DNA methylation profiling for molecular classification of adult diffuse lower-grade gliomas.

BACKGROUND: DNA methylation profiling has facilitated and improved the classification of a wide variety of tumors of the central nervous system. In this study, we investigated the potential utility of DNA methylation profiling to achieve molecular diagnosis in adult primary diffuse lower-grade glioma (dLGG) according to WHO 2016 classification system. We also evaluated whether methylation profiling could provide improved molecular characterization and identify prognostic differences beyond the classical histological WHO grade together with IDH mutation status and 1p/19q codeletion status. All patients diagnosed with dLGG in the period 2007-2016 from the Västra Götaland region in Sweden were assessed for inclusion in the study. RESULTS: A total of 166 dLGG cases were subjected for genome-wide DNA methylation analysis. Of these, 126 (76%) were assigned a defined diagnostic methylation class with a class prediction score ≥ 0.84 and subclass score ≥ 0.50. The assigned methylation classes were highly associated with their IDH mutation status and 1p/19q codeletion status. IDH-wildtype gliomas were further divided into subgroups with distinct molecular features. CONCLUSION: The stratification of the patients by methylation profiling was as effective as the integrated WHO 2016 molecular reclassification at predicting the clinical outcome of the patients. Our study shows that DNA methylation profiling is a reliable and robust approach for the classification of dLGG into molecular defined subgroups, providing accurate detection of molecular markers according to WHO 2016 classification

DNA methylation alterations across time and space in paediatric brain tumours

Abstract DNA methylation is increasingly used for tumour classification and has expanded upon the > 100 currently known brain tumour entities. A correct diagnosis is the basis for suitable treatment for patients with brain tumours, which is the leading cause of cancer-related death in children. DNA methylation profiling is required for diagnosis of certain tumours, and used clinically for paediatric brain tumours in several countries. We therefore evaluated if the methylation-based classification is robust in different locations of the same tumour, and determined how the methylation pattern changed over time to relapse. We sampled 3–7 spatially separated biopsies per patient, and collected samples from paired primary and relapse brain tumours from children. Altogether, 121 samples from 46 paediatric patients with brain tumours were profiled with EPIC methylation arrays. The methylation-based classification was mainly homogeneous for all included tumour types that were successfully classified, which is promising for clinical diagnostics. There were indications of multiple subclasses within tumours and switches in the relapse setting, but not confirmed as the classification scores were below the threshold. Site-specific methylation alterations did occur within the tumours and varied significantly between tumour types for the temporal samples, and as a trend in spatial samples. More alterations were present in high-grade tumours compared to low-grade, and significantly more alterations with longer relapse times. The alterations in the spatial and temporal samples were significantly depleted in CpG islands, exons and transcription start sites, while enriched in OpenSea and regions not affiliated with a gene, suggesting a random location of the alterations in less conserved regions. In conclusion, more DNA methylation changes accumulated over time and more alterations occurred in high-grade tumours. The alterations mainly occurred in regions without gene affiliation, and did not affect the methylation-based classification, which largely remained homogeneous in paediatric brain tumours

Preoperative Patient-Reported Outcomes in Suspected Low-Grade Glioma : Markers of Disease Severity and Correlations with Molecular Subtypes

This prospective study aims to determine the overall health-related quality of life (HRQoL), functioning, fatigue, and psychological distress preoperatively in patients with suspected diffuse low-grade glioma (dLGG). We were particularly interested if these parameters differed by molecular tumor subtypes: oligodendroglioma, IDHmut astrocytoma and IDHwt astrocytoma. Fifty-one patients answered self-assessed questionnaires prior to operation (median age 51 years; range 19-75; 19 females [37%]). Thirty-five (69%) patients had IDH-mutated tumors, of which 17 were 1p/19q codeleted (i.e., oligodendroglioma) and 18 non-1p/19q codeleted (i.e., IDHmut astrocytoma). A lower overall generic HRQoL was associated with a high level of fatigue (rs = -0.49, p < 0.001), visual disorder (rs = -0.5, p < 0.001), motor dysfunction (rs = -0.51, p < 0.001), depression (rs = -0.54, p < 0.001), and reduced functioning. Nearly half of the patients reported high fatigue (23 out of 51 patients) and anxiety (26/51 patients). Patients with IDHwt had worse generic HRQoL, worse functioning, and more severe fatigue, though differences were not statistically significant between the molecular subtypes. In conclusion, fatigue and anxiety are prominent self-assessed symptoms of patients with suspected dLGG in a preoperative setting, but do not seem to be a reliable method to make assumptions of underlying biology or guide treatment decisions

