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

Diffusion Weighted Imaging in Gliomas: A Histogram-Based Approach for Tumor Characterization

(1) Background: Astrocytic gliomas present overlapping appearances in conventional MRI. Supplementary techniques are necessary to improve preoperative diagnostics. Quantitative DWI via the computation of apparent diffusion coefficient (ADC) histograms has proven valuable for tumor characterization and prognosis in this regard. Thus, this study aimed to investigate (I) the potential of ADC histogram analysis (HA) for distinguishing low-grade gliomas (LGG) and high-grade gliomas (HGG) and (II) whether those parameters are associated with Ki-67 immunolabelling, the isocitrate-dehydrogenase-1 (IDH1) mutation profile and the methylguanine-DNA-methyl-transferase (MGMT) promoter methylation profile; (2) Methods: The ADC-histograms of 82 gliomas were computed. Statistical analysis was performed to elucidate associations between histogram features and WHO grade, Ki-67 immunolabelling, IDH1 and MGMT profile; (3) Results: Minimum, lower percentiles (10th and 25th), median, modus and entropy of the ADC histogram were significantly lower in HGG. Significant differences between IDH1-mutated and IDH1-wildtype gliomas were revealed for maximum, lower percentiles, modus, standard deviation (SD), entropy and skewness. No differences were found concerning the MGMT status. Significant correlations with Ki-67 immunolabelling were demonstrated for minimum, maximum, lower percentiles, median, modus, SD and skewness; (4) Conclusions: ADC HA facilitates non-invasive prediction of the WHO grade, tumor-proliferation rate and clinically significant mutations in case of astrocytic gliomas

Histogram Profiling of Postcontrast T1-Weighted MRI Gives Valuable Insights into Tumor Biology and Enables Prediction of Growth Kinetics and Prognosis in Meningiomas

BACKGROUND: Meningiomas are the most frequently diagnosed intracranial masses, oftentimes requiring surgery. Especially procedure-related morbidity can be substantial, particularly in elderly patients. Hence, reliable imaging modalities enabling pretherapeutic prediction of tumor grade, growth kinetic, realistic prognosis, and—as a consequence—necessity of surgery are of great value. In this context, a promising diagnostic approach is advanced analysis of magnetic resonance imaging data. Therefore, our study investigated whether histogram profiling of routinely acquired postcontrast T1-weighted images is capable of separating low-grade from high-grade lesions and whether histogram parameters reflect Ki-67 expression in meningiomas. MATERIAL AND METHODS: Pretreatment T1-weighted postcontrast volumes of 44 meningioma patients were used for signal intensity histogram profiling. WHO grade, tumor volume, and Ki-67 expression were evaluated. Comparative and correlative statistics investigating the association between histogram profile parameters and neuropathology were performed. RESULTS: None of the investigated histogram parameters revealed significant differences between low-grade and high-grade meningiomas. However, significant correlations were identified between Ki-67 and the histogram parameters skewness and entropy as well as between entropy and tumor volume. CONCLUSIONS: Contrary to previously reported findings, pretherapeutic postcontrast T1-weighted images can be used to predict growth kinetics in meningiomas if whole tumor histogram analysis is employed. However, no differences between distinct WHO grades were identifiable in out cohort. As a consequence, histogram analysis of postcontrast T1-weighted images is a promising approach to obtain quantitative in vivo biomarkers reflecting the proliferative potential in meningiomas

