CpG-biomarkers in tumor tissue and prediction models for the survival of colorectal cancer: A systematic review and external validation study.

The research aimed to identify previously published CpG-methylation-based prognostic biomarkers and prediction models for colorectal cancer (CRC) prognosis and validate them in a large external cohort. A systematic search was conducted, analyzing 298 unique CpGs and 12 CpG-based prognostic models from 28 studies. After adjustment for clinical variables, 48 CpGs and five prognostic models were confirmed to be associated with survival. However, the discrimination ability of the models was insufficient, with area under the receiver operating characteristic curves ranging from 0.53 to 0.62. Calibration accuracy was mostly poor, and no significant added prognostic value beyond traditional clinical variables was observed. All prognostic models were rated at high risk of bias. While a fraction of CpGs showed potential clinical utility and generalizability, the CpG-based prognostic models performed poorly and lacked clinical relevance.

DNA-methylome-assisted classification of patients with poor prognostic subventricular zone associated IDH-wildtype glioblastoma.

Glioblastoma (GBM) derived from the "stem cell" rich subventricular zone (SVZ) may constitute a therapy-refractory subgroup of tumors associated with poor prognosis. Risk stratification for these cases is necessary but is curtailed by error prone imaging-based evaluation. Therefore, we aimed to establish a robust DNA methylome-based classification of SVZ GBM and subsequently decipher underlying molecular characteristics. MRI assessment of SVZ association was performed in a retrospective training set of IDH-wildtype GBM patients (n = 54) uniformly treated with postoperative chemoradiotherapy. DNA isolated from FFPE samples was subject to methylome and copy number variation (CNV) analysis using Illumina Platform and cnAnalysis450k package. Deep next-generation sequencing (NGS) of a panel of 130 GBM-related genes was conducted (Agilent SureSelect/Illumina). Methylome, transcriptome, CNV, MRI, and mutational profiles of SVZ GBM were further evaluated in a confirmatory cohort of 132 patients (TCGA/TCIA). A 15 CpG SVZ methylation signature (SVZM) was discovered based on clustering and random forest analysis. One third of CpG in the SVZM were associated with MAB21L2/LRBA. There was a 14.8% (n = 8) discordance between SVZM vs. MRI classification. Re-analysis of these patients favored SVZM classification with a hazard ratio (HR) for OS of 2.48 [95% CI 1.35-4.58], p = 0.004 vs. 1.83 [1.0-3.35], p = 0.049 for MRI classification. In the validation cohort, consensus MRI based assignment was achieved in 62% of patients with an intraclass correlation (ICC) of 0.51 and non-significant HR for OS (2.03 [0.81-5.09], p = 0.133). In contrast, SVZM identified two prognostically distinct subgroups (HR 3.08 [1.24-7.66], p = 0.016). CNV alterations revealed loss of chromosome 10 in SVZM- and gains on chromosome 19 in SVZM- tumors. SVZM- tumors were also enriched for differentially mutated genes (p < 0.001). In summary, SVZM classification provides a novel means for stratifying GBM patients with poor prognosis and deciphering molecular mechanisms governing aggressive tumor phenotypes.

Tumor DNA-methylome derived epigenetic fingerprint identifies HPV-negative head and neck patients at risk for locoregional recurrence after postoperative radiochemotherapy.

Biomarkers with relevance for loco-regional therapy are needed in human papillomavirus negative aka HPV(-) head and neck squamous cell carcinoma (HNSCC). Based on the premise that DNA methylation pattern is highly conserved, we sought to develop a reliable and robust methylome-based classifier identifying HPV(-) HNSCC patients at risk for loco-regional recurrence (LR) and all-event progression after postoperative radiochemotherapy (PORT-C). The training cohort consisted of HPV-DNA negative HNSCC patients (n = 128) homogeneously treated with PORT-C in frame of the German Cancer Consortium-Radiation Oncology Group (DKTK-ROG) multicenter biomarker trial. DNA Methylation analysis was performed using Illumina 450 K and 850 K-EPIC microarray technology. The performance of the classifier was integrated with a series of biomarkers studied in the training set namely hypoxia-, 5-microRNA (5-miR), stem-cell gene-expression signatures and immunohistochemistry (IHC)-based immunological characterization of tumors (CD3/CD8/PD-L1/PD1). Validation occurred in an independent cohort of HPV(-) HNSCC patients, pooled from two German centers (n = 125). We identified a 38-methylation probe-based HPV(-) Independent Classifier of disease Recurrence (HICR) with high prognostic value for LR, distant metastasis and overall survival (P < 10-9 ). HICR remained significant after multivariate analysis adjusting for anatomical site, lymph node extracapsular extension (ECE) and size (T-stage). HICR high-risk tumors were enriched for younger patients with hypoxic tumors (15-gene signature) and elevated 5-miR score. After adjustment for hypoxia and 5-miR covariates, HICR maintained predicting all endpoints. HICR provides a novel mean for assessing the risk of LR in HPV(-) HNSCC patients treated with PORT-C and opens a new opportunity for biomarker-assisted stratification and therapy adaptation in these patients.