Meningioma classification by immunohistochemistry : A replicability study

Introduction: Meningiomas account for nearly 40% of intracranial tumors. Recently, the immunohistochemistry (IHC) markers S100B, SCGN, ACADL and MCM2 have been shown to be associated with underlying biological subtypes of meningioma (MG1-MG4). We aimed to evaluate these IHC markers in a clinical setting. Research question: Are the new proposed IHC markers clinically useful? Methods: In total, 244 patients with meningiomas with tissue in TMAs were included and the IHC markers S100B, SCGN, ACADL and MCM2 were analyzed. Two sets of analyses were performed; the first included all samples with any staining considered positive, the second only samples with >10% immunopositivity. PFS and OS were analyzed in correlation to immunopositivity in the second analysis set. Results: In the first set of analyses only 26.2% of samples could be to allocate to one group. No further analyses were performed with this selection. In the second set of analyses 52.0% could be allocated to a group. There was an enrichment of WHO grade 2 and 3 tumors in MG3 and MG4 as compared to MG1 (24.1% and 25.7% vs. 12.1%). Both the molecular group (p 1/4 0.032) and WHO grade (p 1/4 0.005) had significant impact on PFS, but only WHO grade predicted OS (p 1/4 0.033). Conclusion: We studied the proposed new method of classifying meningiomas into groups MG1, MG2, MG3 and MG4 using IHC markers, but found difficulties applying the classification system in our material mainly due to lack of exclusivity of markers. Thus, in its present form the classification method lacks clinical applicability

The clinical value of proneural, classical and mesenchymal protein signatures in WHO 2021 adult-type diffuse lower-grade gliomas.

ObjectivesAccumulating evidence shows that mesenchymal transition of glioblastomas is associated with a more aggressive course of disease and therapy resistance. In WHO2021-defined adult-type diffuse gliomas of lower grade (dLGG), the transition of the tumor phenotype over time, has not been studied. Most efforts to correlate proneural, classical or mesenchymal phenotype with outcome in dLGG were made prior to the WHO 2021 classification. Here, we set out to investigate if phenotype predicted survival and tumor recurrence in a clinical cohort of dLGGs, re-classified according to the 2021 WHO criteria.MethodsUsing a TMA-based approach with five immunohistochemical markers (EGFR, p53, MERTK, CD44 and OLIG2), we investigated 183 primary and 49 recurrent tumors derived from patients with previously diagnosed dLGG. Of the 49 relapses, nine tumors recurred a second time, and one a third time.ResultsIn total, 71.0% of all tumors could be subtyped. Proneural was most dominant in IDH-mut tumors (78.5%), mesenchymal more common among IDH-wt tumors (63.6%). There was a significant difference in survival between classical, proneural and mesenchymal phenotypes in the total cohort (pConclusionSubtyping into classical, proneural and mesenchymal phenotypes by five immunohistochemical markers, was possible for the majority of tumors, but protein signatures did not correlate with patient survival in our WHO2021-stratified cohort. At recurrence, IDH-mut tumors mainly retained proneural, while IDH-wt tumors mostly retained or gained mesenchymal signatures. This phenotypic shift, associated with increased aggressiveness in glioblastoma, did not affect survival. Group sizes were, however, too small to draw any firm conclusions

Machine learning for cell classification and neighborhood analysis in glioma tissue

Multiplexed and spatially resolved single-cell analyses that intend to study tissue heterogeneity and cell organization invariably face as a first step the challenge of cell classification. Accuracy and reproducibility are important for the downstream process of counting cells, quantifying cell–cell interactions, and extracting information on disease-specific localized cell niches. Novel staining techniques make it possible to visualize and quantify large numbers of cell-specific molecular markers in parallel. However, due to variations in sample handling and artifacts from staining and scanning, cells of the same type may present different marker profiles both within and across samples. We address multiplexed immunofluorescence data from tissue microarrays of low-grade gliomas and present a methodology using two different machine learning architectures and features insensitive to illumination to perform cell classification. The fully automated cell classification provides a measure of confidence for the decision and requires a comparably small annotated data set for training, which can be created using freely available tools. Using the proposed method, we reached an accuracy of 83.1% on cell classification without the need for standardization of samples. Using our confidence measure, cells with low-confidence classifications could be excluded, pushing the classification accuracy to 94.5%. Next, we used the cell classification results to search for cell niches with an unsupervised learning approach based on graph neural networks. We show that the approach can re-detect specialized tissue niches in previously published data, and that our proposed cell classification leads to niche definitions that may be relevant for sub-groups of glioma, if applied to larger data sets

