Conumee 2.0: enhanced copy-number variation analysis from DNA methylation arrays for humans and mice.

MOTIVATION: Copy-number variations (CNVs) are common genetic alterations in cancer and their detection may impact tumor classification and therapeutic decisions. However, detection of clinically relevant large and focal CNVs remains challenging when sample material or resources are limited. This has motivated us to create a software tool to infer CNVs from DNA methylation arrays which are often generated as part of clinical routines and in research settings. RESULTS: We present our R package, conumee 2.0, that combines tangent normalization, an adjustable genomic binning heuristic, and weighted circular binary segmentation to utilize DNA methylation arrays for CNV analysis and mitigate technical biases and batch effects. Segmentation results were validated in a lung squamous cell carcinoma dataset from TCGA (n = 367 samples) by comparison to segmentations derived from genotyping arrays (Pearson's correlation coefficient of 0.91). We further introduce a segmented block bootstrapping approach to detect focal alternations that achieved 60.9% sensitivity and 98.6% specificity for deletions affecting CDKN2A/B (60.0% and 96.9% for RB1, respectively) in a low-grade glioma cohort from TCGA (n = 239 samples). Finally, our tool provides functionality to detect and summarize CNVs across large sample cohorts. AVAILABILITY AND IMPLEMENTATION: Conumee 2.0 is available under open-source license at: https://github.com/hovestadtlab/conumee2.

DNA methylation-array interlaboratory comparison trial demonstrates highly reproducible paediatric CNS tumour classification across 13 international centres.

AIMS: DNA methylation profiling, recently endorsed by the World Health Organisation (WHO) as a pivotal diagnostic tool for brain tumours, most commonly relies on bead arrays. Despite its widespread use, limited data exist on the technical reproducibility and potential cross-institutional differences. The LOGGIC Core BioClinical Data Bank registry conducted a prospective laboratory comparison trial with 12 international laboratories to enhance diagnostic accuracy for paediatric low-grade gliomas, focusing on technical aspects of DNA methylation data generation and profile interpretation under clinical real-time conditions. METHODS: Four representative low-grade gliomas of distinct histologies were centrally selected, and DNA extraction was performed. Participating laboratories received a DNA aliquot and performed the DNA methylation-based classification and result interpretation without knowledge of tumour histology. Additionally, participants were required to interpret the copy number profile derived from DNA methylation data and conduct DNA sequencing of the BRAF hotspot p.V600 due to its relevance for low-grade gliomas. Results had to be returned within 30 days. RESULTS: High technical reproducibility was observed, with a median pairwise correlation of 0.99 (range 0.94-0.99) between coordinating laboratory and participants. DNA methylation-based tumour classification and copy number profile interpretation were consistent across all centres, and BRAF mutation status was accurately reported for all cases. Eleven out of 12 centres successfully reported their analysis within the 30-day timeframe. CONCLUSION: Our study demonstrates remarkable concordance in DNA methylation profiling and profile interpretation across 12 international centres. These findings underscore the potential contribution of DNA methylation analysis to the harmonisation of brain tumour diagnostics.

Expanded analysis of high-grade astrocytoma with piloid features identifies an epigenetically and clinically distinct subtype associated with neurofibromatosis type 1.

High-grade astrocytoma with piloid features (HGAP) is a recently recognized glioma type whose classification is dependent on its global epigenetic signature. HGAP is characterized by alterations in the mitogen-activated protein kinase (MAPK) pathway, often co-occurring with CDKN2A/B homozygous deletion and/or ATRX mutation. Experience with HGAP is limited and to better understand this tumor type, we evaluated an expanded cohort of patients (n = 144) with these tumors, as defined by DNA methylation array testing, with a subset additionally evaluated by next-generation sequencing (NGS). Among evaluable cases, we confirmed the high prevalence CDKN2A/B homozygous deletion, and/or ATRX mutations/loss in this tumor type, along with a subset showing NF1 alterations. Five of 93 (5.4%) cases sequenced harbored TP53 mutations and RNA fusion analysis identified a single tumor containing an NTRK2 gene fusion, neither of which have been previously reported in HGAP. Clustering analysis revealed the presence of three distinct HGAP subtypes (or groups = g) based on whole-genome DNA methylation patterns, which we provisionally designated as gNF1 (n = 18), g1 (n = 72), and g2 (n = 54) (median ages 43.5 years, 47 years, and 32 years, respectively). Subtype gNF1 is notable for enrichment with patients with Neurofibromatosis Type 1 (33.3%, p = 0.0008), confinement to the posterior fossa, hypermethylation in the NF1 enhancer region, a trend towards decreased progression-free survival (p = 0.0579), RNA processing pathway dysregulation, and elevated non-neoplastic glia and neuron cell content (p < 0.0001 and p < 0.0001, respectively). Overall, our expanded cohort broadens the genetic, epigenetic, and clinical phenotype of HGAP and provides evidence for distinct epigenetic subtypes in this tumor type.

