Methylation Class Research Articles

Human epidermal growth factor receptor 2/3 (HER2/HER3) expression in higher-grade meningioma.

e14063 Background: Meningiomas are the most frequently diagnosed primary central nervous system (CNS) tumors in adults. Although most meningiomas can be cured by resection, higher-grade lesions (CNS WHO grades 2 & 3) tend to recur, with limited systemic treatment options after exhaustion of local therapies. Antibody drug conjugates (ADCs) targeting human epidermal growth factor receptors 2 and 3 HER2/HER3) have shown remarkable clinical activity in solid tumors including breast cancer brain metastases and are under investigation in various malignancies. Methods: 64 patients with WHO grade 2 (atypical) and 3 (anaplastic) meningioma have been included. DNA methylation analysis has been performed using Illumina EPIC methylation arrays. Panel sequencing for NF2, PIK3CA, SMO, ARID1A, ARID1B, KLF4, SUFU, TERT promotor, and TRAF7 has been executed applying the Illumina NextSeq 500 platform. HER2 and HER3 expression was evaluated by immunohistochemical analysis using PATHWAY HER2 (4B5, Roche) and HER3 #12708 (Cell Signaling) antibodies on a Ventana Benchmark Ultra staining system. Results: In total, 44/64 (68.8%) patients with WHO grade 2 and 20/64 (31.2%) patients with WHO grade 3 meningioma were included. Median age at surgery was 60 years (range: 19-83), and 37/64 (57.8%) patients were female. DNA methylation classes according to the Molecular Neuropathology classifier were benign-1 in 10 (15.6%), benign-2 in 10 (15.6%), benign-3 in 4 (6.3%), intermediate-A in 26 (40.6%), intermediate-B in 4 (6.3%), and malignant in 10 (15.6%) out of 64 tumors. Weak membranous HER2 expression was observed in 1/64 (1.6%) tumor, which was categorized as WHO grade 3/intermediate-B meningioma characterized by infiltration of adjacent bone and fat tissue as well as positive Ki-67 staining of up to 39% of cells. Similarly, only one sample (1.6%) was HER3-positive which was diagnosed as WHO grade 2 tumor of methylation class benign-2, showing meningothelial morphology with elevated mitotic activity and a mutation in TRAF7. The single HER2+ as well as the HER3+ sample were from two distinct female patients. Conclusions: In our cohort, HER2 and HER3 were only infrequently expressed in a small subset of samples of different WHO grade, methylation class, and genetic background. Exploration of further targets of ADCs which are approved or under investigation in other tumors is currently ongoing.

Cancer signature ensemble integrating cfDNA methylation, copy number, and fragmentomic patterns for multi-cancer early detection.

e15040 Background: The use of cfDNA sequencing has demonstrated great potential for cancer screening; particularly, methylation signatures, copy number variations, and fragmentomic profiles have proven to be effective for identifying early cancer signals. However, most large-scale studies have only focused on either targeted methylation sites or whole-genome sequencing, limiting comprehensive analysis that integrates both epigenetic and genetic signatures. In this study, we present a platform for multi-cancer early detection that enables simultaneous analysis of whole-genome methylation, copy number, and fragmentomic patterns of cfDNA in a single assay. Methods: For a total of 950 plasma samples (361 healthy controls and 107 colon, 113 liver, 238 lung, and 131 prostate cancer) and 239 tissue samples, whole-genome methylation sequencing data were generated. Machine learning was conducted for multiple feature types engineered from cfDNA samples, and independent test performance was assessed. Results: A multi-feature cancer signature ensemble (CSE) classifier, integrating all features, outperformed single-feature classifiers. At 95.2% specificity, the cancer detection sensitivity with methylation, copy number, and fragmentomic models were 77.2% [CI 72-82], 61.4% [CI 56-67], and 60.5% [CI 55-66], respectively; but it was significantly increased to 87.7% [CI 84-91] with CSE ( p-value < 0.0001). For tracing the tissue of origin, CSE enhanced the accuracy beyond the methylation classifier, from 74.7% [CI 69-80] to 77.5% [CI 72-82]. Conclusions: This work proves the utility of a signature ensemble integrating epigenetic and genetic information for accurate cancer detection.

DIPG-like MYB-altered diffuse astrocytoma with durable response to intensive chemotherapy.

