The Implementation of DNA Methylation Profiling into a Multistep Diagnostic Process in Pediatric Neuropathology: A 2-Year Real-World Experience by the French Neuropathology Network

Pediatric-type high-grade gliomas with PDGFRA amplification in adult patients with Li-Fraumeni syndrome: clinical and molecular characterization of three cases

Li-Fraumeni syndrome (LFS) is an autosomal dominant tumor predisposition syndrome caused by heterozygous germline mutations or deletions in the TP53 tumor suppressor gene. Central nervous system tumors, such as choroid plexus tumors, medulloblastomas, and diffuse gliomas, are frequently found in patients with LFS. Although molecular profiles of diffuse gliomas that develop in pediatric patients with LFS have been elucidated, those in adults are limited. Recently, diffuse gliomas have been divided into pediatric- and adult-type gliomas, based on their distinct molecular profiles. In the present study, we investigated the molecular profiles of high-grade gliomas in three adults with LFS. These tumors revealed characteristic histopathological findings of high-grade glioma or glioblastoma and harbored wild-type IDH1/2 according to whole exome sequencing (WES). However, these tumors did not exhibit the key molecular alterations of glioblastoma, IDH-wildtype such as TERT promoter mutation, EGFR amplification, or chromosome 7 gain and 10 loss. Although WES revealed no other characteristic gene mutations or copy number alterations in high-grade gliomas, such as those in histone H3 genes, PDGFRA amplification was found in all three cases together with uniparental disomy of chromosome 17p, where the TP53 gene is located. DNA methylation analyses revealed that all tumors exhibited DNA methylation profiles similar to those of pediatric-type high-grade glioma H3-wildtype and IDH-wildtype (pHGG H3-/IDH-wt), RTK1 subtype. These data suggest that high-grade gliomas developed in adult patients with LFS may be involved in pHGG H3-/IDH-wt. PDGFRA and homozygous alterations in TP53 may play pivotal roles in the development of this type of glioma in adult patients with LFS.

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.

Unclassifiable CNS tumors in DNA methylation-based classification: clinical challenges and prognostic impact

DNA methylation analysis has become a powerful tool in neuropathology. Although DNA methylation-based classification usually shows high accuracy, certain samples cannot be classified and remain clinically challenging. We aimed to gain insight into these cases from a clinical perspective. To address, central nervous system (CNS) tumors were subjected to DNA methylation profiling and classified according to their calibrated score using the DKFZ brain tumor classifier (V11.4) as "≥ 0.84" (score ≥ 0.84), "0.3-0.84" (score 0.3-0.84), or "< 0.3" (score < 0.3). Histopathology, patient characteristics, DNA input amount, and tumor purity were correlated. Clinical outcome parameters were time to treatment decision, progression-free, and overall survival. In 1481 patients, the classifier identified 69 (4.6%) tumors with an unreliable score as "< 0.3". Younger age (P < 0.01) and lower tumor purity (P < 0.01) compromised accurate classification. A clinical impact was demonstrated as unclassifiable cases ("< 0.3") had a longer time to treatment decision (P < 0.0001). In a subset of glioblastomas, these cases experienced an increased time to adjuvant treatment start (P < 0.001) and unfavorable survival (P < 0.025). Although DNA methylation profiling adds an important contribution to CNS tumor diagnostics, clinicians should be aware of a potentially longer time to treatment initiation, especially in malignant brain tumors.

Multiomic neuropathology improves diagnostic accuracy in pediatric neuro-oncology

The large diversity of central nervous system (CNS) tumor types in children and adolescents results in disparate patient outcomes and renders accurate diagnosis challenging. In this study, we prospectively integrated DNA methylation profiling and targeted gene panel sequencing with blinded neuropathological reference diagnostics for a population-based cohort of more than 1,200 newly diagnosed pediatric patients with CNS tumors, to assess their utility in routine neuropathology. We show that the multi-omic integration increased diagnostic accuracy in a substantial proportion of patients through annotation to a refining DNA methylation class (50%), detection of diagnostic or therapeutically relevant genetic alterations (47%) or identification of cancer predisposition syndromes (10%). Discrepant results by neuropathological WHO-based and DNA methylation-based classification (30%) were enriched in histological high-grade gliomas, implicating relevance for current clinical patient management in 5% of all patients. Follow-up (median 2.5 years) suggests improved survival for patients with histological high-grade gliomas displaying lower-grade molecular profiles. These results provide preliminary evidence of the utility of integrating multi-omics in neuropathology for pediatric neuro-oncology.