Genetic and epigenetic characterization of posterior pituitary tumors.

Pituicytoma (PITUI), granular cell tumor (GCT), and spindle cell oncocytoma (SCO) are rare tumors of the posterior pituitary. Histologically, they may be challenging to distinguish and have been proposed to represent a histological spectrum of a single entity. We performed targeted next-generation sequencing, DNA methylation profiling, and copy number analysis on 47 tumors (14 PITUI; 12 GCT; 21 SCO) to investigate molecular features and explore possibilities of clinically meaningful tumor subclassification. We detected two main epigenomic subgroups by unsupervised clustering of DNA methylation data, though the overall methylation differences were subtle. The largest group (n = 23) contained most PITUIs and a subset of SCOs and was enriched for pathogenic mutations within genes in the MAPK/PI3K pathways (12/17 [71%] of sequenced tumors: FGFR1 (3), HRAS (3), BRAF (2), NF1 (2), CBL (1), MAP2K2 (1), PTEN (1)) and two with accompanying TERT promoter mutation. The second group (n = 16) contained most GCTs and a subset of SCOs, all of which mostly lacked identifiable genetic drivers. Outcome analysis demonstrated that the presence of chromosomal imbalances was significantly associated with reduced progression-free survival especially within the combined PITUI and SCO group (p = 0.031). In summary, we observed only subtle DNA methylation differences between posterior pituitary tumors, indicating that these tumors may be best classified as subtypes of a single entity. Nevertheless, our data indicate differences in mutation patterns and clinical outcome. For a clinically meaningful subclassification, we propose a combined histo-molecular approach into three subtypes: one subtype is defined by granular cell histology, scarcity of identifiable oncogenic mutations, and favorable outcome. The other two subtypes have either SCO or PITUI histology but are segregated by chromosomal copy number profile into a favorable group (no copy number changes) and a less favorable group (copy number imbalances present). Both of the latter groups have recurrent MAPK/PI3K genetic alterations that represent potential therapeutic targets.

High-grade astrocytoma with piloid features (HGAP): the Charité experience with a new central nervous system tumor entity.

PURPOSE: High-grade astrocytoma with piloid features (HGAP) is a recently described brain tumor entity defined by a specific DNA methylation profile. HGAP has been proposed to be integrated in the upcoming World Health Organization classification of central nervous system tumors expected in 2021. In this series, we present the first single-center experience with this new entity. METHODS: During 2017 and 2020, six HGAP were identified. Clinical course, surgical procedure, histopathology, genome-wide DNA methylation analysis, imaging, and adjuvant therapy were collected. RESULTS: Tumors were localized in the brain stem (n = 1), cerebellar peduncle (n = 1), diencephalon (n = 1), mesencephalon (n = 1), cerebrum (n = 1) and the thoracic spinal cord (n = 2). The lesions typically presented as T1w hypo- to isointense and T2w hyperintense with inhomogeneous contrast enhancement on MRI. All patients underwent initial surgical intervention. Three patients received adjuvant radiochemotherapy, and one patient adjuvant radiotherapy alone. Four patients died of disease, with an overall survival of 1.8, 9.1, 14.8 and 18.1 months. One patient was alive at the time of last follow-up, 14.6 months after surgery, and one patient was lost to follow-up. Apart from one tumor, the lesions did not present with high grade histology, however patients showed poor clinical outcomes. CONCLUSIONS: Here, we provide detailed clinical, neuroradiological, histological, and molecular pathological information which might aid in clinical decision making until larger case series are published. With the exception of one case, the tumors did not present with high-grade histology but patients still showed short intervals between diagnosis and tumor progression or death even after extensive multimodal therapy.

Clinical implications of DNA methylation-based integrated classification of histologically defined grade 2 meningiomas.

The combination of DNA methylation analysis with histopathological and genetic features allows for a more accurate risk stratification and classification of meningiomas. Nevertheless, the implications of this classification for patients with grade 2 meningiomas, a particularly heterogeneous tumor entity, are only partially understood. We correlate the outcomes of histopathologically confirmed grade 2 meningioma with an integrated molecular-morphologic risk stratification and determine its clinical implications. Grade 2 meningioma patients treated at our institution were re-classified using an integrated risk stratification involving DNA methylation array-based data, copy number assessment and TERT promoter mutation analyses. Grade 2 meningioma cases according to the WHO 2021 criteria treated between 2007 and 2021 (n = 100) were retrospectively analyzed. The median clinical and radiographic follow-up periods were 59.8 and 54.4 months. A total of 38 recurrences and 17 deaths were observed. The local control rates of the entire cohort after 2-, 4-, and 6-years were 84.3%, 68.5%, and 50.8%, with a median local control time of 77.2 months. The distribution of the integrated risk groups were as follows: 31 low, 54 intermediate, and 15 high risk cases. In the multivariable Cox regression analysis, integrated risk groups were significantly associated with the risk of local recurrence (hazard ratio (HR) intermediate: 9.91, HR high-risk: 7.29, p < 0.01). Gross total resections decreased the risk of local tumor progression (HR gross total resection: 0.19, p < 0.01). The comparison of 1p status and integrated risk groups (low vs. intermediate/high) revealed nearly identical local control rates within their respective subgroups. In summary, only around 50% of WHO 2021 grade 2 meningiomas have an intermediate risk profile. Integrated molecular risk stratification is crucial to guide the management of patients with grade 2 tumors and should be routinely applied to avoid over- and undertreatment, especially concerning the use of adjuvant radiotherapy.

