German Cancer Research Center Research Articles

Decoding the DNA methylome of central nervous system tumors: An emerging modality for integrated diagnosis.

The definitive diagnosis and classification of individual cancers are crucial for patient care and cancer research. To achieve a robust diagnosis of central nervous system (CNS) tumors, a genotype-phenotype integrated diagnostic approach was introduced in recent versions of the World Health Organization classification, followed by the incorporation of a genome-wide DNA methylome-based classification. Microarray-based platforms are widely used to obtain DNA methylome data, and the German Cancer Research Center (Deutsches Krebsforschungszentrum [DKFZ]) has a webtool for a DNA methylation-based classifier (DKFZ classifier). Integration of DNA methylome will further enhance the precision of CNS tumor classification, especially in diagnostically challenging cases. However, in the clinical application of DNA methylome-based classification, challenges related to data interpretation persist, in addition to technical caveats, regulations, and limited accessibility. Dimensionality reduction (DMR) can complement integrated diagnosis by visualizing a profile and comparing it with other known samples. Therefore, DNA methylome-based classification is a highly useful research tool for auxiliary analysis in challenging diagnostic and rare disease cases, and for establishing novel tumor concepts. Decoding the DNA methylome, especially by DMR in addition to DKFZ classifier, emphasizes the capability of grasping the fundamental biological principles that provide new perspectives on CNS tumors.

PATH-41. INTEGRATED MOLECULAR ANALYSIS REVEALS HYPERMETHYLATION AND OVEREXPRESSION OF HOX GENES TO BE POOR PROGNOSTICATORS IN IDH MUTANT GLIOMA

Abstract BACKGROUND Diffuse gliomas represent over 80% of malignant brain tumors ranging from low-grade to aggressive high-grade lesions. Within IDH-mutant gliomas there is a high variability in survival and a need to more accurately predict outcome. METHODS To identify and characterize a predictive signature of outcome in gliomas, we utilized an integrative molecular analysis (using methylation, mRNA, copy number variation (CNV) and mutation data), analyzing a total of 729 IDH-mutant samples including a test set of 99 from University Health Network (UHN) and two validation cohorts including the German Cancer Research Center (DKFZ) and The Cancer Genome Atlas (TCGA). RESULTS Cox regression analysis of methylation data from the UHN cohort identified CpG-based signatures that split the glioma cohort into two prognostic groups strongly predicting survival that were validated using two independent cohorts from TCGA and DKFZ (all p-values< 0.0001). The methylation signatures that predicted poor outcome also exhibited high CNV instability and hypermethylation of HOX gene probes. Integrated multi-platform analyses using mRNA and methylation (iRM) showed that parallel HOX gene overexpression and simultaneous hypermethylation were significantly associated with increased mutational load, high aneuploidy and worse survival (p-value< 0.0001). A 7-HOX gene signature was developed and validated using the most significantly associated HOX genes with patient outcome in both 1p/19q codeleted and non-codeleted IDHmut gliomas. CONCLUSIONS HOX gene methylation and expression provide important prognostic information in IDH-mutant gliomas that are not captured by current molecular diagnostics. A 7-HOX gene signature of outcome shows significant survival differences in both 1p/19q codeleted and non-codeleted IDH-mutant gliomas.

NCT/DKFZ MASTER handbook of interpreting whole-genome, transcriptome, and methylome data for precision oncology

Analysis of selected cancer genes has become an important tool in precision oncology but cannot fully capture the molecular features and, most importantly, vulnerabilities of individual tumors. Observational and interventional studies have shown that decision-making based on comprehensive molecular characterization adds significant clinical value. However, the complexity and heterogeneity of the resulting data are major challenges for disciplines involved in interpretation and recommendations for individualized care, and limited information exists on how to approach multilayered tumor profiles in clinical routine. We report our experience with the practical use of data from whole-genome or exome and RNA sequencing and DNA methylation profiling within the MASTER (Molecularly Aided Stratification for Tumor Eradication Research) program of the National Center for Tumor Diseases (NCT) Heidelberg and Dresden and the German Cancer Research Center (DKFZ). We cover all relevant steps of an end-to-end precision oncology workflow, from sample collection, molecular analysis, and variant prioritization to assigning treatment recommendations and discussion in the molecular tumor board. To provide insight into our approach to multidimensional tumor profiles and guidance on interpreting their biological impact and diagnostic and therapeutic implications, we present case studies from the NCT/DKFZ molecular tumor board that illustrate our daily practice. This manual is intended to be useful for physicians, biologists, and bioinformaticians involved in the clinical interpretation of genome-wide molecular information.

