized the function of SOX9 directly in patient-derived glioma stem cells. Notably, transcriptome analysis of GSCs with SOX9 knockdown revealed STAT3 and PML as downstream targets. Functional studies demonstrated that SOX9, STAT3, and PML form a regulatory loop that is key for GSC activity and self-renewal. Analysis of glioma clinical biopsies confirmed a positive correlation between SOX9/STAT3/PML and poor patient survival among the cases with the highest SOX9 expression levels. Importantly, direct STAT3 or PML inhibitors reduced the expression of SOX9, STAT3, and PML proteins, which significantly reduced GSCs tumorigenicity. In summary, our study reveals a novel role for SOX9 upstream of STAT3, as a GSC pathway regulator, and presents pharmacological inhibitors of the signaling cascade.

Larotrectinib Response in NTRK3 Fusion-Driven Diffuse High-Grade Glioma.

High-grade glioma (HGG) and glioblastoma are the most common adult malignant brain tumors. The standard treatment consists of surgical resection followed by radiochemotherapy with temozolomide. The prognosis and the therapeutic options of these malignant brain tumors however are limited. Here, we describe a case of a patient with HGG with a previously unknown NTRK3 fusion that showed an extraordinary response to treatment with larotrectinib. This case supports regular testing for NTRK fusion proteins.

Comprehensive profiling of myxopapillary ependymomas identifies a distinct molecular subtype with relapsing disease.

BACKGROUND: Myxopapillary ependymoma (MPE) is a heterogeneous disease regarding histopathology and outcome. The underlying molecular biology is poorly understood, and markers that reliably predict the patients' clinical course are unknown. METHODS: We assembled a cohort of 185 tumors classified as MPE based on DNA methylation. Methylation patterns, copy number profiles, and MGMT promoter methylation were analyzed for all tumors, 106 tumors were evaluated histomorphologically, and RNA sequencing was performed for 37 cases. Based on methylation profiling, we defined two subtypes MPE-A and MPE-B, and explored associations with epidemiological, clinical, pathological, and molecular characteristics of these tumors. RESULTS: MPE-A occurred at a median age of 27 years and were enriched with tumors demonstrating papillary morphology and MGMT promoter hypermethylation. Half of these tumors could not be totally resected, and 85% relapsed within 10 years. Copy number alterations were more common in MPE-A. RNA sequencing revealed an enrichment for extracellular matrix and immune system-related signatures in MPE-A. MPE-B occurred at a median age of 45 years and included many tumors with a histological diagnosis of WHO grade II and tanycytic morphology. Patients within this subtype had a significantly better outcome with a relapse rate of 33% in 10 years (P = 3.4e-06). CONCLUSIONS: We unraveled the morphological and clinical heterogeneity of MPE by identifying two molecularly distinct subtypes. These subtypes significantly differed in progression-free survival and will likely need different protocols for surveillance and treatment.

Methylation and copy number profiling: emerging tools to differentiate osteoblastoma from malignant mimics?

Rearrangements of the transcription factors FOS and FOSB have recently been identified as the genetic driver event underlying osteoid osteoma and osteoblastoma. Nuclear overexpression of FOS and FOSB have since then emerged as a reliable surrogate marker despite limitations in specificity and sensitivity. Indeed, osteosarcoma can infrequently show nuclear FOS expression and a small fraction of osteoblastomas seem to arise independent of FOS/FOSB rearrangements. Acid decalcification and tissue preservation are additional factors that can negatively influence immunohistochemical testing and make diagnostic decision-making challenging in individual cases. Particularly aggressive appearing osteoblastomas, also referred to as epithelioid osteoblastomas, and osteoblastoma-like osteosarcoma can be difficult to distinguish, underlining the need for additional markers to support the diagnosis. Methylation and copy number profiling, a technique well established for the classification of brain tumors, might fill this gap. Here, we set out to comprehensively characterize a series of 77 osteoblastomas by immunohistochemistry, fluorescence in-situ hybridization as well as copy number and methylation profiling and compared our findings to histologic mimics. Our results show that osteoblastomas are uniformly characterized by flat copy number profiles that can add certainty in reaching the correct diagnosis. The methylation cluster formed by osteoblastomas, however, so far lacks specificity and can be misleading in individual cases.