Pontine gliomas represent difficult to treat entity due to the location and heterogeneous biology varying from indolent low-grade gliomas to aggressive diffuse intrinsic pontine glioma (DIPG). Making the correct tumor diagnosis in the pontine location is thus critical. Here, we report a case study of a 14-month-old patient initially diagnosed as histone H3 wild-type DIPG. Due to the low age of the patient, the MRI appearance of DIPG, and anaplastic astrocytoma histology, intensive chemotherapy based on the HIT-SKK protocol with vinblastine maintenance chemotherapy was administered. Rapid clinical improvement and radiological regression of the tumor were observed with nearly complete remission with durable effect and excellent clinical condition more than 6.5years after diagnosis. Based on this unexpected therapeutic outcome, genome-wide DNA methylation array was employed and the sample was classified into the methylation class "Low-grade glioma, MYB(L1) altered." Additionally, RT-PCR revealed the presence of MYB::QKI fusion. Taken together, the histopathological classification, molecular-genetic and epigenetic features, clinical behavior, and pontine location have led us to reclassify the tumor as a pontine MYB-altered glioma. Our case demonstrates that more intensive chemotherapy can achieve long-term clinical effect in the treatment of MYB-altered pontine gliomas compared to previously used LGG-based regimens or radiotherapy. It also emphasizes the importance of a biopsy and a thorough molecular investigation of pontine lesions.

NKX3.1 immunohistochemistry and methylome profiling in mesenchymal chondrosarcoma: additional diagnostic value for a well-defined disease?

Mesenchymal chondrosarcoma (MCS) is a rare and highly aggressive tumour of soft tissue and bone that is defined by an underlying and highly specific fusion transcript involving HEY1 and NCOA2. Histologically, the tumours show a biphasic appearance consisting of an undifferentiated blue and round cell component as well as islands of highly differentiated cartilage. Particularly in core needle biopsies, the chondromatous component can be missed and the non-specific morphology and immunophenotype of the round cell component can cause diagnostic challenges. We applied NKX3.1 immunohistochemistry which was recently reported as a highly specific marker as well as methylome and copy number profiling to a set of 45 well characterised MCS cases to evaluate their potential diagnostic value. Methylome profiling revealed a highly distinct cluster for MCS. Notably, the findings were reproducible also when analysing the round cell and cartilaginous component separately. Furthermore, four outliers were identified by methylome profiling for which the diagnosis had to be revised. NKX3.1 immunohistochemistry showed positivity in 36% of tumours, the majority of which was rather focal and weak. Taken together, NKX3.1 expression showed a low sensitivity but a high specificity in our analysis. Methylome profiling on the other hand represents a sensitive, specific and reliable tool to support the diagnosis of MCS, particularly if only the round cell component is obtained in a biopsy and the diagnosis is not suspected. Furthermore, it can aid in confirming the diagnosis in case RNA sequencing for the HEY1::NCOA2 fusion transcript is not available.

Genomic profiles of IDH-mutant gliomas: MYCN-amplified IDH-mutant astrocytoma had the worst prognosis

This study aimed to find any ambiguous genetic outlier for “oligodendroglioma, IDH-mutant and 1p/19q-codeleted (O_IDH_mut)” and “astrocytoma, IDH-mutant (A_IDH_mut)” and to redefine the genetic landscape and prognostic factors of IDH-mutant gliomas. Next-generation sequencing (NGS) using a brain tumor-targeted gene panel, methylation profiles, and clinicopathological features were analyzed for O_IDH_mut (n = 74) in 70 patients and for A_IDH_mut (n = 95) in 90 patients. 97.3% of O_IDH_mut and 98.9% of A_IDH_mut displayed a classic genomic landscape. Combined CIC (75.7%) and/or FUBP1 (45.9%) mutations were detected in 93.2% and MGMTp methylation in 95.9% of O_IDH_mut patients. In A_IDH_mut, TP53 mutations were found in 86.3% and combined ATRX (82.1%) and TERTp (6.3%) mutations in 88.4%. Although there were 3 confusing cases, NOS (not otherwise specified) category, based on genetic profiles, but they were clearly classified by combining histopathology and DKFZ methylation classifier algorithms. The patients with MYCN amplification and/or CDKN2A/2B homozygous deletion in the A_IDH_mut category had a worse prognosis than those without these gene alterations and MYCN-amplified A_IDH_mut showed the worst prognosis. However, there was no prognostic genetic marker in O_IDH_mut. In histopathologically or genetically ambiguous cases, methylation profiles can be used as an objective tool to avoid a diagnosis of NOS or NEC (not elsewhere classified), as well as for tumor classification. The authors have not encountered a case of true mixed oligoastrocytoma using an integrated diagnosis of histopathological, genetic and methylation profiles. MYCN amplification, in addition to CDKN2A/2B homozygous deletion, should be included in the genetic criteria for CNS WHO grade 4 A_IDH_mut.