Prognostic significance of molecular subgroups in survival outcome for children with medulloblastoma in Malaysia.

Advancements in genomic profiling led to the discovery of four major molecular subgroups in medulloblastoma (MB), which have now been incorporated into the World Health Organization classification of central nervous system tumors. The current study aimed to determine the prognostic significance of the MB molecular subgroups among children in Malaysia. We assembled MB samples from children <18 years between January 2003 and June 2017 from four pediatric oncology centers in Malaysia. MB was sub-grouped using 850k DNA methylation testing at German Cancer Research Centre, Heidelberg, Germany. Fifty samples from patients diagnosed and treated as MB were identified. Two (4%) of the 50 patients' tumor DNA samples were insufficient for analysis. Of the remaining 48 patients, 41 (85%) samples were confirmed as MB, while for 7 (15%) patients, DNA methylation classification results were discrepant with the histopathological diagnosis of MB, with various other diagnoses. Of the 41 MB patients, 15 patients were stratified as standard-risk (SR), 16 patients as high-risk (HR), and ten as infants (age <3 years old). Molecular subgrouping of the whole cohort revealed four (14%) WNT, 11 (27%) SHH, 10 (24%) Group 3, and 16 (39%) Group 4. Treatment abandonment rates for older children and infants were 22.5% and 10%, respectively. After censoring treatment abandonment, for SR patients, the 5-year event-free survival (EFS) and overall survival (OS) were 43.1% ± 14.7% and 46.9 ± 15.6%, respectively, while in HR, 5-year EFS and OS were both 63.6% ± 14.5%. Infants had a 5-year EFS and OS of 55.6% ± 16.6% and 66.7% ± 15.7%, respectively. WNT tumors had the best 5y-OS, followed by Group 3, Group 4, and SHH in children ≥3 years old. In younger children, SHH MB patients showed favorable outcomes. The study highlights the importance of DNA methylation profiling for diagnostic accuracy. Most infants had SHH MB, and their EFS and OS were comparable to those reported in high-income countries. Due to the relatively small cohort and the high treatment abandonment rate, definite conclusions cannot be made regarding the prognostic significance of molecular subgroups of MB. Implementing this high-technology investigation would assist pathologists in improving the diagnosis and provide molecular subgrouping of MB, permitting subgroup-specific therapies.

Implementation of DNA Methylation Array Profiling in Pediatric Central Nervous System Tumors: The AIM BRAIN Project: An Australian and New Zealand Children's Haematology/Oncology Group Study

DNA methylation array profiling for classifying pediatric central nervous system (CNS) tumors is a valuable adjunct to histopathology. However, unbiased prospective and interlaboratory validation studies have been lacking. The AIM BRAIN diagnostic trial involving 11 pediatric cancer centers in Australia and New Zealand was designed to test the feasibility of routine clinical testing and ran in parallel with the Molecular Neuropathology 2.0 (MNP2.0) study at Deutsches Krebsforschungszentrum (German Cancer Research Center). CNS tumors from 269 pediatric patients were prospectively tested on Illumina EPIC arrays, including 104 cases co-enrolled on MNP2.0. Using MNP classifier versions 11b4 and 12.5, we report classifications with a probability score ≥0.90 in 176 of 265 (66.4%) and 213 of 269 (79.2%) cases, respectively. Significant diagnostic information was obtained in 130 of 176 (74%) for 11b4, and 12 of 174 (7%) classifications were discordant with histopathology. Cases prospectively co-enrolled on MNP2.0 gave concordant classifications (99%) and score thresholds (93%), demonstrating excellent test reproducibility and sensitivity. Overall, DNA methylation profiling is a robust single workflow technique with an acceptable diagnostic yield that is considerably enhanced by the extensive subgroup and copy number profile information generated by the platform. The platform has excellent test reproducibility and sensitivity and contributes significantly to CNS tumor diagnosis.

