Ultra-fast deep-learned CNS tumour classification during surgery.

Central nervous system tumours represent one of the most lethal cancer types, particularly among children1. Primary treatment includes neurosurgical resection of the tumour, in which a delicate balance must be struck between maximizing the extent of resection and minimizing risk of neurological damage and comorbidity2,3. However, surgeons have limited knowledge of the precise tumour type prior to surgery. Current standard practice relies on preoperative imaging and intraoperative histological analysis, but these are not always conclusive and occasionally wrong. Using rapid nanopore sequencing, a sparse methylation profile can be obtained during surgery4. Here we developed Sturgeon, a patient-agnostic transfer-learned neural network, to enable molecular subclassification of central nervous system tumours based on such sparse profiles. Sturgeon delivered an accurate diagnosis within 40 minutes after starting sequencing in 45 out of 50 retrospectively sequenced samples (abstaining from diagnosis of the other 5 samples). Furthermore, we demonstrated its applicability in real time during 25 surgeries, achieving a diagnostic turnaround time of less than 90 min. Of these, 18 (72%) diagnoses were correct and 7 did not reach the required confidence threshold. We conclude that machine-learned diagnosis based on low-cost intraoperative sequencing can assist neurosurgical decision-making, potentially preventing neurological comorbidity and avoiding additional surgeries.

Medulloblastoma in adults: evaluation of the Dutch society for neuro-oncology treatment protocol.

PURPOSE: Medulloblastoma is a rare tumor in adults. The objective of this nationwide, multicenter study was to evaluate the toxicity and efficacy of the Dutch treatment protocol for adult medulloblastoma patients. METHODS: Adult medulloblastoma patients diagnosed between 2010 and 2018 were identified in the Dutch rare tumors registry or nationwide pathology database. Patients with intention to treat according to the national treatment protocol were included. Risk stratification was performed based on residual disease, histological subtype and extent of disease. All patients received postoperative radiotherapy [craniospinal axis 36 Gy/fossa posterior boost 19.8 Gy (14.4 Gy in case of metastases)]. High-risk patients received additional neoadjuvant (carboplatin-etoposide), concomitant (vincristine) and adjuvant chemotherapy (carboplatin-vincristine-cyclophosphamide) as far as feasible by toxicity. Methylation profiling, and additional next-generation sequencing in case of SHH-activated medulloblastomas, were performed. RESULTS: Forty-seven medulloblastoma patients were identified, of whom 32 were treated according to the protocol. Clinical information and tumor material was available for 28 and 20 patients, respectively. The histological variants were mainly classic (43%) and desmoplastic medulloblastoma (36%). Sixteen patients (57%) were considered standard-risk and 60% were SHH-activated medulloblastomas. Considerable treatment reductions and delays in treatment occurred due to especially hematological and neurotoxicity. Only one high-risk patient could complete all chemotherapy courses. 5-years progression-free survival (PFS) and overall survival (OS) for standard-risk patients appeared worse than for high-risk patients (PFS 69% vs. 90%, OS 81% vs. 90% respectively), although this wasn't statistically significant. CONCLUSION: Combined chemo-radiotherapy is a toxic regimen for adult medulloblastoma patients that may result in improved survival.

Brain tumour diagnostics using a DNA methylation-based classifier as a diagnostic support tool.

AIMS: Methylation profiling (MP) is increasingly incorporated in the diagnostic process of central nervous system (CNS) tumours at our centres in The Netherlands and Scandinavia. We aimed to identify the benefits and challenges of MP as a support tool for CNS tumour diagnostics. METHODS: About 502 CNS tumour samples were analysed using (850 k) MP. Profiles were matched with the DKFZ/Heidelberg CNS Tumour Classifier. For each case, the final pathological diagnosis was compared to the diagnosis before MP. RESULTS: In 54.4% (273/502) of all analysed cases, the suggested methylation class (calibrated score ≥0.9) corresponded with the initial pathological diagnosis. The diagnosis of 24.5% of these cases (67/273) was more refined after incorporation of the MP result. In 9.8% of cases (49/502), the MP result led to a new diagnosis, resulting in an altered WHO grade in 71.4% of these cases (35/49). In 1% of cases (5/502), the suggested class based on MP was initially disregarded/interpreted as misleading, but in retrospect, the MP result predicted the right diagnosis for three of these cases. In six cases, the suggested class was interpreted as 'discrepant but noncontributory'. The remaining 33.7% of cases (169/502) had a calibrated score <0.9, including 7.8% (39/502) for which no class indication was given at all (calibrated score <0.3). CONCLUSIONS: MP is a powerful tool to confirm and fine-tune the pathological diagnosis of CNS tumours, and to avoid misdiagnoses. However, it is crucial to interpret the results in the context of clinical, radiological, histopathological and other molecular information.