Liquid biopsy in pediatric brain tumors

Malignant primary brain tumors are the most common cancer in children aged 0-14 years, and are the most common cause of death among pediatric cancer patients. Compared to other cancers, pediatric brain tumors have been difficult to diagnose and study given the high risk of intracranial biopsy penetrating through vital midline structures, where the majority of pediatric brain tumors originate (Ostrom et al., 2015). Furthermore, the vast majority of these tumors recur. With limitations in the ability to monitor using clinical and radiographic methods alone, minimally invasive methods such as liquid biopsy will be crucial to our understanding and treatment. Liquid biopsy of blood, urine, and cerebrospinal fluid (CSF) can be used to sample cfDNA, ctDNA, RNA, extracellular vesicles, and tumor-associated proteins. In the past year, four seminal papers have made significant advances in the use of liquid biopsy in pediatric brain tumor patients (Liu et al., 2021; Cantor et al., 2022; Miller et al., 2022; Pagès et al., 2022). In this review, we integrate the results of these studies and others to discuss how the newest technologies in liquid biopsy are being developed for molecular diagnosis and treatment response in pediatric brain tumors.

Cancer epigenetics in clinical practice

Cancer development is driven by the accumulation of alterations affecting the structure and function of the genome. Whereas genetic changes disrupt the DNA sequence, epigenetic alterations contribute to the acquisition of hallmark tumor capabilities by regulating gene expression programs that promote tumorigenesis. Shifts in DNA methylation and histone mark patterns, the two main epigenetic modifications, orchestrate tumor progression and metastasis. These cancer-specific events have been exploited as useful tools for diagnosis, monitoring, and treatment choice to aid clinical decision making. Moreover, the reversibility of epigenetic modifications, in contrast to the irreversibility of genetic changes, has made the epigenetic machinery an attractive target for drug development. This review summarizes the most advanced applications of epigenetic biomarkers and epigenetic drugs in the clinical setting, highlighting commercially available DNA methylation-based assays and epigenetic drugs already approved by the US Food and Drug Administration.

The genomic landscape of dysembryoplastic neuroepithelial tumours and a comprehensive analysis of recurrent cases

AIMS

Dysembryoplastic neuroepithelial tumour (DNT) is a glioneuronal tumour that is challenging to diagnose, with a wide spectrum of histological features. Three histopathological patterns have been described: specific DNTs (both the simple form and the complex form) comprising the specific glioneuronal element, and also the non-specific/diffuse form which lacks it, and has unclear phenotype-genotype correlations with numerous differential diagnoses.

METHODS

We used targeted methods (immunohistochemistry, fluorescence in situ hybridisation and targeted sequencing) and large-scale genomic methodologies including DNA methylation profiling to perform an integrative analysis to better characterise a large retrospective cohort of 82 DNTs, enriched for tumours that showed progression on imaging.

RESULTS

We confirmed that specific DNTs are characterised by a single driver event with a high frequency of FGFR1 variants. However, a subset of DNA methylation-confirmed DNTs harbour alternative genomic alterations to FGFR1 duplication/mutation. We also demonstrated that a subset of DNTs sharing the same FGFR1 alterations can show in situ progression. In contrast to the specific forms, "non-specific/diffuse DNTs" corresponded to a heterogeneous molecular group encompassing diverse, newly-described, molecularly distinct entities.

CONCLUSIONS

Specific DNT is a homogeneous group of tumours sharing characteristics of paediatric low-grade gliomas: a quiet genome with a recurrent genomic alteration in the RAS-MAPK signalling pathway, a distinct DNA methylation profile and a good prognosis but showing progression in some cases. The "non-specific/diffuse DNTs" subgroup encompasses various recently described histomolecular entities, such as PLNTY and diffuse astrocytoma, MYB or MYBL1 altered.

Methylation classifiers: brain tumors, sarcomas and what's next

Tumor classification has evolved over the last decades with technical progress contributing much to our current concepts. Among diagnostic hallmark novelties were immunostaining, Fluorescence in situ hybridization, Sanger sequencing followed by massive parallel DNA sequencing and recently, epigenetic analyses have entered the stage. Although each of these techniques was revolutionary and, in some way, also disruptive in certain diagnostic fields, it took years to decades for broad implementation into standard pathological-diagnostic algorithms. In contrast, DNA methylation profiling has been accepted in short time as a game changer with lasting impact on brain tumor classification and with potential for classification of other tumor types. This review provides a brief introduction in DNA methylation-based tumor classification. We present why DNA methylation signatures are attractive diagnostic biomarkers, discuss present achievements and future aims and explain the integration of methylation-based classifiers in diagnostic procedure. Finally, we provide an outlook on the challenges and opportunities associated with DNA methylation-based tumor profiling. This article is protected by copyright. All rights reserved.