Abstract 1025: OvaPrint - a novel cfDNA methylation liquid biopsy for cancer risk assessment in high grade serous ovarian carcinoma

Abstract Background: High grade serous ovarian carcinoma (HGSOC) is a highly lethal gynecologic malignancy with a typical 5-year survival rate of 40% or less when diagnosed with late-stage disease. There is currently no single effective screening tool for high risk or community-based risk assessment for HGSOC and multivariate tests for preselected patients are suboptimal. In women with a known pelvic mass, surgery followed pathological assessment is currently the only definitive way to diagnose HGSOC. About 15% of women with a suspicious mass will have HGSOC and less than 15% will present with stage 1 cancer. A liquid biopsy assay based on cell-free (cf)DNA enables non-invasive dynamic assessment of disease status in patients with cancer where cfDNA methylation is particularly promising for detection of early stage HGSOC. The goal of the current study is to develop a cfDNA methylation liquid biopsy that can be used for the screening and risk assessment for HGSOC. Methods: Tissue and plasma samples were acquired under informed consent from multiple commercial and academic sources. Reduced representation bisulfite sequencing (RRBS) was performed on 33 HGSOC tissues as well as 8 normal ovary and 13 normal fallopian tube controls. Differentially methylated regions (DMRs) were called between HGSOC and normal controls using metilene and DSS. DMR calls with p-values < 0.05 and |αβ| > 0.45 (n = 1677 DMRs) were used to generate a targeted tissue-based methylation assay using the myBaits® hybrid probe capture platform (Daicel Arbor Biosciences). Next, targeted enrichment was performed on bisulfite converted plasma cfDNA on an independent set of 84 HGSOC samples (27 stage 1, 20 stage 2, 37 stage 3) and 100 samples from patients with benign ovarian masses. Mean beta value across DMRs were used to train a novel cfDNA methylation classifier model called OvaPrintTM to discriminate HGSOC from benign masses using a repeated 3-fold cross validation approach to obtain an unbiased estimate of the performance of the classifier. The average cross validated score for each sample was used to generate a receiver operator characteristic (ROC) curve. Results. RRBS analysis on HGSOC tissue and normal tissue controls demonstrated excellent separation of HGSOC from normal tissue samples using the selected DMRs. OvaPrintTM testing in an independent cohort of 184 plasma samples discriminated HGSOC from benign tumors with a high sensitivity and specificity (area under curve (AUC) = 0.931) using cfDNA methylation. Conclusions: OvaPrintTM is a novel cfDNA methylation liquid biopsy that can be used for effective cancer risk assessment for HGSOC in women presenting with pelvic masses. Citation Format: David N. Buckley, Gerald Gooden, Lee Shulman, Monica Newman, Mona Guo, Ben Yi Tew, Lynda Roman, Juan Pablo Lewinger, Bodour Salhia. OvaPrint - a novel cfDNA methylation liquid biopsy for cancer risk assessment in high grade serous ovarian carcinoma [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 1025.

892 Validation of Docetaxel as a Radiosensitizer in High-Risk Meningiomas Based on DNA Methylation Profiling

INTRODUCTION: Genome-wide methylation profiling has emerged as a transformative prognostic tool in meningiomas, and has identified discrete epigenetic clusters that share distinct clinical and biological features. The association of these signatures with underlying pathological mechanisms has not been well-explored. METHODS: From a collection of over two-hundred well-annotated tumors, we found 981 genes in which methylation signal was predictive of recurrence. Using pathway enrichment analysis, Docetaxel was identified as a candidate therapeutic agent; a medication that is frequently utilized in other common malignancies. This chemotherapy was validated in vitro and in vivo using patient derived meningiomas, and also tested in combination with radiotherapy. RESULTS: Based on 15 patient-derived cultures from our institution and 2 public cell lines, we found that Docetaxel could inhibit meningioma growth at concentrations that were favorable relative to other cancers. This drug triggered apoptosis in meningiomas of all tumor grades and methylation classes, with IC50 values ranging from 0.8 nm to 4.4 nm in vitro. Combining Docetaxel with radiation therapy resulted in synergistic cytotoxic effects on meningioma cultures, associated with elevated markers of cell death and dsDNA breaks. We confirmed our results via orthotopic meningioma models of the cell lines CH157 and IOMM-Lee, which exhibited dose-dependent improvements in mortality and tumor volume in response to Docetaxel and radiation. CONCLUSIONS: Our results leverage DNA methylation patterns to repurpose FDA-approved medications in the treatment of meningiomas, and suggest a clinical trial of Docetaxel with radiotherapy may be efficacious in aggressive lesions.