Integrated molecular analysis reveals hypermethylation and overexpression of HOX genes to be poor prognosticators in isocitrate dehydrogenase mutant glioma.

Diffuse gliomas represent over 80% of malignant brain tumors ranging from low-grade to aggressive high-grade lesions. Within isocitrate dehydrogenase (IDH)-mutant gliomas, there is a high variability in survival and a need to more accurately predict outcome. To identify and characterize a predictive signature of outcome in gliomas, we utilized an integrative molecular analysis (using methylation, mRNA, copy number variation (CNV), and mutation data), analyzing a total of 729 IDH-mutant samples including a test set of 99 from University Health Network (UHN) and 2 validation cohorts including the German Cancer Research Center (DKFZ) and The Cancer Genome Atlas (TCGA). Cox regression analysis of methylation data from the UHN cohort identified CpG-based signatures that split the glioma cohort into 2 prognostic groups strongly predicting survival that were validated using 2 independent cohorts from TCGA and DKFZ (all P-values < .0001). The methylation signatures that predicted poor outcomes also exhibited high CNV instability and hypermethylation of HOX gene probes. Integrated multi-platform analyses using mRNA and methylation (iRM) showed that parallel HOX gene overexpression and simultaneous hypermethylation were significantly associated with increased mutational load, high aneuploidy, and worse survival (P-value < .0001). A 7-HOX gene signature was developed and validated using the most significantly associated HOX genes with patient outcome in both 1p/19q codeleted and non-codeleted IDHmut gliomas. HOX gene methylation and expression provide important prognostic information in IDH-mutant gliomas that are not captured by current molecular diagnostics. A 7-HOX gene signature of outcome shows significant survival differences in both 1p/19q codeleted and non-codeleted IDH-mutant gliomas.

Bibliometric Analysis of The Scientific Literature on Human Papillomavirus Vaccine Clinical Trials: Analysis of PubMed Database

Background: Cervical cancer is the 4th most common cancer in the world caused by human papillomavirus (HPV). A preventive measure for cervical cancer is immunization with the HPV vaccine. Hence globally many clinical trials on HPV vaccines are being performed to prevent HPV infection. This bibliometric analysis is done to determine the trend of clinical trials on HPV vaccines worldwide over the years. Methodology: The articles on HPV vaccine clinical trials were extracted from the PubMed database (Mar 1999 – Sept 2022) and the bibliometric data analysis was done using Microsoft Excel. Result: We extracted 308 articles from the PubMed database and obtained 296 clinical trial articles after removing the non-relevant ones. The majority of the papers were published by institutions in the United States of America (USA) among 39 countries (n=112, 37.8%). Most publications were done by the National Cancer Institute of the USA among 188 institutions worldwide (n=19, 6.4%). The majority of articles were published by more than five authors. Lehtinen M from the Department of Infections and Cancer, German Cancer Research Center has done the most number of publications (n=7). More publications were from the Vaccine journal (n=38). The first three highly cited articles had more than 2000 citations. The years 2015 and 2019 had the highest number of publications (n=25). Conclusion: We can observe a gradual increase in clinical research on the HPV vaccine over the years that accounts for the reduction in cervical cancer cases.

Heterogeneity in the gene regulatory landscape of leiomyosarcoma.