Integrated Molecular-Morphologic Meningioma Classification: A Multicenter Retrospective Analysis, Retrospectively and Prospectively Validated.

PURPOSE: Meningiomas are the most frequent primary intracranial tumors. Patient outcome varies widely from benign to highly aggressive, ultimately fatal courses. Reliable identification of risk of progression for individual patients is of pivotal importance. However, only biomarkers for highly aggressive tumors are established (CDKN2A/B and TERT), whereas no molecularly based stratification exists for the broad spectrum of patients with low- and intermediate-risk meningioma. METHODS: DNA methylation data and copy-number information were generated for 3,031 meningiomas (2,868 patients), and mutation data for 858 samples. DNA methylation subgroups, copy-number variations (CNVs), mutations, and WHO grading were analyzed. Prediction power for outcome was assessed in a retrospective cohort of 514 patients, validated on a retrospective cohort of 184, and on a prospective cohort of 287 multicenter cases. RESULTS: Both CNV- and methylation family-based subgrouping independently resulted in increased prediction accuracy of risk of recurrence compared with the WHO classification (c-indexes WHO 2016, CNV, and methylation family 0.699, 0.706, and 0.721, respectively). Merging all risk stratification approaches into an integrated molecular-morphologic score resulted in further substantial increase in accuracy (c-index 0.744). This integrated score consistently provided superior accuracy in all three cohorts, significantly outperforming WHO grading (c-index difference P = .005). Besides the overall stratification advantage, the integrated score separates more precisely for risk of progression at the diagnostically challenging interface of WHO grade 1 and grade 2 tumors (hazard ratio 4.34 [2.48-7.57] and 3.34 [1.28-8.72] retrospective and prospective validation cohorts, respectively). CONCLUSION: Merging these layers of histologic and molecular data into an integrated, three-tiered score significantly improves the precision in meningioma stratification. Implementation into diagnostic routine informs clinical decision making for patients with meningioma on the basis of robust outcome prediction.

DNA Methylation-Based Estimates of Circulating Leukocyte Composition for Predicting Colorectal Cancer Survival: A Prospective Cohort Study.

Leukocytes are involved in the progression of colorectal cancer (CRC). The proportion of six major leukocyte subtypes can be estimated using epigenome-wide DNA methylation (DNAm) data from stored blood samples. Whether the composition of circulating leukocytes can be used as a prognostic factor is unclear. DNAm-based leukocyte proportions were obtained from a prospective cohort of 2206 CRC patients. Multivariate Cox regression models and survival curves were applied to assess associations between leukocyte composition and survival outcomes. A higher proportion of lymphocytes, including CD4+ T cells, CD8+ T cells, B cells, and NK cells, was associated with better survival, while a higher proportion of neutrophils was associated with poorer survival. CD4+ T cells outperformed other leukocytes in estimating the patients' prognosis. Comparing the highest quantile to the lowest quantile of CD4+ T cells, hazard ratios (95% confidence intervals) of all-cause and CRC-specific mortality were 0.59 (0.48, 0.72) and 0.59 (0.45, 0.77), respectively. Furthermore, the association of CD4+ T cells and prognosis was stronger among patients with early or intermediate CRC or patients with colon cancer. In conclusion, the composition of circulating leukocytes estimated from DNAm, particularly the proportions of CD4+ T cells, could be used as promising independent predictors of CRC survival.

Sarcoma classification by DNA methylation profiling.