Integrated Molecular-Morphologic Meningioma Classification: A Multicenter Retrospective Analysis, Retrospectively and Prospectively Validated.

PURPOSE: Meningiomas are the most frequent primary intracranial tumors. Patient outcome varies widely from benign to highly aggressive, ultimately fatal courses. Reliable identification of risk of progression for individual patients is of pivotal importance. However, only biomarkers for highly aggressive tumors are established (CDKN2A/B and TERT), whereas no molecularly based stratification exists for the broad spectrum of patients with low- and intermediate-risk meningioma. METHODS: DNA methylation data and copy-number information were generated for 3,031 meningiomas (2,868 patients), and mutation data for 858 samples. DNA methylation subgroups, copy-number variations (CNVs), mutations, and WHO grading were analyzed. Prediction power for outcome was assessed in a retrospective cohort of 514 patients, validated on a retrospective cohort of 184, and on a prospective cohort of 287 multicenter cases. RESULTS: Both CNV- and methylation family-based subgrouping independently resulted in increased prediction accuracy of risk of recurrence compared with the WHO classification (c-indexes WHO 2016, CNV, and methylation family 0.699, 0.706, and 0.721, respectively). Merging all risk stratification approaches into an integrated molecular-morphologic score resulted in further substantial increase in accuracy (c-index 0.744). This integrated score consistently provided superior accuracy in all three cohorts, significantly outperforming WHO grading (c-index difference P = .005). Besides the overall stratification advantage, the integrated score separates more precisely for risk of progression at the diagnostically challenging interface of WHO grade 1 and grade 2 tumors (hazard ratio 4.34 [2.48-7.57] and 3.34 [1.28-8.72] retrospective and prospective validation cohorts, respectively). CONCLUSION: Merging these layers of histologic and molecular data into an integrated, three-tiered score significantly improves the precision in meningioma stratification. Implementation into diagnostic routine informs clinical decision making for patients with meningioma on the basis of robust outcome prediction.

Glioblastomas with primitive neuronal component harbor a distinct methylation and copy-number profile with inactivation of TP53, PTEN, and RB1.

Glioblastoma IDH-wildtype presents with a wide histological spectrum. Some features are so distinctive that they are considered as separate histological variants or patterns for the purpose of classification. However, these usually lack defined (epi-)genetic alterations or profiles correlating with this histology. Here, we describe a molecular subtype with overlap to the unique histological pattern of glioblastoma with primitive neuronal component. Our cohort consists of 63 IDH-wildtype glioblastomas that harbor a characteristic DNA methylation profile. Median age at diagnosis was 59.5 years. Copy-number variations and genetic sequencing revealed frequent alterations in TP53, RB1 and PTEN, with fewer gains of chromosome 7 and homozygous CDKN2A/B deletions than usually described for IDH-wildtype glioblastoma. Gains of chromosome 1 were detected in more than half of the cases. A poorly differentiated phenotype with frequent absence of GFAP expression, high proliferation index and strong staining for p53 and TTF1 often caused misleading histological classification as carcinoma metastasis or primitive neuroectodermal tumor. Clinically, many patients presented with leptomeningeal dissemination and spinal metastasis. Outcome was poor with a median overall survival of only 12 months. Overall, we describe a new molecular subtype of IDH-wildtype glioblastoma with a distinct histological appearance and genetic signature.

Supratentorial ependymoma in childhood: more than just RELA or YAP.

