Refinement of prognostication for IDH-mutant astrocytomas using DNA methylation-based classification.

The 2021 World Health Organization (WHO) grading system of isocitrate dehydrogenase (IDH)-mutant astrocytomas relies on histological features and the presence of homozygous deletion of the cyclin-dependent kinase inhibitor 2A and 2B (CDKN2A/B). DNA methylation profiling has become highly relevant in the diagnosis of central nervous system (CNS) tumors including gliomas, and it has been incorporated into routine clinical diagnostics in some countries. In this study, we, therefore, examined the value of DNA methylation-based classification for prognostication of patients with IDH-mutant astrocytomas. We analyzed histopathological diagnoses, genome-wide DNA methylation array data, and chromosomal copy number alteration profiles from a cohort of 385 adult-type IDH-mutant astrocytomas, including a local cohort of 127 cases and 258 cases from public repositories. Prognosis based on WHO 2021 CNS criteria (histological grade and CDKN2A/B homozygous deletion status), other relevant chromosomal/gene alterations in IDH-mutant astrocytomas and DNA methylation-based subclassification according to the molecular neuropathology classifier were assessed. We demonstrate that DNA methylation-based classification of IDH-mutant astrocytomas can be used to predict outcome of the patients equally well as WHO 2021 CNS criteria. In addition, methylation-based subclassification enabled the identification of IDH-mutant astrocytoma patients with poor survival among patients with grade 3 tumors and patients with grade 4 tumors with a more favorable outcome. In conclusion, DNA methylation-based subclassification adds prognostic information for IDH-mutant astrocytomas that can further refine the current WHO 2021 grading scheme for these patients.

Diagnostic Yield From a Nationwide Implementation of Precision Medicine for all Children With Cancer.

PURPOSE: Several studies have indicated that broad genomic characterization of childhood cancer provides diagnostically and/or therapeutically relevant information in selected high-risk cases. However, the extent to which such characterization offers clinically actionable data in a prospective broadly inclusive setting remains largely unexplored. METHODS: We implemented prospective whole-genome sequencing (WGS) of tumor and germline, complemented by whole-transcriptome sequencing (RNA-Seq) for all children diagnosed with a primary or relapsed solid malignancy in Sweden. Multidisciplinary molecular tumor boards were set up to integrate genomic data in the clinical decision process along with a medicolegal framework enabling secondary use of sequencing data for research purposes. RESULTS: During the study's first 14 months, 118 solid tumors from 117 patients were subjected to WGS, with complementary RNA-Seq for fusion gene detection in 52 tumors. There was no significant geographic bias in patient enrollment, and the included tumor types reflected the annual national incidence of pediatric solid tumor types. Of the 112 tumors with somatic mutations, 106 (95%) exhibited alterations with a clear clinical correlation. In 46 of 118 tumors (39%), sequencing only corroborated histopathological diagnoses, while in 59 cases (50%), it contributed to additional subclassification or detection of prognostic markers. Potential treatment targets were found in 31 patients (26%), most commonly ALK mutations/fusions (n = 4), RAS/RAF/MEK/ERK pathway mutations (n = 14), FGFR1 mutations/fusions (n = 5), IDH1 mutations (n = 2), and NTRK2 gene fusions (n = 2). In one patient, the tumor diagnosis was revised based on sequencing. Clinically relevant germline variants were detected in 8 of 94 patients (8.5%). CONCLUSION: Up-front, large-scale genomic characterization of pediatric solid malignancies provides diagnostically valuable data in the majority of patients also in a largely unselected cohort.

Tailoring vascular phenotype through AAV therapy promotes anti-tumor immunity in glioma.

Glioblastomas are aggressive brain tumors that are largely immunotherapy resistant. This is associated with immunosuppression and a dysfunctional tumor vasculature, which hinder T cell infiltration. LIGHT/TNFSF14 can induce high endothelial venules (HEVs) and tertiary lymphoid structures (TLS), suggesting that its therapeutic expression could promote T cell recruitment. Here, we use a brain endothelial cell-targeted adeno-associated viral (AAV) vector to express LIGHT in the glioma vasculature (AAV-LIGHT). We found that systemic AAV-LIGHT treatment induces tumor-associated HEVs and T cell-rich TLS, prolonging survival in αPD-1-resistant murine glioma. AAV-LIGHT treatment reduces T cell exhaustion and promotes TCF1+CD8+ stem-like T cells, which reside in TLS and intratumoral antigen-presenting niches. Tumor regression upon AAV-LIGHT therapy correlates with tumor-specific cytotoxic/memory T cell responses. Our work reveals that altering vascular phenotype through vessel-targeted expression of LIGHT promotes efficient anti-tumor T cell responses and prolongs survival in glioma. These findings have broader implications for treatment of other immunotherapy-resistant cancers.