Papillary tumor of the pineal region : A distinct molecular entity

Papillary tumor of the pineal region (PTPR) is a neuroepithelial brain tumor, which might pose diagnostic difficulties and recurs often. Little is known about underlying molecular alterations. We therefore investigated chromosomal copy number alterations, DNA methylation patterns and mRNA expression profiles in a series of 24 PTPRs. Losses of chromosome 10 were identified in all 13 PTPRs examined. Losses of chromosomes 3 and 22q (54%) as well as gains of chromosomes 8p (62%) and 12 (46%) were also common. DNA methylation profiling using Illumina 450k arrays reliably distinguished PTPR from ependymomas and pineal parenchymal tumors of intermediate differentiation. PTPR could be divided into two subgroups based on methylation pattern, PTPR group 2 showing higher global methylation and a tendency toward shorter progression-free survival (P = 0.06). Genes overexpressed in PTPR as compared with ependymal tumors included SPDEF, known to be expressed in the rodent subcommissural organ. Notable SPDEF protein expression was encountered in 15/19 PTPRs as compared with only 2/36 ependymal tumors, 2/19 choroid plexus tumors and 0/23 samples of other central nervous system (CNS) tumor entities. In conclusion, PTPRs show typical chromosomal alterations as well as distinct DNA methylation and expression profiles, which might serve as useful diagnostic tools

Melanotic tumors of the nervous system are characterized by distinct mutational, chromosomal and epigenomic profiles.

Melanotic tumors of the nervous system show overlapping histological characteristics but differ substantially in their biological behavior. In order to achieve a better delineation of such tumors, we performed an in-depth molecular characterization. Eighteen melanocytomas, 12 melanomas, and 14 melanotic and 14 conventional schwannomas (control group) were investigated for methylome patterns (450k array), gene mutations associated with melanotic tumors and copy number variants (CNVs). The methylome fingerprints assigned tumors to entity-specific groups. Methylation groups also showed a substantial overlap with histology-based diagnosis suggesting that they represent true biological entities. On the molecular level, melanotic schwannomas were characterized by a complex karyotype with recurrent monosomy of chromosome 22q and variable whole chromosomal gains and recurrent losses commonly involving chromosomes 1, 17p and 21. Melanocytomas carried GNAQ/11 mutations and presented with CNV involving chromosomes 3 and 6. Melanomas were frequently mutated in the TERT promoter, harbored additional oncogene mutations and showed recurrent chromosomal losses involving chromosomes 9, 10 and 6q, as well as gains of 22q. Together, melanotic nervous system tumors have several distinct mutational and chromosomal alterations and can reliably be distinguished by methylome profiling

GOPC:ROS1 and other ROS1 fusions represent a rare but recurrent drug target in a variety of glioma types

The genetic basis of brain tumor development is poorly understood. Here, leukocyte DNA of 21 patients from 15 families with ≥ 2 glioma cases each was analyzed by whole-genome or targeted sequencing. As a result, we identified two families with rare germline variants, p.(A592T) or p.(A817V), in the E-cadherin gene CDH1 that co-segregate with the tumor phenotype, consisting primarily of oligodendrogliomas, WHO grade II/III, IDH-mutant, 1p/19q-codeleted (ODs). Rare CDH1 variants, previously shown to predispose to gastric and breast cancer, were significantly overrepresented in these glioma families (13.3%) versus controls (1.7%). In 68 individuals from 28 gastric cancer families with pathogenic CDH1 germline variants, brain tumors, including a pituitary adenoma, were observed in three cases (4.4%), a significantly higher prevalence than in the general population (0.2%). Furthermore, rare CDH1 variants were identified in tumor DNA of 6/99 (6%) ODs. CDH1 expression was detected in undifferentiated and differentiating oligodendroglial cells isolated from rat brain. Functional studies using CRISPR/Cas9-mediated knock-in or stably transfected cell models demonstrated that the identified CDH1 germline variants affect cell membrane expression, cell migration and aggregation. E-cadherin ectodomain containing variant p.(A592T) had an increased intramolecular flexibility in a molecular dynamics simulation model. E-cadherin harboring intracellular variant p.(A817V) showed reduced β-catenin binding resulting in increased cytosolic and nuclear β-catenin levels reverted by treatment with the MAPK interacting serine/threonine kinase 1 inhibitor CGP 57380. Our data provide evidence for a role of deactivating CDH1 variants in the risk and tumorigenesis of neuroepithelial and epithelial brain tumors, particularly ODs, possibly via WNT/β-catenin signaling