Characterizing inter-tumor heterogeneity is crucial for selecting suitable cancer therapy, as the presence of diverse molecular subgroups of patients can be associated with disease outcome or response to treatment. While cancer subtypes are often characterized by differences in gene expression, the mechanisms driving these differences are generally unknown. We set out to model the regulatory mechanisms driving sarcoma heterogeneity based on patient-specific, genome-wide gene regulatory networks. We developed a new computational framework, PORCUPINE, which combines knowledge on biological pathways with permutation-based network analysis to identify pathways that exhibit significant regulatory heterogeneity across a patient population. We applied PORCUPINE to patient-specific leiomyosarcoma networks modeled on data from The Cancer Genome Atlas and validated our results in an independent dataset from the German Cancer Research Center. PORCUPINE identified 37 heterogeneously regulated pathways, including pathways representing potential targets for treatment of subgroups of leiomyosarcoma patients, such as FGFR and CTLA4 inhibitory signaling. We validated the detected regulatory heterogeneity through analysis of networks and chromatin states in leiomyosarcoma cell lines. We showed that the heterogeneity identified with PORCUPINE is not associated with methylation profiles or clinical features, thereby suggesting an independent mechanism of patient heterogeneity driven by the complex landscape of gene regulatory interactions.

Abstract ND04: BAY 2965501: A highly selective DGK- ζ inhibitor for cancer immuno-therapy with first-in-class potential

Abstract The second messenger diacyl glycerol (DAG) plays a key role in T cell receptor downstream signaling and thereby in T-cell activation. Diacylglycerol kinase zeta (DGK-ζ) is a lipid kinase that can down-modulate T-cell activation by catalyzing the conversion of DAG to phosphatidic acid, thereby acting as a ligand independent, intracellular immune checkpoint. Inhibition of DGK- ζ offers the potential to enhance T cell priming against suboptimal tumor antigens and to overcome multiple immune-suppressive mechanisms in the tumor microenvironment. Bayer AG in collaboration with the German Cancer Research Center (DKFZ) have developed BAY 2965501, a highly selective, orally available DGK-ζ inhibitor which shows a unique binding mode and good DMPK profile. The compound enhances the reactivity of human and mouse T-cells, both in the priming and the effector phase, and overcomes the inhibitory impact of suppressive factors, such as adenosine and prostaglandin E2. Oral dosing of BAY 2965501 shows T cell dependent efficacy in syngeneic, murine tumor models. Furthermore, this results in reactivation of exhausted T cells in vivo. Preclinical safety studies showed only mild findings, so that good clinical tolerability is expected. Collectively, the preclinical data support first in human (FiH) phase I testing of therapeutic potential. A FiH trial with BAY 2965501 in patients with advanced solid tumors including NSCLC, gastric/GEJ AdCa, ccRCC, and melanoma patients, is currently enrolling patients (NCT05614102). This study will evaluate the safety, tolerability, maximum tolerated or administered dose, pharmacokinetics, pharmacodynamics, and tumor response profile of BAY 2965501. Citation Format: Rienk Offringa, Catherine Olesch, Frederik Cichon, Mareike Grees, Norbert Schmees, Ulrike Roehn, Florian Prinz, Judith Guenther, Detlef Stoeckigt, Michael Erkelenz, Thi Thanh Uyen Nguyen, Ulf Boemer, Nicolas Werbeck, Marc Kunze, Kirstin Petersen, Dennis Kirchhoff. BAY 2965501: A highly selective DGK- ζ inhibitor for cancer immuno-therapy with first-in-class potential [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr ND04.

A Novel Ultrahigh-Dose-Rate Proton Therapy Technology: Spot-Scanning Proton Arc Therapy + FLASH (SPLASH)