Ancestry dependent balancing selection of placental dysferlin at high-altitude.

Introduction: The placenta mediates fetal growth by regulating gas and nutrient exchange between the mother and the fetus. The cell type in the placenta where this nutrient exchange occurs is called the syncytiotrophoblast, which is the barrier between the fetal and maternal blood. Residence at high-altitude is strongly associated with reduced 3rd trimester fetal growth and increased rates of complications such as preeclampsia. We asked whether altitude and/or ancestry-related placental gene expression contributes to differential fetal growth under high-altitude conditions, as native populations have greater fetal growth than migrants to high-altitude. Methods: We have previously shown that methylation differences largely accounted for altitude-associated differences in placental gene expression that favor improved fetal growth among high-altitude natives. We tested for differences in DNA methylation between Andean and European placental samples from Bolivia [La Paz (∼3,600m) and Santa Cruz, Bolivia (∼400m)]. One group of genes showing significant altitude-related differences are those involved in cell fusion and membrane repair in the syncytiotrophoblast. Dysferlin (DYSF) shows greater expression levels in high- vs. low-altitude placentas, regardless of ancestry. DYSF has a single nucleotide variant (rs10166384;G/A) located at a methylation site that can potentially stimulate or repress DYSF expression. Following up with individual DNA genotyping in an expanded sample size, we observed three classes of DNA methylation that corresponded to individual genotypes of rs10166384 (A/A < A/G < G/G). We tested whether these genotypes are under Darwinian selection pressure by sequencing a ∼2.5kb fragment including the DYSF variants from 96 Bolivian samples and compared them to data from the 1000 genomes project. Results: We found that balancing selection (Tajima's D = 2.37) was acting on this fragment among Andeans regardless of altitude, and in Europeans at high-altitude (Tajima's D = 1.85). Discussion: This supports that balancing selection acting on dysferlin is capable of altering DNA methylation patterns based on environmental exposure to high-altitude hypoxia. This finding is analogous to balancing selection seen frequency-dependent selection, implying both alleles are advantageous in different ways depending on environmental circumstances. Preservation of the adenine (A) and guanine (G) alleles may therefore aid both Andeans and Europeans in an altitude dependent fashion.

Clinicopathological and molecular characterization of a case classified by DNA‑methylation profiling as “CNS embryonal tumor with BRD4–LEUTX fusion”

Central Nervous System (CNS) embryonal tumors represent a heterogeneous group of highly aggressive tumors occurring preferentially in children but also described in adolescents and adults. In 2021, the CNS World Health Organization (WHO) classification drastically changed the diagnosis of the other CNS embryonal tumors including new histo-molecular tumor types. Here, we report a pediatric case of a novel tumor type among the other CNS embryonal tumors classified within the methylation class “CNS Embryonal Tumor with BRD4–LEUTX Fusion”. The patient was a 4-year girl with no previous history of disease. For a few weeks, she suffered from headaches, vomiting and mild fever associated with increasing asthenia and loss of weight leading to a global deterioration of health. MRI brain examination revealed a large, grossly well-circumscribed tumoral mass lesion located in the left parietal lobe, contralateral hydrocephalus and midline shift. Microscopic examination showed a highly cellular tumor with a polymorphic aspect. The majority of the tumor harbored neuroectodermal features composed of small cells with scant cytoplasm and hyperchromatic nuclei associated with small “medulloblastoma-like” cells characterized by syncytial arrangement and focally a streaming pattern. Tumor cells were diffusely positive for Synaptophysin, CD56, INI1 and SMARCA4 associated with negativity for GFAP, OLIG-2, EMA, BCOR, LIN28A and MIC-2. Additional IHC features included p53 protein expression in more than 10% of the tumor’s cells and very interestingly, loss of H3K27me3 expression. The Heidelberg DNA-methylation classifier classified this case as “CNS Embryonal Tumor with BRD4:LEUTX Fusion”. RNA-sequencing analyses confirmed the BRD4 (exon 13)–LEUTX (exon 2) fusion with no other molecular alterations found by DNA sequencing. Our case report confirmed that a new subgroup of CNS embryonal tumor with high aggressive potential, loss of H3K27me3 protein expression, BRDA4–LEUTX fusion, named “Embryonal CNS tumor with BRD4–LEUTX fusion”, has to be considered into the new CNS WHO classification.