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.

Longitudinal DNA methylation analysis of adult-type IDH-mutant gliomas.

Diffuse gliomas are the most prevalent malignant primary brain tumors in adults and remain incurable despite standard therapy. Tumor recurrence is currently inevitable, which contributes to a persistent high morbidity and mortality in these patients. In this study, we examined the genome-wide DNA methylation profiles of primary and recurrent adult-type IDH-mutant gliomas to elucidate DNA methylation changes associated with tumor progression (with or without malignant transformation). We analyzed DNA methylation profiles of 37 primary IDH-mutant gliomas and 42 paired recurrences using the DNA methylation EPIC beadChip array. DNA methylation-based classification reflected the tumor progression over time. We observed a methylation subtype switch in a proportion of IDH-mutant astrocytomas; the primary tumors were subclassified as low-grade astrocytomas, which progressed to high-grade astrocytomas in the recurrent tumors. The CNS WHO grade 4 IDH-mutant astrocytomas did not always resemble methylation subclasses of higher grades. The number of differentially methylated CpG sites increased over time, and astrocytomas accumulated more differentially methylated CpG sites than oligodendrogliomas during tumor progression. Few differentially methylated CpG sites were shared between patients. We demonstrated that DNA methylation profiles are mostly maintained during IDH-mutant glioma progression, but CpG site-specific methylation alterations can occur.

DNA methylation profiling improves routine diagnosis of paediatric central nervous system tumours: A prospective population-based study.

AIMS: Paediatric brain tumours are rare, and establishing a precise diagnosis can be challenging. Analysis of DNA methylation profiles has been shown to be a reliable method to classify central nervous system (CNS) tumours with high accuracy. We aimed to prospectively analyse CNS tumours diagnosed in Sweden, to assess the clinical impact of adding DNA methylation-based classification to standard paediatric brain tumour diagnostics in an unselected cohort. METHODS: All CNS tumours diagnosed in children (0-18 years) during 2017-2020 were eligible for inclusion provided sufficient tumour material was available. Tumours were analysed using genome-wide DNA methylation profiling and classified by the MNP brain tumour classifier. The initial histopathological diagnosis was compared with the DNA methylation-based classification. For incongruent results, a blinded re-evaluation was performed by an experienced neuropathologist. RESULTS: Two hundred forty tumours with a histopathology-based diagnosis were profiled. A high-confidence methylation score of 0.84 or more was reached in 78% of the cases. In 69%, the histopathological diagnosis was confirmed, and for some of these also refined, 6% were incongruent, and the re-evaluation favoured the methylation-based classification. In the remaining 3% of cases, the methylation class was non-contributory. The change in diagnosis would have had a direct impact on the clinical management in 5% of all patients. CONCLUSIONS: Integrating DNA methylation-based tumour classification into routine clinical analysis improves diagnostics and provides molecular information that is important for treatment decisions. The results from methylation profiling should be interpreted in the context of clinical and histopathological information.

DNA methylation alterations across time and space in paediatric brain tumours.

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.

Spatial heterogeneity in DNA methylation and chromosomal alterations in diffuse gliomas and meningiomas.

Adult-type diffuse gliomas and meningiomas are the most common primary intracranial tumors of the central nervous system. DNA methylation profiling is a novel diagnostic technique increasingly used also in the clinic. Although molecular heterogeneity is well described in these tumors, DNA methylation heterogeneity is less studied. We therefore investigated the intratumor genetic and epigenetic heterogeneity in diffuse gliomas and meningiomas, with focus on potential clinical implications. We further investigated tumor purity as a source for heterogeneity in the tumors. We analyzed genome-wide DNA methylation profiles generated from 126 spatially separated tumor biopsies from 39 diffuse gliomas and meningiomas. Moreover, we evaluated five methods for measurement of tumor purity and investigated intratumor heterogeneity by assessing DNA methylation-based classification, chromosomal copy number alterations and molecular markers. Our results demonstrated homogeneous methylation-based classification of IDH-mutant gliomas and further corroborates subtype heterogeneity in glioblastoma IDH-wildtype and high-grade meningioma patients after excluding samples with low tumor purity. We detected a large number of differentially methylated CpG sites within diffuse gliomas and meningiomas, particularly in tumors of higher grades. The presence of CDKN2A/B homozygous deletion differed in one out of two patients with IDH-mutant astrocytomas, CNS WHO grade 4. We conclude that diffuse gliomas and high-grade meningiomas are characterized by intratumor heterogeneity, which should be considered in clinical diagnostics and in the assessment of methylation-based and molecular markers.