To take full advantage of FLASH dose rate (40 Gy/s) and high-dose conformity, we introduce a novel optimization and delivery technique, the spot-scanning proton arc therapy (SPArc)+FLASH (SPLASH). SPLASH framework was implemented in an open-source proton planning platform (MatRad, Department of Medical Physics in Radiation Oncology, German Cancer Research Center). It optimizes with the clinical dose-volume constraint based on dose distribution and the dose-average dose rate by minimizing the monitor unit constraint on spot weight and accelerator beam current sequentially, enabling the first dynamic arc therapy with voxel-based FLASH dose rate. This new optimization framework minimizes the overall cost function value combined with plan quality and voxel-based dose-rate constraints. Three representative cases (brain, liver, and prostate cancer) were used for testing purposes. Dose-volume histogram, dose-rate-volume histogram, and dose-rate map were compared among intensity modulated proton radiation therapy (IMPT), SPArc, and SPLASH. SPLASH/SPArc could offer superior plan quality over IMPT in terms of dose conformity. The dose-rate-volume histogram results indicated SPLASH could significantly improve V40 Gy/s in the target and region of interest for all tested cases compared with SPArc and IMPT. The optimal beam current per spot is simultaneously generated, which is within the existing proton machine specifications in the research version (<200 nA). SPLASH offers the first voxel-based ultradose-rate and high-dose conformity treatment using proton beam therapy. Such a technique has the potential to fit the needs of a broad range of disease sites and simplify clinical workflow without applying a patient-specific ridge filter, which has never before been demonstrated.

Commentary: Diffuse Isocitrate Dehydrogenase-Mutant Gliomas With Histone H3 Alterations Are Distinguished by Unique Clinical Characteristics, Molecular Expression Profile, and Survival Prognosis.

*Department of Neurosurgery, LMU University Hospital, Ludwig Maximilians University (LMU), Munich, Germany; ‡German Cancer Consortium (DKTK), Partner Site Munich, German Cancer Research Center (DKFZ), Heidelberg, Germany; Correspondence: Joerg-Christian Tonn, MD, Department of Neurosurgery, LMU University Hospital, Ludwig Maximilians University (LMU), Marchioninistrasse 15, Munich, 81377, Germany. Email: [email protected]

Protocol of the OPTIMAL study: Optimization of polypharmacy in geriatric oncology - A randomized controlled trial

BackgroundPolypharmacy is very common in older cancer patients and these patients are particularly vulnerable to drug-drug interactions and adverse drug reactions because they often receive chemotherapy and symptom-relieving agents.MethodsThe primary aim of the randomized, controlled Optimization of Polypharmacy in Geriatric Oncology (OPTIMAL) trial is to test whether an advisory letter with the results of a comprehensive medication review conducted with the Fit fOR The Aged (FORTA) list to the caring physician in rehabilitation clinics improves the quality of life (QoL) of older cancer patients exposed to polypharmacy more than usual care. The FORTA list detects medication overuse, underuse, and potentially inappropriate drug use among older adults. In the oncology departments of approximately 10 German rehabilitation clinics, we aim to recruit 514 cancer patients (22 common cancers; diagnosis or recurrence requiring treatment in the last 5 years; all stages) who are ≥ 65 years old, regularly take ≥ 5 drugs, and have ≥ 1 medication-related problem. All necessary information about the patients will be provided to a pharmacist at the coordinating center (German Cancer Research Center, Heidelberg), who will perform randomization (1:1) and conduct the medication review with the FORTA list. For the intervention group only, the results are sent by letter to the treating physician in the rehabilitation clinics, who shall discuss medication changes with the patient at the discharge visit, as well as implement them afterwards and disclose them in the discharge letter to the general practitioner. The control group gets the usual care provided in German rehabilitation clinics, which usually does not include a comprehensive medication review but can include medication changes. Patients will be blinded, as they cannot know whether proposed medication changes were part of the study or part of usual care. Study physicians cannot be blinded. The primary endpoint will be the EORTC-QLQ-C30 global health status/QoL score, assessed via self-administered questionnaires 8 months after baseline.DiscussionIf the planned study shows that a medication review with the FORTA list improves the QoL of older cancer patients in oncological rehabilitation more than usual care, it would provide the necessary evidence to translate the trial’s findings into routine care.Trial registrationGerman Clinical Trials Register (DRKS): DRKS00031024.

Moisturizing at a molecular level - The basis of Corneocare.