Sarcomas are malignant soft tissue and bone tumours affecting adults, adolescents and children. They represent a morphologically heterogeneous class of tumours and some entities lack defining histopathological features. Therefore, the diagnosis of sarcomas is burdened with a high inter-observer variability and misclassification rate. Here, we demonstrate classification of soft tissue and bone tumours using a machine learning classifier algorithm based on array-generated DNA methylation data. This sarcoma classifier is trained using a dataset of 1077 methylation profiles from comprehensively pre-characterized cases comprising 62 tumour methylation classes constituting a broad range of soft tissue and bone sarcoma subtypes across the entire age spectrum. The performance is validated in a cohort of 428 sarcomatous tumours, of which 322 cases were classified by the sarcoma classifier. Our results demonstrate the potential of the DNA methylation-based sarcoma classification for research and future diagnostic applications.

A complementary study approach unravels novel players in the pathoetiology of Hirschsprung disease.

Hirschsprung disease (HSCR, OMIM 142623) involves congenital intestinal obstruction caused by dysfunction of neural crest cells and their progeny during enteric nervous system (ENS) development. HSCR is a multifactorial disorder; pathogenetic variants accounting for disease phenotype are identified only in a minority of cases, and the identification of novel disease-relevant genes remains challenging. In order to identify and to validate a potential disease-causing relevance of novel HSCR candidate genes, we established a complementary study approach, combining whole exome sequencing (WES) with transcriptome analysis of murine embryonic ENS-related tissues, literature and database searches, in silico network analyses, and functional readouts using candidate gene-specific genome-edited cell clones. WES datasets of two patients with HSCR and their non-affected parents were analysed, and four novel HSCR candidate genes could be identified: ATP7A, SREBF1, ABCD1 and PIAS2. Further rare variants in these genes were identified in additional HSCR patients, suggesting disease relevance. Transcriptomics revealed that these genes are expressed in embryonic and fetal gastrointestinal tissues. Knockout of these genes in neuronal cells demonstrated impaired cell differentiation, proliferation and/or survival. Our approach identified and validated candidate HSCR genes and provided further insight into the underlying pathomechanisms of HSCR.

Blood-derived DNA methylation predictors of mortality discriminate tumor and healthy tissue in multiple organs.

Evidence has shown that certain methylation markers derived from blood can mirror corresponding methylation signatures in internal tissues. In the current study, we aimed to investigate two strong epigenetic predictors for life span, derived from blood DNA methylation data, in tissue samples of solid cancer patients. Using data from the Cancer Genome Atlas (TCGA) and the German DACHS study, we compared a mortality risk score (MRscore) and DNAmPhenoAge in paired tumor and adjacent normal tissue samples of patients with lung (N = 69), colorectal (n = 299), breast (n = 90), head/neck (n = 50), prostate (n = 50), and liver (n = 50) cancer. To explore the concordance across tissue and blood, we additionally assessed the two markers in blood samples of colorectal cancer (CRC) cases and matched controls (n = 93) in the DACHS+ study. The MRscore was significantly elevated in tumor tissues compared to normal tissues of all cancers except prostate cancer, for which an opposite pattern was observed. DNAmPhenoAge was consistently higher in all tumor tissues. The MRscore discriminated lung, colorectal, and prostate tumor tissues from normal tissues with very high accuracy [AUCs of 0.87, 0.99 (TCGA) /0.94 (DACHS), and 0.92, respectively]. DNAmPhenoAge accurately discriminated five types of tumor tissues from normal tissues (except prostate cancer), with AUCs of 0.82-0.93. The MRscore was also significantly higher in blood samples of CRC cases than in controls, with areas under the curve (AUC) of 0.74, whereas DNAmPhenoAge did not distinguish cases from controls, with AUC of 0.54. This study provides compelling evidence that blood-derived DNAm markers could reflect methylation changes in less accessible tissues. Further research should explore the potential use of these findings for cancer diagnosis and early detection.

A prognostic CpG score derived from epigenome-wide profiling of tumor tissue was independently associated with colorectal cancer survival.