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.

A DNA methylation signature for the prediction of tumour recurrence in stage II colorectal cancer.

A major challenge in stage II colorectal carcinoma is to identify patients with increased risk of recurrence. Biomarkers that distinguish patients with poor prognosis from patients without recurrence are currently lacking. This study aims to develop a robust DNA methylation classifier that allows the prediction of recurrence and chemotherapy benefit in patients with stage II colorectal cancer. We performed a genome-wide DNA methylation capture sequencing in 243 stage II colorectal carcinoma samples and identified a relapse-specific DNA methylation signature consisting of eight CpG sites. Two hundred and forty-three patients with stage II CRC were enrolled in this study. In order to select differential methylation sites among recurrence and non-recurrence stage II CRC samples, DNA methylation profiles of 62 tumour samples including 31 recurrence and 31 nonrecurrence samples were analysed using the Agilent SureSelectXT Human Methyl-Seq, a comprehensive target enrichment system to analyse CpG methylation. Pyrosequencing was applied to quantify the methylation level of candidate DNA methylation sites in 243 patients. Least absolute shrinkage and selection operator (LASSO) method was employed to build the disease recurrence prediction classifier. We identified a relapse-related DNA methylation signature consisting of eight CpG sites in stage II CRC by DNA methylation capture sequencing. The classifier showed significantly higher prognostic accuracy than any clinicopathological risk factors. The Kaplan-Meier survival curve showed an association of high-risk score with poor prognosis. In multivariate analysis, the signature was the most significant prognosis factor, with an HR of 2.80 (95% CI, 1.71-4.58, P < 0.001). The signature could identify patients who are suitable candidates for adjuvant chemotherapy. An eight-CpG DNA methylation signature is a reliable prognostic and predictive tool for disease recurrence in patients with stage II CRC.

CNS tumor with EP300::BCOR fusion: discussing its prevalence in adult population

The Central Nervous System (CNS) tumor with BCOR internal tandem duplication (ITD) has recently been added as a novel embryonal histomolecular tumor type to the 2021 World Health Organization (WHO) Classification of CNS Tumors. In addition, other CNS tumors harboring a BCOR/BCORL1 fusion, which are defined by a distinct DNA-methylation profile, have been recently identified in the literature but clinical, radiological and histopathological data remain scarce. Herein, we present two adult cases of CNS tumors with EP300::BCOR fusion. These two cases presented radiological, histopathological, and immunohistochemical homologies with CNS tumors having BCOR ITD in children. To compare these tumors with different BCOR alterations, we performed a literature review with a meta-analysis. CNS tumors with EP300::BCOR fusion seem to be distinct from their BCOR ITD counterparts in terms of age, location, progression-free survival, tumor growth pattern, and immunopositivity for the BCOR protein. CNS tumors from the EP300::BCOR fusion methylation class in adults may be added to the future WHO classification.

Expanding the Molecular Diversity of CIC-Rearranged Sarcomas With Novel and Very Rare Partners

Capicua transcriptional repressor (CIC)-rearranged sarcoma represents a distinct pathologic entity and constitutes the second most prevalent category of undifferentiated round cell sarcomas (URCSs) after Ewing sarcoma. The 2 most common translocations are t(4;19) and t(10;19), resulting in CIC fusions with either DUX4 and DUX4L paralog, respectively; however, other rare variant fusions have also been reported. In this study, we expand the molecular spectrum of CIC-gene partners, reporting on 5 cases of URCSs showing CIC fusions with AXL, CITED1, SYK, and LEUTX by targeted RNA or DNA sequencing. There were 4 female patients and 1 male patient with a wide age range (12-70 years; median, 36 years). Four cases occurred in the deep soft tissues (lower extremity, 3; neck, 1) and 1 case in the central nervous system (midbrain/thalamus). All cases showed similar histologic findings within the spectrum of URCSs. Immunohistochemistry, showed variable positivity for ETV4 in 4 of the 4 cases and positive results for ERG in 3 of the 4 cases and for WT1 in 1 of the 4 cases. CD31 showed positivity in 2 of the 3 cases, including one coexpressing ERG. Unsupervised clustering of methylation profiles by T-distributed stochastic neighborhood embedding performed in 4 cases showed that all clustered tightly together and along the CIC sarcoma methylation class. RNA-sequencing data showed consistent upregulation of ETV1 and ETV4 mRNA in all cases examined, at similar levels to CIC::DUX4 URCSs. Our study expands the molecular diversity of CIC-rearranged URCSs to include novel and rare partners, providing morphologic, immunohistochemical, gene expression, and methylation evidence supporting their classification within the family of tumors harboring the more common DUX4/DUX4L partner genes.