The clinical significance of the T2-FLAIR mismatch sign in grade II and III gliomas : a population-based study

BACKGROUND: The T2-FLAIR mismatch sign is an imaging finding highly suggestive of isocitrate dehydrogenase mutated (IDH-mut) 1p19q non-codeleted (non-codel) gliomas (astrocytomas). In previous studies, it has shown excellent specificity but limited sensitivity for IDH-mut astrocytomas. Whether the mismatch sign is a marker of a clinically relevant subtype of IDH-mut astrocytomas is unknown. METHODS: We included histopathologically verified supratentorial lower-grade gliomas (LGG) WHO grade II-III retrospectively during the period 2010-2016. In the period 2017-2018, patients with suspected LGG radiologically were prospectively included, and in this cohort other diagnoses than glioma could occur. Clinical, radiological and molecular data were collected. For clinical evaluation we included all patients with IDH-mut astrocytomas. In the 2010-2016 cohort DNA methylation analysis with Infinium MethylationEPIC BeadChip (Illumina) was performed for patients with an IDH-mut astrocytoma with available tissue. We aimed to examine the association of the T2-FLAIR mismatch sign with clinical factors and outcomes. Additionally, we evaluated the diagnostic reliability of the mismatch sign and its relation to methylation profiles. RESULTS: Out of 215 patients with LGG, 135 had known IDH-mutation and 1p19q codeletion status. Fifty patients had an IDH-mut astrocytoma and 12 of these (24.0%) showed a mismatch sign. The sensitivity and specificity of the mismatch sign for IDH-mut detection were 26.4 and 97.6%, respectively. There were no differences between patients with an IDH-mut astrocytoma with or without mismatch sign when grouped according to T2-FLAIR mismatch sign with respect to baseline characteristics, clinical outcomes and methylation profiles. The overall interrater agreement between neuroradiologist and clinical neurosurgeons for the T2-FLAIR mismatch sign was significant when all 215 MRI examination assessed (κ = 0.77, p < 0.001, N = 215). CONCLUSION: The T2-FLAIR mismatch sign in patients with an IDH-mut astrocytoma is not associated with clinical presentation or outcome. It seems unlikely that the IDH-mut astrocytomas with mismatch sign represent a specific subentity. Finally, we have validated that the T2-FLAIR mismatch sign is a reliable and specific marker of IDH-mut astrocytomas

WHO Grade Loses Its Prognostic Value in Molecularly Defined Diffuse Lower-Grade Gliomas.

Background: While molecular insights to diffuse lower-grade glioma (dLGG) have improved the basis for prognostication, most established clinical prognostic factors come from the pre-molecular era. For instance, WHO grade as a predictor for survival in dLGG with isocitrate dehydrogenase (IDH) mutation has recently been questioned. We studied the prognostic role of WHO grade in molecularly defined subgroups and evaluated earlier used prognostic factors in the current molecular setting. Material and Methods: A total of 253 adults with morphological dLGG, consecutively included between 2007 and 2018, were assessed. IDH mutations, codeletion of chromosomal arms 1p/19q, and cyclin-dependent kinase inhibitor 2A/B (CDKN2A/B) deletions were analyzed. Results: There was no survival benefit for patients with WHO grade 2 over grade 3 IDH-mut dLGG after exclusion of tumors with known CDKN2A/B homozygous deletion (n=157) (log-rank p=0.97). This was true also after stratification for oncological postoperative treatment and when astrocytomas and oligodendrogliomas were analyzed separately. In IDH-mut astrocytomas, residual tumor volume after surgery was an independent prognostic factor for survival (HR 1.02; 95% CI 1.01-1.03; p=0.003), but not in oligodendrogliomas (HR 1.02; 95% CI 1.00-1.03; p=0.15). Preoperative tumor size was an independent predictor in both astrocytomas (HR 1.03; 95% CI 1.00-1.05; p=0.02) and oligodendrogliomas (HR 1.05; 95% CI 1.01-1.09; p=0.01). Age was not a significant prognostic factor in multivariable analyses (astrocytomas p=0.64, oligodendrogliomas p=0.08). Conclusion: Our findings suggest that WHO grade is not a robust prognostic factor in molecularly well-defined dLGG. Preoperative tumor size remained a prognostic factor in both IDH-mut astrocytomas and oligodendrogliomas in our cohort, whereas residual tumor volume predicted prognosis in IDH-mut astrocytomas only. The age cutoffs for determining high risk in patients with IDH-mut dLGG from the pre-molecular era are not supported by our results