BACKGROUND: Results of previous studies on the association of the CpG island methylator phenotype (CIMP) with colorectal cancer (CRC) prognosis were inconsistent and mostly based on different CIMP definitions. The current study aimed to comprehensively investigate the associations between DNA methylation on genes previously used to define CIMP status with CRC survival. RESULTS: Patients with CRC followed up for a median of 5.2 years were divided into a study cohort (n = 568) and a validation cohort (n = 308). DNA methylation was measured in tumor tissue using the Illumina Infinium HumanMethylation450 BeadChip and restricted to 43 genes used to define CIMP status in previous studies. Cox proportional hazard regression models were used to estimate adjusted hazard ratios (HR) and 95% confidence intervals (CI) of survival after CRC, including adjustment for tumor stage, microsatellite instability, and BRAF mutation status. In the study cohort, ten CpG sites were identified to be associated with CRC survival. Seven of these ten CpG sites were also associated with CRC survival in the validation cohort and were used to construct a prognostic score. CRC patients with a prognostic score of the lowest methylation level showed poorer disease-specific survival compared with patients with the highest methylation level in both the study cohort and the validation cohort (HR = 3.11 and 95% CI = 1.97-4.91, and HR = 3.06 and 95% CI = 1.71-5.45, respectively). CONCLUSIONS: A CpG panel consisting of seven CpG sites was found to be strongly associated with CRC survival, independent from important clinical factors and mutations associated with CIMP. Further studies are required to confirm these findings.

Mutational patterns and regulatory networks in epigenetic subgroups of meningioma.

DNA methylation patterns delineate clinically relevant subgroups of meningioma. We previously established the six meningioma methylation classes (MC) benign 1-3, intermediate A and B, and malignant. Here, we set out to identify subgroup-specific mutational patterns and gene regulation. Whole genome sequencing was performed on 62 samples across all MCs and WHO grades from 62 patients with matched blood control, including 40 sporadic meningiomas and 22 meningiomas arising after radiation (Mrad). RNA sequencing was added for 18 of these cases and chromatin-immunoprecipitation for histone H3 lysine 27 acetylation (H3K27ac) followed by sequencing (ChIP-seq) for 16 samples. Besides the known mutations in meningioma, structural variants were found as the mechanism of NF2 inactivation in a small subset (5%) of sporadic meningiomas, similar to previous reports for Mrad. Aberrations of DMD were found to be enriched in MCs with NF2 mutations, and DMD was among the most differentially upregulated genes in NF2 mutant compared to NF2 wild-type cases. The mutational signature AC3, which has been associated with defects in homologous recombination repair (HRR), was detected in both sporadic meningioma and Mrad, but widely distributed across the genome in sporadic cases and enriched near genomic breakpoints in Mrad. Compared to the other MCs, the number of single nucleotide variants matching the AC3 pattern was significantly higher in the malignant MC, which also exhibited higher genomic instability, determined by the numbers of both large segments affected by copy number alterations and breakpoints between large segments. ChIP-seq analysis for H3K27ac revealed a specific activation of genes regulated by the transcription factor FOXM1 in the malignant MC. This analysis also revealed a super enhancer near the HOXD gene cluster in this MC, which, together with general upregulation of HOX genes in the malignant MC, indicates a role of HOX genes in meningioma aggressiveness. This data elucidates the biological mechanisms rendering different epigenetic subgroups of meningiomas, and suggests leveraging HRR as a novel therapeutic target.

Profiling of gallbladder carcinoma reveals distinct miRNA profiles and activation of STAT1 by the tumor suppressive miRNA-145-5p.

Gallbladder carcinoma (GBC) is a biliary tract cancer with few treatment options and poor prognosis. Radical surgery is the only potentially curative treatment option but most patients diagnosed with GBC are unresectable. Thus, there is a great need for the development of new treatment options including targeted therapy. Here, we aimed at identifying deregulated miRNAs and affected pathways involved in GBC development and progression. We performed global miRNA profiling of 40 GBC and 8 normal gallbladder tissues and identified large differences with 30% of miRNAs being differentially expressed (false discovery rate: FDR < 0.001). We found 24 miRNAs to be differentially regulated in GBC with poor outcome (p < 0.05) of which miR-145-5p was the most downregulated miRNA. Overexpression of miR-145-5p significantly reduced cell proliferation and colony formation. Gene expression analysis of cells expressing miR-145-5p mimics revealed activation of the Signal transducer and activator of transcription 1 (STAT1) signaling pathway which is mainly tumor suppressive. Furthermore, the activation of STAT1 by miR-145-5p was specifically observed in gallbladder carcinoma and cholangiocarcinoma but not in hepatocellular carcinoma cells. The Protein Tyrosine Phosphatase Receptor Type F (PTPRF) is downregulated upon miR-145 expression and may be involved in STAT1 regulation. In addition, we found that the STAT1-regulated protein IRF7 is downregulated in GBC compared to normal gallbladder tissue and low IRF7 expression is associated with significantly lower overall survival of GBC patients. Thus, this study identified GBC patient subgroups and provides new mechanistic insights in the tumor suppressive function of miR-145-5p leading to activation of STAT1 signaling.