Unveiling the identities of null cell tumours: Epigenomics corroborate subtle histological cues in pituitary neuroendocrine tumour/adenoma classification.

Pituitary neuroendocrine tumour (PitNET)/adenoma classification is based on cell lineage and requires immunopositivity for adenohypophysial hormones and/or transcription factors (TFs) SF1, TPIT, or PIT1. PitNET/adenomas lacking lineage affiliation are termed "null cell" tumours (NCTs). NCT diagnosis may be afflicted by methodological limitations and inconsistent diagnostic approaches. Previous studies have questioned the existence of true NCTs. In this study, we explore the epigenomic identities of PitNET/adenomas lacking clear TF-immunopositivity. 74 hormone-negative PitNET/adenomas were immunostained and scored for SF1, TPIT, and PIT1 expression. All tumours were classified as gonadotroph, corticotroph, PIT1-positive or "null cell". NCTs were subjected to global DNA methylation analysis. Epigenomic profiles of NCTs were compared to reference tumours using UMAP plotting and methylation-based classification. TF-immunostaining revealed definite lineage identity in 59 of 74 (79.7%) hormone-negative PitNET/adenomas. Of the remaining 15 NCTs, 13 demonstrated minimal and inconclusive nuclear SF1- or TPIT-expression (5 and 8, respectively). Two NCTs were entirely immunonegative. UMAP plotting and methylation-based classification demonstrated that the epigenomes of NCTs with minimal SF1- or TPIT-expression, were adequately affiliated with gonadotroph or corticotroph lineages, respectively. The two immunonegative NCTs were located near the corticotroph PitNET/adenomas via UMAP, while the methylation classifier could not match these two cases to predefined tumour classes. Epigenomic analyses substantiate lineage identification based on minimal TF-immunopositivity in PitNET/adenomas. This strategy dramatically decreases the incidence of NCTs and further challenges the legitimacy of NCTs as a distinct PitNET/adenoma subtype. Our study may be useful for guiding diagnostic efforts and future considerations of PitNET/adenoma classification.

Clinico-pathological and epigenetic heterogeneity of diffuse gliomas with FGFR3::TACC3 fusion

BackgroundGliomas with FGFR3::TACC3 fusion mainly occur in adults, display pathological features of glioblastomas (GB) and are usually classified as glioblastoma, IDH-wildtype. However, cases demonstrating pathological features of low-grade glioma (LGG) lead to difficulties in classification and clinical management. We report a series of 8 GB and 14 LGG with FGFR3:TACC3 fusion in order to better characterize them.MethodsCentralized pathological examination, search for TERT promoter mutation and DNA-methylation profiling were performed in all cases. Search for prognostic factors was done by the Kaplan–Meir method.ResultsTERT promoter mutation was recorded in all GB and 6/14 LGG. Among the 7 cases with a methylation score > 0.9 in the classifier (v12.5), 2 were classified as glioblastoma, 4 as ganglioglioma (GG) and 1 as dysembryoplastic neuroepithelial tumor (DNET). t-SNE analysis showed that the 22 cases clustered into three groups: one included 12 cases close to glioblastoma, IDH-wildtype methylation class (MC), 5 cases each clustered with GG or DNET MC but none with PLNTY MC. Unsupervised clustering analysis revealed four groups, two of them being clearly distinct: 5 cases shared age (< 40), pathological features of LGG, lack of TERT promoter mutation, FGFR3(Exon 17)::TACC3(Exon 10) fusion type and LGG MC. In contrast, 4 cases shared age (> 40), pathological features of glioblastoma, and were TERT-mutated. Relevant factors associated with a better prognosis were age < 40 and lack of TERT promoter mutation.ConclusionAmong gliomas with FGFR3::TACC3 fusion, age, TERT promoter mutation, pathological features, DNA-methylation profiling and fusion subtype are of interest to determine patients’ risk.

A High MCM6 Proliferative Index in Atypical Meningioma Is Associated with Shorter Progression Free and Overall Survivals.