Diffuse paediatric-type high-grade glioma, H3-wildtype and IDH-wildtype: case series of a new entity.

Diffuse paediatric-type high-grade glioma, H3-wildtype and IDH-wildtype (pHGG) is a rare and aggressive brain tumor characterized by a specific DNA methylation profile. It was recently introduced in the 5th World Health Organization classification of central nervous system tumors of 2021. Clinical data on this tumor is scarce. This is a case series, which presents the first clinical experience with this entity. We compiled a retrospective case series on pHGG patients treated between 2015 and 2022 at our institution. Data collected include patients' clinical course, surgical procedure, histopathology, genome-wide DNA methylation analysis, imaging and adjuvant therapy. Eight pHGG were identified, ranging in age from 8 to 71 years. On MRI tumors presented with an unspecific intensity profile, T1w hypo- to isointense and T2w hyperintense, with inhomogeneous contrast enhancement, often with rim enhancement. Three patients died of the disease, with overall survival of 19, 28 and 30 months. Four patients were alive at the time of the last follow-up, 4, 5, 6 and 79 months after the initial surgery. One patient was lost to follow-up. Findings indicate that pHGG prevalence might be underestimated in the elderly population.

DNA methylation-based classifier differentiates intrahepatic pancreato-biliary tumours.

BACKGROUND: Differentiating intrahepatic cholangiocarcinomas (iCCA) from hepatic metastases of pancreatic ductal adenocarcinoma (PAAD) is challenging. Both tumours have similar morphological and immunohistochemical pattern and share multiple driver mutations. We hypothesised that DNA methylation-based machine-learning algorithms may help perform this task. METHODS: We assembled genome-wide DNA methylation data for iCCA (n = 259), PAAD (n = 431), and normal bile duct (n = 70) from publicly available sources. We split this cohort into a reference (n = 399) and a validation set (n = 361). Using the reference cohort, we trained three machine learning models to differentiate between these entities. Furthermore, we validated the classifiers on the technical validation set and used an internal cohort (n = 72) to test our classifier. FINDINGS: On the validation cohort, the neural network, support vector machine, and the random forest classifiers reached accuracies of 97.68%, 95.62%, and 96.5%, respectively. Filtering by anomaly detection and thresholds improved the accuracy to 99.07% (37 samples excluded by filtering), 96.22% (17 samples excluded), and 100% (44 samples excluded) for the neural network, support vector machine and random forest, respectively. Because of best balance between accuracy and number of predictable cases we tested the neural network with applied filters on the in-house cohort, obtaining an accuracy of 95.45%. INTERPRETATION: We developed a classifier that can differentiate between iCCAs, intrahepatic metastases of a PAAD, and normal bile duct tissue with high accuracy. This tool can be used for improving the diagnosis of pancreato-biliary cancers of the liver. FUNDING: This work was supported by Berlin Institute of Health (JCS Program), DKTK Berlin (Young Investigator Grant 2022), German Research Foundation (493697503 and 314905040 - SFB/TRR 209 Liver Cancer B01), and German Cancer Aid (70113922).

A Novel Type of IDH-wildtype Glioma Characterized by Gliomatosis Cerebri-like Growth Pattern, TERT Promoter Mutation, and Distinct Epigenetic Profile.