This review covers the last 20 years of research we and our collaborators have conducted on ethnic differences in facial skin moisturization placed in historical context with previous research. We have focussed particularly on the biochemical and cellular gradients of the stratum corneum (SC) with the aim of discovering new skin moisturization and SC maturation mechanisms, identifying new technologies and/or providing conceptual innovations for ingredients that will improve our understanding and treatment of dry skin. Specifically, we discuss gradients for corneodesmosomes and proteases, corneocyte phenotype-inducing enzymes, filaggrin and natural moisturizing factor (NMF), and barrier lipids. These gradients are interdependent and influence greatly corneocyte maturation. The interrelationship between corneodesmolysis and the covalent attachment of ω-hydroxy ceramides and ω-hydroxy fatty acids to the corneocyte protein envelope forming the corneocyte lipid envelope is especially relevant in our new understanding of mechanisms leading to dry skin. This process is initiated by a linoleoyl-ω-acyl ceramide transforming enzyme cascade including 12R lipoxygenase (12R-LOX), epidermal lipoxygenase-3 (eLOX3), epoxide hydrolase 3 (EPHX3), short-chain dehydrogenase/reductase family 9C member 7 (SDR9C7), ceramidase and transglutaminase 1. Our research has opened the opportunity of using novel treatment systems for dry skin based on lipids, humectants, niacinamide and inhibitors of the plasminogen system. It is clear that skin moisturization is a more complex mechanism than simple skin hydration.

DNA methylation provides diagnostic value for meningioma recurrence in clinical practice.

Meningiomas are the most common intracranial tumors. Recent advancements in the genetic profiling of tumors have allowed information including DNA copy number analysis, mutational analysis, and RNA sequencing to be more frequently reported, in turn allowing better characterization of meningiomas. In recent years, analysis of tumor methylomes that reflects both cell-origin methylation signatures and somatically acquired DNA methylation changes has been utilized to better classify meningiomas with great success. We report DNA methylation profiling on meningiomas from 17 patients. Formalin-fixed paraffin-embedded (FFPE) meningioma tumor samples were processed, loaded onto the Infinium Methylation EPIC array, and scanned using the Illumina IScan system. Raw IDAT files were processed through the the CNS tumor classifier developed by the Molecular Neuropathology group at the German Cancer Research Center (DKFZ). Corresponding genomics were captured using targeted sequencing panels. Among the meningioma samples, 13 samples were classified as "benign," two samples as "intermediate," and the remaining three samples (from two patients) as "malignant," based on previously validated classification algorithms. In addition to tumor methylation profiling, we also present information that includes patient demographics, clinical presentations, tumor characteristics (including size and location), surgical approaches, and mutational analysis. The two patients who provided the samples with "malignant" methylation classifications had tumor recurrence, reflecting a more aggressive disease course. In accordance with prior reports, our case series provides support that tumor DNA methylation profiling adds meaningful classification information and may be beneficial to incorporate in clinical practice. Our report also reveals that DNA methylation combined with WHO histology classification can more accurately predict tumor behavior than WHO classification alone.

Optimizing the cancer research landscape for the benefit of patients and society: A strategic perspective of the German Cancer Research Center (DKFZ) and its partnerships with university medical centers

This issue of Cancer Biology & Medicine, a premium Chinese international scientific journal in this field, focuses on cooperation between Chinese and German cancer research, particularly between the Tianjin Medical University Cancer Institute & Hospital and the German Cancer Research Center (DKFZ)

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

BackgroundSarcomas 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.MethodsIn 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.ResultsFive 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.ConclusionsThe 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.