Two distinct genetically defined entities of ependymoma arising in the supratentorial compartment are characterized by the presence of either a C11orf95-RELA or a YAP-MAMLD1 fusion, respectively. There is growing evidence that supratentorial ependymomas without these genetic features exist. In this study, we report on 18 pediatric non-RELA/non-YAP supratentorial ependymomas that were systematically characterized by means of their histology, immunophenotype, genetics, and epigenomics. Comprehensive molecular analyses included high-resolution copy number analysis, methylation profiling, analysis of fusion transcripts by Nanostring technology, and RNA sequencing. Based upon histological and immunohistochemical features two main patterns were identified-RELA-like (n = 9) and tanycytic ependymomas (n = 6). In the RELA-like group histologically assigned to WHO grade III and resembling RELA-fused ependymomas, tumors lacked nuclear expression of p65-RelA as a surrogate marker for a pathological activation of the NF-κB pathway. Three tumors showed alternative C11orf95 fusions to MAML2 or NCOA1. A methylation-based brain tumor classifier assigned two RELA-like tumors to the methylation class "EP, RELA-fusion"; the others demonstrated no significant similarity score. Of the tanycytic group, 5/6 tumors were assigned a WHO grade II. No gene fusions were detected. Methylation profiling did not show any association with an established methylation class. We additionally identified two astroblastoma-like tumors that both presented with chromothripsis of chromosome 22 but lacked MN1 breaks according to FISH analysis. They revealed novel fusion events involving genes in chromosome 22. One further tumor with polyploid cytogenetics was interpreted as PFB ependymoma by the brain tumor methylation classifier but had no relation to the posterior fossa. Clinical follow-up was available for 16/18 patients. Patients with tanycytic and astroblastoma-like tumors had no relapse, while 2 patients with RELA-like ependymomas died. Our data indicate that in addition to ependymomas discovered so far, at least two more supratentorial ependymoma types (RELA-like and tanycytic) exist.

Hunting coronavirus by transmission electron microscopy - a guide to SARS-CoV-2-associated ultrastructural pathology in COVID-19 tissues.

Transmission electron microscopy has become a valuable tool to investigate tissues of COVID-19 patients because it allows visualisation of SARS-CoV-2, but the 'virus-like particles' described in several organs have been highly contested. Because most electron microscopists in pathology are not accustomed to analysing viral particles and subcellular structures, our review aims to discuss the ultrastructural changes associated with SARS-CoV-2 infection and COVID-19 with respect to pathology, virology and electron microscopy. Using micrographs from infected cell cultures and autopsy tissues, we show how coronavirus replication affects ultrastructure and put the morphological findings in the context of viral replication, which induces extensive remodelling of the intracellular membrane systems. Virions assemble by budding into the endoplasmic reticulum-Golgi intermediate complex and are characterised by electron-dense dots of cross-sections of the nucleocapsid inside the viral particles. Physiological mimickers such as multivesicular bodies or coated vesicles serve as perfect decoys. Compared to other in-situ techniques, transmission electron microscopy is the only method to visualise assembled virions in tissues, and will be required to prove SARS-CoV-2 replication outside the respiratory tract. In practice, documenting in tissues the characteristic features seen in infected cell cultures seems to be much more difficult than anticipated. In our view, the hunt for coronavirus by transmission electron microscopy is still on.

Clear cell meningiomas are defined by a highly distinct DNA methylation profile and mutations in SMARCE1.

Clear cell meningioma represents an uncommon variant of meningioma that typically affects children and young adults. Although an enrichment of loss-of-function mutations in the SMARCE1 gene has been reported for this subtype, comprehensive molecular investigations are lacking. Here we describe a molecularly distinct subset of tumors (n = 31), initially identified through genome-wide DNA methylation screening among a cohort of 3093 meningiomas, of which most were diagnosed histologically as clear cell meningioma. This cohort was further supplemented by an additional 11 histologically diagnosed clear cell meningiomas for analysis (n = 42). Targeted DNA sequencing revealed SMARCE1 mutations in 33/34 analyzed samples, accompanied by a nuclear loss of expression determined via immunohistochemistry and a decreased SMARCE1 transcript expression in the tumor cells. Analysis of time to progression or recurrence of patients within the clear cell meningioma group (n = 14) in comparison to those with meningioma WHO grade 2 (n = 220) revealed a similar outcome and support the assignment of WHO grade 2 to these tumors. Our findings indicate the existence of a highly distinct epigenetic signature of clear cell meningiomas, separate from all other variants of meningiomas, with recurrent mutations in the SMARCE1 gene. This suggests that these tumors may arise from a different precursor cell population than the broad spectrum of the other meningioma subtypes.