Diffuse gliomas in adults encompass a heterogenous group of central nervous system neoplasms. In recent years, extensive (epi-)genomic profiling has identified several glioma subgroups characterized by distinct molecular characteristics, most importantly IDH1/2 and histone H3 mutations. A group of 16 diffuse gliomas classified as "adult-type diffuse high-grade glioma, IDH-wildtype, subtype F (HGG-F)" was identified by the DKFZ v12.5 Brain Tumor Classifier . Histopathologic characterization, exome sequencing, and review of clinical data was performed in all cases. Based on unsupervised t -distributed stochastic neighbor embedding and clustering analysis of genome-wide DNA methylation data, HGG-F shows distinct epigenetic profiles separate from established central nervous system tumors. Exome sequencing demonstrated frequent TERT promoter (12/15 cases), PIK3R1 (11/16), and TP53 mutations (5/16). Radiologic characteristics were reminiscent of gliomatosis cerebri in 9/14 cases (64%). Histopathologically, most cases were classified as diffuse gliomas (7/16, 44%) or were suspicious for the infiltration zone of a diffuse glioma (5/16, 31%). None of the cases demonstrated microvascular proliferation or necrosis. Outcome of 14 patients with follow-up data was better compared to IDH-wildtype glioblastomas with a median progression-free survival of 58 months and overall survival of 74 months (both P <0.0001). Our series represents a novel type of adult-type diffuse glioma with distinct molecular and clinical features. Importantly, we provide evidence that TERT promoter mutations in diffuse gliomas without further morphologic or molecular signs of high-grade glioma should be interpreted in the context of the clinicoradiologic presentation as well as epigenetic profile and may not be suitable as a standalone marker for glioblastoma, IDH-wildtype.

Adult intracranial ependymoma-relevance of DNA methylation profiling for diagnosis, prognosis, and treatment.

BACKGROUND: A methylation-based classification of ependymoma has recently found broad application. However, the diagnostic advantage and implications for treatment decisions remain unclear. Here, we retrospectively evaluate the impact of surgery and radiotherapy on outcome after molecular reclassification of adult intracranial ependymomas. METHODS: Tumors diagnosed as intracranial ependymomas from 170 adult patients collected from 8 diagnostic institutions were subjected to DNA methylation profiling. Molecular classes, patient characteristics, and treatment were correlated with progression-free survival (PFS). RESULTS: The classifier indicated an ependymal tumor in 73.5%, a different tumor entity in 10.6%, and non-classifiable tumors in 15.9% of cases, respectively. The most prevalent molecular classes were posterior fossa ependymoma group B (EPN-PFB, 32.9%), posterior fossa subependymoma (PF-SE, 25.9%), and supratentorial ZFTA fusion-positive ependymoma (EPN-ZFTA, 11.2%). With a median follow-up of 60.0 months, the 5- and 10-year-PFS rates were 64.5% and 41.8% for EPN-PFB, 67.4% and 45.2% for PF-SE, and 60.3% and 60.3% for EPN-ZFTA. In EPN-PFB, but not in other molecular classes, gross total resection (GTR) (P = .009) and postoperative radiotherapy (P = .007) were significantly associated with improved PFS in multivariable analysis. Histological tumor grading (WHO 2 vs. 3) was not a predictor of the prognosis within molecularly defined ependymoma classes. CONCLUSIONS: DNA methylation profiling improves diagnostic accuracy and risk stratification in adult intracranial ependymoma. The molecular class of PF-SE is unexpectedly prevalent among adult tumors with ependymoma histology and relapsed as frequently as EPN-PFB, despite the supposed benign nature. GTR and radiotherapy may represent key factors in determining the outcome of EPN-PFB patients.

Sarcoma classification by DNA methylation profiling in clinical everyday life: the Charité experience.

BACKGROUND: Sarcomas are a heterogeneous group of rare malignant tumors with more than 100 subtypes. Accurate diagnosis remains challenging due to a lack of characteristic molecular or histomorphological hallmarks. A DNA methylation-based tumor profiling classifier for sarcomas (known as sarcoma classifier) from the German Cancer Research Center (Deutsches Krebsforschungszentrum) is now employed in selected cases to guide tumor classification and treatment decisions at our institution. Data on the usage of the classifier in daily clinical routine are lacking. METHODS: In this single-center experience, we describe the clinical course of five sarcoma cases undergoing thorough pathological and reference pathological examination as well as DNA methylation-based profiling and their impact on subsequent treatment decisions. We collected data on the clinical course, DNA methylation analysis, histopathology, radiological imaging, and next-generation sequencing. RESULTS: Five clinical cases involving DNA methylation-based profiling in 2021 at our institution were included. All patients' DNA methylation profiles were successfully matched to a methylation profile cluster of the sarcoma classifier's dataset. In three patients, the classifier reassured diagnosis or aided in finding the correct diagnosis in light of contradictory data and differential diagnoses. In two patients with intracranial tumors, the classifier changed the diagnosis to a novel diagnostic tumor group. CONCLUSIONS: The sarcoma classifier is a valuable diagnostic tool that should be used after comprehensive clinical and histopathological evaluation. It may help to reassure the histopathological diagnosis or indicate the need for thorough reassessment in cases where it contradicts previous findings. However, certain limitations (non-classifiable cases, misclassifications, unclear degree of sample purity for analysis and others) currently preclude wide clinical application. The current sarcoma classifier is therefore not yet ready for a broad clinical routine. With further refinements, this promising tool may be implemented in daily clinical practice in selected cases.