116. Integrating methylation profiling into adult brain tumor diagnostics - the Australian experience

While genomic data has revolutionized brain tumor diagnostics in the past decade, methylation profiling has emerged as a valuable classification tool. Methylation profiling is increasingly being shown to be a compelling diagnostic adjunct in pediatric brain tumors. We therefore sought to delineate its most useful indications in diagnostically challenging adult tumors, in combination with current genomic classification parameters. Here we detail our initial experience at a national tertiary referral centre for neuro-oncology diagnostics in Australia. To date, we have profiled 80 such cases using Illumina MethylationEPIC arrays, with DNA extracted from formalin fixed paraffin embedded tissue. Methylation data was analysed using the German Cancer Research Centre (DKFZ) Brain Tumor Methylation Classifier (v12.3). 50 tumours had undergone a concomitant next generation sequencing (NGS) targeted glioma gene panel (20 low grade gliomas/glioneuronal tumors; 30 high grade gliomas). Concordance between the histological diagnosis and methylation class result (with recommended calibrated score ?0.84) was observed in 75% of classifiable cases. Of the low grade gliomas (LGGs), 45% of diagnoses were unresolved by NGS. Of these unresolved cases, the diagnosis of 1 case was resolved by methylation profiling (11%). Of the high grade gliomas (HGGs), 57% of diagnoses were unresolved by NGS. By contrast, 65% of unresolved HGG cases were resolved by methylation profiling, largely comprising ependymomas, medulloblastomas and high grade neuroepithelial tumours. Our preliminary results indicate that methylation profiling has an important role in diagnostically challenging, high grade adult brain tumors, particularly where the tumor entity is also found in the pediatric population.

The utility of DNA methylation analysis in elderly patients with pilocytic astrocytoma morphology.

Pilocytic astrocytoma (PA) is a circumscribed low-grade astrocytic glioma, generally considered to be associated with a good prognosis. However, a subset of PA patients shows unfavorable outcomes. In this study, we retrospectively reviewed PA patients and performed further molecular analysis, such as DNA methylation profiling, to identify prognostic factors. We analyzed 29 histologically-confirmed PA patients from a single center from 2002 to 2021 and conducted integrated molecular analyses among elderly PA patients since age was an independent prognostic factor for poor outcomes. The median age at diagnosis was 14years (range 3-82years) and 4 patients (14%) were elderly (patients ≥ 60years old). Age over 60 was associated with poor progression-free survival and overall survival. We performed DNA methylation analysis on 2 of the 4 elderly patients. Both cases were histologically diagnosed as PA, but DNA methylation profiling revealed one as high-grade astrocytoma with piloid features (all methylation class scores were below 0.3 in both v11b4 and v12.5) and the other as glioblastoma, IDH-wildtype (score was over 0.5 in both v11b4 and v12.5), using the German Cancer Research Center methylation profiling classifiers and t-SNE analysis. Elderly patients with PA morphology showed unfavorable outcomes in this cohort. In those patients, further molecular analysis and DNA methylation profiling revealed the possibility of high-grade astrocytic tumors, including newly defined entities.

PATH-13. Methylation analysis in the diagnosis of pediatric CNS tumors; a single center experience

Abstract BACKGROUND: Tumors of Central Nervous System (CNS) comprise major cause of cancer-related morbidity and mortality during childhood. Recent advances in genome and epigenome research allow for molecular classification of CNS tumors, treatment stratification and therapeutic target identification. In many countries, including Greece, this integrated diagnosis is not possible, yet, in a routine setting due to financial and infrastructural reasons. DESIGN/METHODS: We analyzed the results from the methylation profiling performed on tumor samples from newly diagnosed and selected retrospective patients followed in our unit. Analyses were performed through the PTT2.0 and MNP2.0 Studies, as part of a collaboration project between ACCC (Athens Cancer Comprehensive Center) and DKFZ (German Cancer Research Center). RESULTS: Methylation arrays from 50 patients (mean age: 8years, range: 0-17years) have been analyzed. High calibrated score (&amp;gt;0.9) was achieved in 38 patients (76%) and in 33 (86%) of these, the histological diagnosis matched the methylation class. The remaining 5 cases, diagnosed by the local pathologist as ganglioneuroma, primitive neuroectodermal tumor, anaplastic astrocytoma, pineoblastoma and oligodendroglioma, were classified according to the methylation profiling as dermatofibrosarcoma protuberans, medulloblastoma group 3, high-grade glioma H3.3G34mutant, high-grade neuroepithelial tumor with BCOR alteration and glioneuronal tumor, respectively. Only four cases had no match in the classifier, while seven cases received low score (0.5-0.8). In 6 out of the 7 cases with low score, the diagnosis was confirmed with the use either of the copy-number profile inferred from the methylation array or by additional testing for gene fusions and mutations. In 25 medulloblastomas, methylation profiling provided molecular classification, according to the 2021 WHO Classification. CONCLUSIONS: Our experience on the first 50 cases suggests that methylation array needs to be considered as an integral part of the diagnostic process of pediatric patients with CNS tumors and highlights the importance of international collaboration programs in pediatric neuro-oncology.