Genome-wide methylation profiling and copy number analysis in atypical fibroxanthomas and pleomorphic dermal sarcomas indicate a similar molecular phenotype.

BACKGROUND: Atypical fibroxanthomas (AFX) and pleomorphic dermal sarcomas (PDS) are lesions of the skin with overlapping histologic features and unspecific molecular traits. PDS behaves aggressive compared to AFX. Thus, a precise delineation, although challenging in some instances, is relevant. METHODS: We examined the value of DNA-methylation profiling and copy number analysis for separating these tumors. DNA-methylation data were generated from 17 AFX and 15 PDS using the Illumina EPIC array. These were compared with DNA-methylation data generated from 196 tumors encompassing potential histologic mimics like cutaneous squamous carcinomas (cSCC; n = 19), basal cell carcinomas (n = 10), melanoma metastases originating from the skin (n = 11), leiomyosarcomas (n = 11), angiosarcomas of the skin and soft tissue (n = 11), malignant peripheral nerve sheath tumors (n = 19), dermatofibrosarcomas protuberans (n = 13), extraskeletal myxoid chondrosarcomas (n = 9), myxoid liposarcomas (n = 14), schwannomas (n = 10), neurofibromas (n = 21), alveolar (n = 19) and embryonal (n = 17) rhabdomyosarcomas as well as undifferentiated pleomorphic sarcomas (n = 12). RESULTS: DNA-methylation profiling did not separate AFX from PDS. The DNA-methylation profiles of the other cases, however, were distinct from AFX/PDS. They reliably assigned to subtype-specific DNA-methylation clusters, although overlap occurred between some AFX/PDS and cSCC. Copy number profiling revealed alterations in a similar frequency and distribution between AFX and PDS. They involved losses of 9p (22/32) and 13q (25/32). Gains frequently involved 8q (8/32). Notably, a homozygous deletion of CDKN2A was more frequent in PDS (6/15) than in AFX (2/17), whereas amplifications were non-recurrent and overall rare (5/32). CONCLUSIONS: Our findings support the concept that AFX and PDS belong to a common tumor spectrum. We could demonstrate the diagnostic value of DNA-methylation profiling to delineating AFX/PDS from potential mimics. However, the assessment of certain histologic features remains crucial for separating PDS from AFX.

MEST mediates the impact of prenatal bisphenol A exposure on long-term body weight development.

Background: Exposure to endocrine-disrupting chemicals can alter normal physiology and increase susceptibility to non-communicable diseases like obesity. Especially the prenatal and early postnatal period is highly vulnerable to adverse effects by environmental exposure, promoting developmental reprogramming by epigenetic alterations. To obtain a deeper insight into the role of prenatal bisphenol A (BPA) exposure in children's overweight development, we combine epidemiological data with experimental models and BPA-dependent DNA methylation changes. Methods: BPA concentrations were measured in maternal urine samples of the LINA mother-child-study obtained during pregnancy (n = 552), and BPA-associated changes in cord blood DNA methylation were analyzed by Illumina Infinium HumanMethylation450 BeadChip arrays (n = 472). Methylation changes were verified by targeted MassARRAY analyses, assessed for their functional translation by qPCR and correlated with children's body mass index (BMI) z scores at the age of 1 and 6 years. Further, female BALB/c mice were exposed to BPA from 1 week before mating until delivery, and weight development of their pups was monitored (n ≥ 8/group). Additionally, human adipose-derived mesenchymal stem cells were treated with BPA during the adipocyte differentiation period and assessed for exposure-related epigenetic, transcriptional and morphological changes (n = 4). Results: In prenatally BPA-exposed children two CpG sites with deviating cord blood DNA-methylation profiles were identified, among them a hypo-methylated CpG in the promoter of the obesity-associated mesoderm-specific transcript (MEST). A mediator analysis suggested that prenatal BPA exposure was connected to cord blood MEST promoter methylation and MEST expression as well as BMI z scores in early infancy. This effect could be confirmed in mice in which prenatal BPA exposure altered Mest promoter methylation and transcription with a concomitant increase in the body weight of the juvenile offspring. An experimental model of in vitro differentiated human mesenchymal stem cells also revealed an epigenetically induced MEST expression and enhanced adipogenesis following BPA exposure. Conclusions: Our study provides evidence that MEST mediates the impact of prenatal BPA exposure on long-term body weight development in offspring by triggering adipocyte differentiation.