Supratentorial CNS-PNETs in children; a Swedish population-based study with molecular re-evaluation and long-term follow-up

Background: Molecular analyses have shown that tumours diagnosed as supratentorial primitive neuro-ectodermal tumours of the central nervous system (CNS-PNETs) in the past represent a heterogenous group of rare childhood tumours including high-grade gliomas (HGG), ependymomas, atypical teratoid/rhabdoid tumours (AT/RT), CNS neuroblastoma with forkhead box R2 (FOXR2) activation and embryonal tumour with multi-layered rosettes (ETMR). All these tumour types are rare and long-term clinical follow-up data are sparse. We retrospectively re-evaluated all children (0-18 years old) diagnosed with a CNS-PNET in Sweden during 1984-2015 and collected clinical data. Methods: In total, 88 supratentorial CNS-PNETs were identified in the Swedish Childhood Cancer Registry and from these formalin-fixed paraffin-embedded tumour material was available for 71 patients. These tumours were histopathologically re-evaluated and, in addition, analysed using genome-wide DNA methylation profiling and classified by the MNP brain tumour classifier. Results: The most frequent tumour types, after histopathological re-evaluation, were HGG (35%) followed by AT/RT (11%), CNS NB-FOXR2 (10%) and ETMR (8%). DNA methylation profiling could further divide the tumours into specific subtypes and with a high accuracy classify these rare embryonal tumours. The 5 and 10-year overall survival (OS) for the whole CNS-PNET cohort was 45% +/- 12% and 42% +/- 12%, respectively. However, the different groups of tumour types identified after re-evaluation displayed very variable survival patterns, with a poor outcome for HGG and ETMR patients with 5-year OS 20% +/- 16% and 33% +/- 35%, respectively. On the contrary, high PFS and OS was observed for patients with CNS NB-FOXR2 (5-year 100% for both). Survival rates remained stable even after 15-years of follow-up. Conclusions: Our findings demonstrate, in a national based setting, the molecular heterogeneity of these tumours and show that DNA methylation profiling of these tumours provides an indispensable tool in distinguishing these rare tumours. Long-term follow-up data confirms previous findings with a favourable outcome for CNS NB-FOXR2 tumours and poor chances of survival for ETMR and HGG

Discovery of a rare GKAP1-NTRK2 fusion in a pediatric low-grade glioma, leading to targeted treatment with TRK-inhibitor larotrectinib

Here we report a case of an 11-year-old girl with an inoperable tumor in the optic chiasm/hypothalamus, who experienced several tumor progressions despite three lines of chemotherapy treatment. Routine clinical examination classified the tumor as a BRAF-negative pilocytic astrocytoma. Copy-number variation profiling of fresh frozen tumor material identified two duplications in 9q21.32–33 leading to breakpoints within the GKAP1 and NTRK2 genes. RT-PCR Sanger sequencing revealed a GKAP1-NTRK2 exon 10–16 in-frame fusion, generating a putative fusion protein of 658 amino acids with a retained tyrosine kinase (TK) domain. Functional analysis by transient transfection of HEK293 cells showed the GKAP1-NTRK2 fusion protein to be activated through phosphorylation of the TK domain (Tyr705). Subsequently, downstream mediators of the MAPK- and PI3K-signaling pathways were upregulated in GKAP1-NTRK2 cells compared to NTRK2 wild-type; phosphorylated (p)ERK (3.6-fold), pAKT (1.8- fold), and pS6 ribosomal protein (1.4-fold). Following these findings, the patient was enrolled in a clinical trial and treated with the specific TRK-inhibitor larotrectinib, resulting in the arrest of tumor growth. The patient’s condition is currently stable and the quality of life has improved significantly. Our findings highlight the value of comprehensive clinical molecular screening of BRAF-negative pediatric low-grade gliomas, to reveal rare fusions serving as targets for precision therapy. CC BY-NC-ND 4.0© 2021 The Author(s). Published with license by Taylor &amp; Francis Group, LLC.</p