Molecular landscape of IDH-wildtype, H3-wildtype glioblastomas of adolescents and young adults (AYA)

OBJECTIVE

We aimed to characterise glioblastomas of adolescents and young adults (AYA) that were IDH wildtype (wt) and H3 wildtype (wt).

MATERIALS AND METHODS

Fifty such patients (aged 16-32) were studied by methylation profiling, targeted sequencing and targeted RNA-seq.

RESULTS

Tumours predominantly clustered into three methylation classes according to the terminology of Capper et al. (2018): (anaplastic) PXA (21 cases), GBM_midline (15 cases) and glioblastoma RTK/mesenchymal (7 cases). Two cases clustered with ANA_PA, 4 cases with LGG classes and 1 with GBM_MYCN. Only fifteen cases reached a calibrated score >0.84 when the cases were uploaded to DKFZ Classifier. GBM_midline-clustered tumours had a poorer overall survival (OS) compared to the PXA-clustered tumours (p=0.030). LGG-clustered cases had a significantly better survival than GBM_midline-clustered tumours and glioblastoma RTK/mesenchymal-clustered tumours. Only 13/21 (62%) of PXA-clustered cases were BRAF V600E mutated. Most GBM_midline-clustered cases were not located in the midline. GBM_midline-clustered cases were characterized by PDGFRA amplification/mutation (73.3%), mutations of mismatch repair genes (40.0%), and all showed H3K27me3 and EZH1P loss, and an unmethylated MGMT promoter. Across the whole cohort, MGMT promoter methylation and wildtype TERT promoter were favourable prognosticators. Mismatch repair gene mutations were poor prognosticators and together with methylation class and MGMT methylation, maintained their significance in multi-variate analyses. BRAF mutation was a good prognosticator in the PXA-clustered tumours.

CONCLUSION

Methylation profiling is a useful tool in the diagnosis and prognostication of AYA glioblastomas and the methylation classes have distinct molecular characteristics. The usual molecular diagnostic criteria for adult IDHwt glioblastoma should be applied with caution within the AYA age group.

Low-grade epilepsy-associated neuroepithelial tumours with a prominent oligodendroglioma-like component: The diagnostic challenges

AIMS

We searched for recurrent pathological features and molecular alterations in a retrospective series of 72 low-grade epilepsy-associated neuroepithelial tumours (LEATs) with a prominent oligodendroglioma-like component, in order to classify them according to the 2021 World Health Organization (WHO) classification of central nervous system (CNS) tumours.

METHODS

Centralised pathological examination was performed as well as targeted molecular analysis of v-Raf murine sarcoma viral oncogene homologue B (BRAF) and fibroblast growth factor receptor 1 (FGFR1) by multiplexed digital polymerase chain reaction (mdPCR). DNA methylation profiling was performed in cases with sufficient DNA. In cases with no genetic alteration by mdPCR and sufficient material, RNA sequencing was done.

RESULTS

We first reclassified our cohort into three groups: ganglioglioma (GG, n = 14), dysembryoplastic neuroepithelial tumours (DNTs, n = 19) and glioneuronal tumours/paediatric-type low-grade glioma (LGG) not otherwise specified (GNT/PLGG NOS, n = 39). mdPCR found an alteration in 38/72 cases. Subsequent RNA sequencing revealed a fusion transcript involving BRAF, FGFR1/2/3 or neurotrophic tyrosine kinase receptor type 2 [NTRK2] in 9/25 cases. DNA methylation profiling found 12/46 cases with a calibrated score ≥0.9. Unsupervised hierarchical clustering revealed two clusters: Cluster 1 was enriched with cases classified as DNT at histology, belonging to the LGG-DNT methylation class (MC), with haematopoietic progenitor cell antigen (CD34) negativity and FGRF1 alterations; Cluster 2 was enriched with cases classified at histology as GG, belonging to the LGG-GG MC MC, with BRAF V600E mutation and CD34 positivity. The tumours reclassified as GNT/PLGG NOS were equally distributed across both clusters. Interestingly, all polymorphous low-grade neuroepithelial tumour of the young belonged to Cluster 2, whereas diffuse LGG mitogen-activated protein kinase (MAPK) pathway-altered were equally distributed among the two clusters. This led us to build an algorithm to classify LEATs with a prominent oligodendroglioma-like component.

CONCLUSIONS

Integrated histomolecular diagnosis of LEATs with a prominent oligodendroglioma-like component remains challenging. Because these tumours can be split into two major clusters of biological significance, the clinicopathological relevance of the four types recognised by the WHO CNS5 within this spectrum of tumours is questionable.