Novel, improved grading system(s) for IDH-mutant astrocytic gliomas.

According to the 2016 World Health Organization Classification of Tumors of the Central Nervous System (2016 CNS WHO), IDH-mutant astrocytic gliomas comprised WHO grade II diffuse astrocytoma, IDH-mutant (AIIIDHmut), WHO grade III anaplastic astrocytoma, IDH-mutant (AAIIIIDHmut), and WHO grade IV glioblastoma, IDH-mutant (GBMIDHmut). Notably, IDH gene status has been made the major criterion for classification while the manner of grading has remained unchanged: it is based on histological criteria that arose from studies which antedated knowledge of the importance of IDH status in diffuse astrocytic tumor prognostic assessment. Several studies have now demonstrated that the anticipated differences in survival between the newly defined AIIIDHmut and AAIIIIDHmut have lost their significance. In contrast, GBMIDHmut still exhibits a significantly worse outcome than its lower grade IDH-mutant counterparts. To address the problem of establishing prognostically significant grading for IDH-mutant astrocytic gliomas in the IDH era, we undertook a comprehensive study that included assessment of histological and genetic approaches to prognosis in these tumors. A discovery cohort of 211 IDH-mutant astrocytic gliomas with an extended observation was subjected to histological review, image analysis, and DNA methylation studies. Tumor group-specific methylation profiles and copy number variation (CNV) profiles were established for all gliomas. Algorithms for automated CNV analysis were developed. All tumors exhibiting 1p/19q codeletion were excluded from the series. We developed algorithms for grading, based on molecular, morphological and clinical data. Performance of these algorithms was compared with that of WHO grading. Three independent cohorts of 108, 154 and 224 IDH-mutant astrocytic gliomas were used to validate this approach. In the discovery cohort several molecular and clinical parameters were of prognostic relevance. Most relevant for overall survival (OS) was CDKN2A/B homozygous deletion. Other parameters with major influence were necrosis and the total number of CNV. Proliferation as assessed by mitotic count, which is a key parameter in 2016 CNS WHO grading, was of only minor influence. Employing the parameters most relevant for OS in our discovery set, we developed two models for grading these tumors. These models performed significantly better than WHO grading in both the discovery and the validation sets. Our novel algorithms for grading IDH-mutant astrocytic gliomas overcome the challenges caused by introduction of IDH status into the WHO classification of diffuse astrocytic tumors. We propose that these revised approaches be used for grading of these tumors and incorporated into future WHO criteria.

DNA methylation-based classification of central nervous system tumours.

Accurate pathological diagnosis is crucial for optimal management of patients with cancer. For the approximately 100 known tumour types of the central nervous system, standardization of the diagnostic process has been shown to be particularly challenging-with substantial inter-observer variability in the histopathological diagnosis of many tumour types. Here we present a comprehensive approach for the DNA methylation-based classification of central nervous system tumours across all entities and age groups, and demonstrate its application in a routine diagnostic setting. We show that the availability of this method may have a substantial impact on diagnostic precision compared to standard methods, resulting in a change of diagnosis in up to 12% of prospective cases. For broader accessibility, we have designed a free online classifier tool, the use of which does not require any additional onsite data processing. Our results provide a blueprint for the generation of machine-learning-based tumour classifiers across other cancer entities, with the potential to fundamentally transform tumour pathology.

Array-based DNA-methylation profiling in sarcomas with small blue round cell histology provides valuable diagnostic information.