The aim of this study was to evaluate the prognostic value of MCM6, in comparison with Ki-67, in two series of grade 1 and 2 meningiomas, and to evaluate its correlation with methylation classes. The first cohort included 100 benign (grade 1, World Health Organization 2021) meningiomas, and the second 69 atypical meningiomas (grade 2). Immunohistochemical Ki-67 and MCM6 labeling indices (LI) were evaluated independently by two observers. Among the atypical meningiomas, 33 cases were also studied by genome-wide DNA methylation. In grade 2 meningiomas, but not grade 1, both Ki-67 and MCM6 LIs were correlated with PFS (p = 0.004 and p = 0.005, respectively; Cox univariate analyses). Additionally, MCM6 was correlated with overall survival only in univariate analysis. In a multivariate model, including mitotic index, Ki-67, MCM6, age, sex, and the quality of surgical resection, only MCM6 was correlated with PFS (p = 0.046). Additionally, we found a significant correlation between PTEN loss and high MCM6 or Ki-67 LIs. Although no correlation was found with the methylation classes and subtypes returned by the meningioma algorithm MNGv2.4., MCM6 LI was significantly correlated with the methylation of 2 MCM6 gene body loci. In conclusion, MCM6 is a relevant prognostic marker in atypical meningiomas. This reproducible and easy-to-use marker allows the identification of a highly aggressive subtype of proliferative meningiomas, characterized notably by frequent PTEN losses, which was previously reported to be sensitive to histone deacetylase inhibitors.

Pediatric BCOR-Altered Tumors From Soft Tissue/Kidney Display Specific DNA Methylation Profiles

In the pediatric population, BCL6-correpresor gene (BCOR)–upregulated tumors include primitive myxoid mesenchymal tumors/undifferentiated sarcomas (PMMTI/UND), clear cell sarcomas of the kidney (CCSK), and high-grade neuroepithelial tumors (HG-NET). We investigated DNA methylation (DNAm) and copy number variation (CNV) profiling in these tumors (N = 34) using an Illumina EPIC BeadChip to better define the potential use of these tools to confirm diagnosis and predict outcomes. Twenty-seven tumors from 25 patients (age range, 0-10 years), showed molecular confirmation of genetic abnormalities as follows: BCOR internal tandem duplication in 14 PMMTI/UND, 8 CCSK, and 3 HG-NET and YWHAE fusions in 2 PMMTI/UND. The remaining 7 cases lacking informative molecular data were analyzed by immunophenotyping and were included in the study as a training cohort, clearly separated from the main study group. These were 4 PMMTI, 1 HG-NET, and 1 CCSK in which poor RNA preservation precluded the confirmation of BCOR rearrangements and 1 CCSK in which no rearrangements were found. DNAm data were compared with those of brain tumor and/or sarcoma classifier. Differentially methylated regions (DMRs) were analyzed in the 3 groups. Twenty-two cases of the 24 molecularly confirmed PMMTI/UND and CCSK and 3 of 6 of those with only immunophenotyping were classified within the methylation class “BCOR-altered sarcoma family” with optimal calibrated scores. PMMTI/UND and CCSK showed similar methylation profiles, whereas thousands of DMRs and significantly enriched pathways were evident between soft tissue/kidney tumors and HG-NET. The CNV analysis showed an overall flat profile in 19 of the 31 evaluable tumors (8/10 CCSK; 9/18 PMMTI/UND; 2/4 HG-NET). The most frequent CNVs were 1q gain and 9p and 10q loss. Follow-up time data were available for 20 patients: ≥2 CNV significantly correlated with a worse overall survival rate. In conclusion, soft tissue and kidney BCOR sarcomas matched with BCOR-altered sarcoma methylation class, whereas those from the brain matched with the central nervous system tumor classifier HG-NET BCOR, supporting the notion that DNAm profiling is an informative diagnostic tool. CNV alterations were associated with a more aggressive clinical behavior.

Predicting methylation class from diffusely infiltrating adult gliomas using multimodality MRI data.