Diffuse glioneuronal tumour with oligodendroglioma-like features and nuclear clusters (DGONC) - a molecularly defined glioneuronal CNS tumour class displaying recurrent monosomy 14.

AIMS: DNA methylation-based central nervous system (CNS) tumour classification has identified numerous molecularly distinct tumour types, and clinically relevant subgroups among known CNS tumour entities that were previously thought to represent homogeneous diseases. Our study aimed at characterizing a novel, molecularly defined variant of glioneuronal CNS tumour. PATIENTS AND METHODS: DNA methylation profiling was performed using the Infinium MethylationEPIC or 450 k BeadChip arrays (Illumina) and analysed using the 'conumee' package in R computing environment. Additional gene panel sequencing was also performed. Tumour samples were collected at the German Cancer Research Centre (DKFZ) and provided by multinational collaborators. Histological sections were also collected and independently reviewed. RESULTS: Genome-wide DNA methylation data from >25 000 CNS tumours were screened for clusters separated from established DNA methylation classes, revealing a novel group comprising 31 tumours, mainly found in paediatric patients. This DNA methylation-defined variant of low-grade CNS tumours with glioneuronal differentiation displays recurrent monosomy 14, nuclear clusters within a morphology that is otherwise reminiscent of oligodendroglioma and other established entities with clear cell histology, and a lack of genetic alterations commonly observed in other (paediatric) glioneuronal entities. CONCLUSIONS: DNA methylation-based tumour classification is an objective method of assessing tumour origins, which may aid in diagnosis, especially for atypical cases. With increasing sample size, methylation analysis allows for the identification of rare, putative new tumour entities, which are currently not recognized by the WHO classification. Our study revealed the existence of a DNA methylation-defined class of low-grade glioneuronal tumours with recurrent monosomy 14, oligodendroglioma-like features and nuclear clusters.

Molecular pathology of tumors of the central nervous system.

Since the update of the 4th edition of the WHO Classification of Central Nervous System (CNS) Tumors published in 2016, particular molecular characteristics are part of the definition of a subset of these neoplasms. This combined 'histo-molecular' approach allows for a much more precise diagnosis of especially diffuse gliomas and embryonal CNS tumors. This review provides an update of the most important diagnostic and prognostic markers for state-of-the-art diagnosis of primary CNS tumors. Defining molecular markers for diffuse gliomas are IDH1/IDH2 mutations, 1p/19q codeletion and mutations in histone H3 genes. Medulloblastomas, the most frequent embryonal CNS tumors, are divided into four molecularly defined groups according to the WHO 2016 Classification: wingless/integrated (WNT) signaling pathway activated, sonic hedgehog (SHH) signaling pathway activated and tumor protein p53 gene (TP53)-mutant, SHH-activated and TP53-wildtype, and non-WNT/non-SHH-activated. Molecular characteristics are also important for the diagnosis of several other CNS tumors, such as RELA fusion-positive subtype of ependymoma, atypical teratoid rhabdoid tumor (AT/RT), embryonal tumor with multilayered rosettes, and solitary fibrous tumor/hemangiopericytoma. Immunohistochemistry is a helpful alternative for further molecular characterization of several of these tumors. Additionally, genome-wide methylation profiling is a very promising new tool in CNS tumor diagnostics. Much progress has thus been made by translating the most relevant molecular knowledge into a more precise clinical diagnosis of CNS tumors. Hopefully, this will enable more specific and more effective therapeutic approaches for the patients suffering from these tumors.