FGFR1:TACC1 fusion is a frequent event in molecularly defined extraventricular neurocytoma

Extraventricular neurocytoma (EVN) is a rare primary brain tumor occurring in brain parenchyma outside the ventricular system. Histopathological characteristics resemble those of central neurocytoma but exhibit a wider morphologic spectrum. Accurate diagnosis of these histologically heterogeneous tumors is often challenging because of the overlapping morphological features and the lack of defining molecular markers. Here, we explored the molecular landscape of 40 tumors diagnosed histologically as EVN by investigating copy number profiles and DNA methylation array data. DNA methylation profiles were compared with those of relevant differential diagnoses of EVN and with a broader spectrum of diverse brain tumor entities. Based on this, our tumor cohort segregated into different groups. While a large fraction (n = 22) formed a separate epigenetic group clearly distinct from established DNA methylation profiles of other entities, a subset (n = 14) of histologically diagnosed EVN grouped with clusters of other defined entities. Three cases formed a small group close to but separated from the epigenetically distinct EVN cases, and one sample clustered with non-neoplastic brain tissue. Four additional samples originally diagnosed otherwise were found to molecularly resemble EVN. Thus, our results highlight a distinct DNA methylation pattern for the majority of tumors diagnosed as EVN, but also indicate that approximately one third of morphological diagnoses of EVN epigenetically correspond to other brain tumor entities. Copy number analysis and confirmation through RNA sequencing revealed FGFR1-TACC1 fusion as a distinctive, recurrent feature within the EVN methylation group (60%), in addition to a small number of other FGFR rearrangements (13%). In conclusion, our data demonstrate a specific epigenetic signature of EVN suitable for characterization of these tumors as a molecularly distinct entity, and reveal a high frequency of potentially druggable FGFR pathway activation in this tumor group

Anaplastic astrocytoma with piloid features, a novel molecular class of IDH wildtype glioma with recurrent MAPK pathway, CDKN2A/B and ATRX alterations.

Tumors with histological features of pilocytic astrocytoma (PA), but with increased mitotic activity and additional high-grade features (particularly microvascular proliferation and palisading necrosis) have often been designated anaplastic pilocytic astrocytomas. The status of these tumors as a separate entity has not yet been conclusively demonstrated and molecular features have only been partially characterized. We performed DNA methylation profiling of 102 histologically defined anaplastic pilocytic astrocytomas. T-distributed stochastic neighbor-embedding (t-SNE) and hierarchical clustering analysis of these 102 cases against 158 reference cases from 12 glioma reference classes revealed that a subset of 83 of these tumors share a common DNA methylation profile that is distinct from the reference classes. These 83 tumors were thus denominated DNA methylation class anaplastic astrocytoma with piloid features (MC AAP). The 19 remaining tumors were distributed amongst the reference classes, with additional testing confirming the molecular diagnosis in most cases. Median age of patients with MC AAP was 41.5 years. The most frequent localization was the posterior fossa (74%). Deletions of CDKN2A/B (66/83, 80%), MAPK pathway gene alterations (49/65, 75%, most frequently affecting NF1, followed by BRAF and FGFR1) and mutations of ATRX or loss of ATRX expression (33/74, 45%) were the most common molecular alterations. All tumors were IDH1/2 wildtype. The MGMT promoter was methylated in 38/83 tumors (45%). Outcome analysis confirmed an unfavorable clinical course in comparison to PA, but better than IDH wildtype glioblastoma. In conclusion, we show that a subset of histologically defined anaplastic pilocytic astrocytomas forms a separate DNA methylation cluster, harbors recurrent alterations in MAPK pathway genes in combination with alterations of CDKN2A/B and ATRX, affects patients who are on average older than those diagnosed with PA and has an intermediate clinical outcome