Agonistic CD40 therapy induces tertiary lymphoid structures but impairs responses to checkpoint blockade in glioma.

Gliomas are brain tumors characterized by an immunosuppressive microenvironment. Immunostimulatory agonistic CD40 antibodies (αCD40) are in clinical development for solid tumors, but are yet to be evaluated for glioma. Here, we demonstrate that systemic delivery of αCD40 in preclinical glioma models induces the formation of tertiary lymphoid structures (TLS) in proximity of meningeal tissue. In treatment-naïve glioma patients, the presence of TLS correlates with increased T cell infiltration. However, systemic delivery of αCD40 induces hypofunctional T cells and impairs the response to immune checkpoint inhibitors in pre-clinical glioma models. This is associated with a systemic induction of suppressive CD11b+ B cells post-αCD40 treatment, which accumulate in the tumor microenvironment. Our work unveils the pleiotropic effects of αCD40 therapy in glioma and reveals that immunotherapies can modulate TLS formation in the brain, opening up for future opportunities to regulate the immune response.

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.

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.

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.

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.

TGF-ß1 Suppresses Proliferation and Induces Differentiation in Human iPSC Neural in vitro Models.

Persistent neural stem cell (NSC) proliferation is, among others, a hallmark of immaturity in human induced pluripotent stem cell (hiPSC)-based neural models. TGF-ß1 is known to regulate NSCs in vivo during embryonic development in rodents. Here we examined the role of TGF-ß1 as a potential candidate to promote in vitro differentiation of hiPSCs-derived NSCs and maturation of neuronal progenies. We present that TGF-ß1 is specifically present in early phases of human fetal brain development. We applied confocal imaging and electrophysiological assessment in hiPSC-NSC and 3D neural in vitro models and demonstrate that TGF-ß1 is a signaling protein, which specifically suppresses proliferation, enhances neuronal and glial differentiation, without effecting neuronal maturation. Moreover, we demonstrate that TGF-ß1 is equally efficient in enhancing neuronal differentiation of human NSCs as an artificial synthetic small molecule. The presented approach provides a proof-of-concept to replace artificial small molecules with more physiological signaling factors, which paves the way to improve the physiological relevance of human neural developmental in vitro models.

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.

Platelet-derived growth factor receptor α/glial fibrillary acidic protein expressing peritumoral astrocytes associate with shorter median overall survival in glioblastoma patients.

The microenvironment and architecture of peritumoral tissue have been suggested to affect permissiveness for infiltration of malignant cells. Astrocytes constitute a heterogeneous population of cells and have been linked to proliferation, migration, and drug sensitivity of glioblastoma (GBM) cells. Through double-immunohistochemical staining for platelet-derived growth factor receptor α (PDGFRα) and glial fibrillary acidic protein (GFAP), this study explored the intercase variability among 45 human GBM samples regarding density of GFAP+ peritumoral astrocytes and a subset of GFAP+ peritumoral astrocyte-like cells also expressing PDGFRα. Large intercase variability regarding the total peritumoral astrocyte density and the density of PDGFRα+/GFAP+ peritumoral astrocyte-like cells was detected. DNA fluorescence in situ hybridization analyses for commonly altered genetic tumor markers supported the interpretation that these cells represented a genetically unaffected host cell subset referred to as PDGFRα+/GFAP+ peritumoral astrocytes. The presence of PDGFRα+/GFAP+ peritumoral astrocytes was significantly positively correlated to older patient age and peritumoral astrocyte density, but not to other established prognostic factors. Notably, presence of PDGFRα+/GFAP+ peritumoral astrocytes, but not peritumoral astrocyte density, was associated with significantly shorter patient overall survival. The prognostic association of PDGFRα+/GFAP+ peritumoral astrocytes was confirmed in multivariable analyses. This exploratory study thus demonstrates previously unrecognized intercase variability and prognostic significance of peritumoral abundance of a novel PDGFRα+ subset of GFAP+ astrocytes. Findings suggest clinically relevant roles of the microenvironment of peritumoral GBM tissue and encourage further characterization of the novel astrocyte subset with regard to origin, function, and potential as biomarker and drug target.