WHO 2016 Classification of gliomas.

Gliomas are the most frequent intrinsic tumours of the central nervous system and encompass two principle subgroups: diffuse gliomas and gliomas showing a more circumscribed growth pattern ('nondiffuse gliomas'). In the revised fourth edition of the WHO Classification of CNS tumours published in 2016, classification of especially diffuse gliomas has fundamentally changed: for the first time, a large subset of these tumours is now defined based on presence/absence of IDH mutation and 1p/19q codeletion. Following this approach, the diagnosis of (anaplastic) oligoastrocytoma can be expected to largely disappear. Furthermore, in the WHO 2016 Classification gliomatosis cerebri is not an entity anymore but is now considered as a growth pattern. The most important changes in the very diverse group of 'nondiffuse' gliomas and neuronal-glial tumours are the introduction of anaplastic pleomorphic xanthoastrocytoma, of diffuse leptomeningeal glioneuronal tumour and of RELA fusion-positive ependymoma as entities. In the last part of this review, after very briefly touching upon classification of neuronal, choroid plexus and pineal region tumours, some practical implications and challenges associated with the WHO 2016 Classification of gliomas are discussed.

Overcoming the blood-brain tumor barrier for effective glioblastoma treatment.

Gliomas are the most common primary brain tumors. Particularly in adult patients, the vast majority of gliomas belongs to the heterogeneous group of diffuse gliomas, i.e. glial tumors characterized by diffuse infiltrative growth in the preexistent brain tissue. Unfortunately, glioblastoma, the most aggressive (WHO grade IV) diffuse glioma is also by far the most frequent one. After standard treatment, the 2-year overall survival of glioblastoma patients is approximately only 25%. Advanced knowledge in the molecular pathology underlying malignant transformation has offered new handles and better treatments for several cancer types. Unfortunately, glioblastoma multiforme (GBM) patients have not yet profited as although numerous experimental drugs have been tested in clinical trials, all failed miserably. This grim prognosis for GBM is at least partly due to the lack of successful drug delivery across the blood-brain tumor barrier (BBTB). The human brain comprises over 100 billion capillaries with a total length of 400 miles, a total surface area of 20 m(2) and a median inter-capillary distance of about 50 µm, making it the best perfused organ in the body. The BBTB encompasses existing and newly formed blood vessels that contribute to the delivery of nutrients and oxygen to the tumor and facilitate glioma cell migration to other parts of the brain. The high metabolic demands of high-grade glioma create hypoxic areas that trigger increased expression of VEGF and angiogenesis, leading to the formation of abnormal vessels and a dysfunctional BBTB. Even though the BBTB is considered 'leaky' in the core part of glioblastomas, in large parts of glioblastomas and, even more so, in lower grade diffuse gliomas the BBTB more closely resembles the intact blood-brain barrier (BBB) and prevents efficient passage of cancer therapeutics, including small molecules and antibodies. Thus, many drugs can still be blocked from reaching the many infiltrative glioblastoma cells that demonstrate 'within-organ-metastasis' away from the core part to brain areas displaying a more organized and less leaky BBTB. Hence, drug delivery in glioblastoma deserves explicit attention as otherwise new experimental therapies will continue to fail. In the current review we highlight different aspects of the BBTB in glioma patients and preclinical models and discuss the advantages and drawbacks of drug delivery approaches for the treatment of glioma patients. We provide an overview on methods to overcome the BBTB, including osmotic blood-brain barrier disruption (BBBD), bradykinin receptor-mediated BBTB opening, inhibition of multidrug efflux transporters, receptor-mediated transport systems and physiological circumvention of the BBTB. While our knowledge about the molecular biology of glioma cells is rapidly expanding and is, to some extent, already assisting us in the design of tumor-tailored therapeutics, we are still struggling to develop modalities to expose the entire tumor to such therapeutics at pharmacologically meaningful quantities. Therefore, we must expand our knowledge about the fundamentals of the BBTB as a step toward the design of practical and safe devices and approaches for enhanced drug delivery into the diseased brain area.