Radiogenomic studies of adult-type diffuse gliomas have used magnetic resonance imaging (MRI) data to infer tumor attributes, including abnormalities such as IDH-mutation status and 1p19q deletion. This approach is effective but does not generalize to tumor types that lack highly recurrent alterations. Tumors have intrinsic DNA methylation patterns and can be grouped into stable methylation classes even when lacking recurrent mutations or copy number changes. The purpose of this study was to prove the principle that a tumor's DNA-methylation class could be used as a predictive feature for radiogenomic modeling. Using a custom DNA methylation-based classification model, molecular classes were assigned to diffuse gliomas in The Cancer Genome Atlas (TCGA) dataset. We then constructed and validated machine learning models to predict a tumor's methylation family or subclass from matched multisequence MRI data using either extracted radiomic features or directly from MRI images. For models using extracted radiomic features, we demonstrated top accuracies above 90% for predicting IDH-glioma and GBM-IDHwt methylation families, IDH-mutant tumor methylation subclasses, or GBM-IDHwt molecular subclasses. Classification models utilizing MRI images directly demonstrated average accuracies of 80.6% for predicting methylation families, compared to 87.2% and 89.0% for differentiating IDH-mutated astrocytomas from oligodendrogliomas and glioblastoma molecular subclasses, respectively. These findings demonstrate that MRI-based machine learning models can effectively predict the methylation class of brain tumors. Given appropriate datasets, this approach could generalize to most brain tumor types, expanding the number and types of tumors that could be used to develop radiomic or radiogenomic models.

Reference on copy number variations in pleomorphic xanthoastrocytoma: Implications for diagnostic approach.

Pleomorphic xanthoastrocytoma (PXA) poses a diagnostic challenge. The present study relies on methylation-based predictions and focuses on copy number variations (CNV) in PXA. We identified 551 tumors from patients having received the histologic diagnosis or differential diagnosis pleomorphic xanthoastrocytoma (PXA) uploaded to the web page www.molecularneuropathology.org. Of these 551 tumors, 165 received the prediction "methylation class (anaplastic) pleomorphic xanthoastrocytoma" with a calibrated score >=0.9 by the brain tumor classifier version v12.8 and, therefore, were defined the PXA reference set designated mcPXAref. In addition to these 165 mcPXAref, 767 other tumors received the prediction mcPXA with a calibrated score >=0.9 but without a histological PXA diagnosis. The total number of individual tumors predicted by histology and/or by methylome based classification as PXA, mcPXA or both was 1318, and these were designated the study cohort. The selection of a control cohort was guided by methylation-based predictions recurrently observed for the other 386/551 tumors diagnosed as histologic PXA. 131/386 received predictions for another entity besides PXA with a score >=0.9. Control tumors corresponding to the 11 most common other predictions were selected, adding up to 1100 reference cases. CNV profiles were calculated from all methylation datasets of the study and control cohorts. Special attention was given to the 7/10 signature, gene amplifications and homozygous deletion of CDKN2A/B. Comparison of CNV in the subsets of the study cohort and the control cohort were used to establish relations independent of histological diagnoses. Tumors in mcPXA were highly homogenous in regard to CNV alterations, irrespective of the histological diagnoses. The 7/10 signature commonly present in glioblastoma, IDH-wildtype, was present in 15-20% of mcPXA, whereas amplification of oncogenes (likewise common in glioblastoma) was very rare in mcPXA (<1%). In contrast, the histology-based PXA group exhibited high variance in regard to methylation classes as well as to CNVs. Our data add to the notion, that histologically defined PXA likely only represent a subset of the biological disease.

Clinical utility of whole-genome DNA methylation profiling as a primary molecular diagnostic assay for central nervous system tumors-A prospective study and guidelines for clinical testing.

Central nervous system (CNS) cancer is the 10th leading cause of cancer-associated deaths for adults, but the leading cause in pediatric patients and young adults. The variety and complexity of histologic subtypes can lead to diagnostic errors. DNA methylation is an epigenetic modification that provides a tumor type-specific signature that can be used for diagnosis. We performed a prospective study using DNA methylation analysis as a primary diagnostic method for 1921 brain tumors. All tumors received a pathology diagnosis and profiling by whole genome DNA methylation, followed by next-generation DNA and RNA sequencing. Results were stratified by concordance between DNA methylation and histopathology, establishing diagnostic utility. Of the 1602 cases with a World Health Organization histologic diagnosis, DNA methylation identified a diagnostic mismatch in 225 cases (14%), 78 cases (5%) did not classify with any class, and in an additional 110 (7%) cases DNA methylation confirmed the diagnosis and provided prognostic information. Of 319 cases carrying 195 different descriptive histologic diagnoses, DNA methylation provided a definitive diagnosis in 273 (86%) cases, separated them into 55 methylation classes, and changed the grading in 58 (18%) cases. DNA methylation analysis is a robust method to diagnose primary CNS tumors, improving diagnostic accuracy, decreasing diagnostic errors and inconclusive diagnoses, and providing prognostic subclassification. This study provides a framework for inclusion of DNA methylation profiling as a primary molecular diagnostic test into professional guidelines for CNS tumors. The benefits include increased diagnostic accuracy, improved patient management, and refinements in clinical trial design.