Reply by Authors.

No AccessJournal of UrologyNew Technology and Techniques1 May 2022Reply by Authorsis a reply to letterEditorial Comment N. Heller, R. Tejpaul, F. Isensee, T. Benidir, M. Hofmann, P. Blake, Z. Rengal, K. Moore, N. Sathianathen, A. Kalapara, J. Rosenberg, S. Peterson, E. Walczak, A. Kutikov, R. G. Uzzo, D. A. Palacios, E. M. Remer, S. C. Campbell, N. Papanikolopoulos, and Christopher J. Weight N. HellerN. Heller Department of Computer Science and Engineering, University of Minnesota, Minneapolis, Minnesota More articles by this author , R. TejpaulR. Tejpaul Department of Computer Science and Engineering, University of Minnesota, Minneapolis, Minnesota More articles by this author , F. IsenseeF. Isensee German Cancer Research Center (DKFZ) Heidelberg, University of Heidelberg, Heidelberg, Germany More articles by this author , T. BenidirT. Benidir https://orcid.org/0000-0003-2043-3658 Glickman Urological and Kidney Institute, Cleveland Clinic, Cleveland, Ohio More articles by this author , M. HofmannM. Hofmann Glickman Urological and Kidney Institute, Cleveland Clinic, Cleveland, Ohio More articles by this author , P. BlakeP. Blake University of Minnesota School of Medicine, Minneapolis, Minnesota Financial and/or other relationship with the University of Minnesota. More articles by this author , Z. RengalZ. Rengal University of Minnesota School of Medicine, Minneapolis, Minnesota More articles by this author , K. MooreK. Moore Carleton College, Northfield, Minnesota More articles by this author , N. SathianathenN. Sathianathen Department of Urology, University of Melbourne, Melbourne, Australia More articles by this author , A. KalaparaA. Kalapara Department of Urology, University of Melbourne, Melbourne, Australia More articles by this author , J. RosenbergJ. Rosenberg University of Minnesota School of Medicine, Minneapolis, Minnesota More articles by this author , S. PetersonS. Peterson Brigham Young University, Provo, Utah More articles by this author , E. WalczakE. Walczak University of Minnesota School of Medicine, Minneapolis, Minnesota More articles by this author , A. KutikovA. Kutikov Urology, Fox Chase Cancer Center, Philadelphia, Pennsylvania More articles by this author , R. G. UzzoR. G. Uzzo Urology, Fox Chase Cancer Center, Philadelphia, Pennsylvania More articles by this author , D. A. PalaciosD. A. Palacios Glickman Urological and Kidney Institute, Cleveland Clinic, Cleveland, Ohio More articles by this author , E. M. RemerE. M. Remer Glickman Urological and Kidney Institute, Cleveland Clinic, Cleveland, Ohio Department of Diagnostic Radiology, Imaging Institute Cleveland Clinic, Cleveland, Ohio More articles by this author , S. C. CampbellS. C. Campbell Glickman Urological and Kidney Institute, Cleveland Clinic, Cleveland, Ohio More articles by this author , N. PapanikolopoulosN. Papanikolopoulos Department of Computer Science and Engineering, University of Minnesota, Minneapolis, Minnesota More articles by this author , and Christopher J. WeightChristopher J. Weight †Correspondence: Cleveland Clinic, Department of Urology, Desk Q10, 9500 Euclid Ave., Cleveland, Ohio 44195 telephone: 763-498-3762, FAX: 216-445-2267; E-mail Address: [email protected]; E-mail Address: [email protected] Glickman Urological and Kidney Institute, Cleveland Clinic, Cleveland, Ohio Financial and/or other relationship with Abbott Molecular. More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000002390.02AboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail "Reply by Authors." The Journal of Urology, 207(5), p. 1115