Undifferentiated solid tumors with small blue round cell histology and expression of CD99 mostly resemble Ewing sarcoma. However, they also may include other tumors such as mesenchymal chondrosarcoma, synovial sarcoma, or small cell osteosarcoma. Definitive classification usually requires detection of entity-specific mutations. While this approach identifies the majority of Ewing sarcomas, a subset of lesions remains unclassified and, therefore, has been termed "Ewing-like sarcomas" or small blue round cell tumors not otherwise specified. We developed an approach for further characterization of small blue round cell tumors not otherwise specified using an array-based DNA-methylation profiling approach. Data were analyzed by unsupervised clustering and t-distributed stochastic neighbor embedding analysis and compared with a reference methylation data set of 460 well-characterized prototypical sarcomas encompassing 18 subtypes. Verification was performed by additional FISH analyses, RNA sequencing from formalin-fixed paraffin-embedded material or immunohistochemical marker analyses. In a cohort of more than 1,000 tumors assumed to represent Ewing sarcomas, 30 failed to exhibit the typical EWS translocation. These tumors were subjected to methylation profiling and could be assigned to Ewing sarcoma in 14 (47%), to small blue round cell tumors with CIC alteration in 6 (20%), to small blue round cell tumors with BCOR alteration in 4 (13%), to synovial sarcoma and to malignant rhabdoid tumor in 2 cases each. One single case each was allotted to mesenchymal chondrosarcoma and adamantinoma. 12/14 tumors classified as Ewing sarcoma could be verified by demonstrating either a canonical EWS translocation evading initial testing, by identifying rare breakpoints or fusion partners. The methylation-based assignment of the remaining small blue round cell tumors not otherwise specified also could be verified by entity-specific molecular alterations in 13/16 cases. In conclusion, array-based DNA-methylation analysis of undifferentiated tumors with small blue round cell histology is a powerful tool for precisely classifying this diagnostically challenging tumor group.

Molecular differences in IDH wildtype glioblastoma according to MGMT promoter methylation.

Background: O6-methylguanine-DNA-methyltransferase (MGMT) promoter methylation status is a predictive biomarker in glioblastoma. We investigated whether this marker furthermore defines a molecularly distinct tumor subtype with clinically different outcome. Methods: We analyzed copy number variation (CNV) and methylation profiles of 1095 primary and 92 progressive isocitrate dehydrogenase wildtype glioblastomas, including paired samples from 49 patients. DNA mutation data from 182 glioblastoma samples of The Cancer Genome Atlas (TCGA) and RNA expression from 107 TCGA and 55 Chinese Glioma Genome Atlas samples were analyzed. Results: Among untreated glioblastomas, MGMT promoter methylated (mMGMT) and unmethylated (uMGMT) tumors did not show different CNV or specific gene mutations, but a higher mutation count in mMGMT tumors. We identified 3 methylation clusters. Cluster 1 showed the highest average methylation and was enriched for mMGMT tumors. Seventeen genes including gastrulation brain homeobox 2 (GBX2) were found to be hypermethylated and downregulated on the mRNA level in mMGMT tumors. In progressive glioblastomas, platelet derived growth factor receptor alpha (PDGFRA) and GLI2 amplifications were enriched in mMGMT tumors. Methylated MGMT tumors gain PDGFRA amplification of PDGFRA, whereas uMGMT tumors with amplified PDGFRA frequently lose this amplification upon progression. Glioblastoma patients surviving <6 months and with mMGMT harbored less frequent epidermal growth factor receptor (EGFR) amplifications, more frequent TP53 mutations, and a higher tumor necrosis factor-nuclear factor-kappaB (TNF-NFκB) pathway activation compared with patients surviving >12 months. Conclusions: MGMT promoter methylation status does not define a molecularly distinct glioblastoma subpopulation among untreated tumors. Progressive mMGMT glioblastomas and mMGMT tumors of patients with short survival tend to have more unfavorable molecular profiles.

Histone 3.3 hotspot mutations in conventional osteosarcomas: a comprehensive clinical and molecular characterization of six H3F3A mutated cases.

BACKGROUND: Histone 3.3 (H3.3) hotspot mutations in bone tumors occur in the vast majority of giant cell tumors of bone (GCTBs; 96%), chondroblastomas (95%) and in a few cases of osteosarcomas. However, clinical presentation, histopathological features, and additional molecular characteristics of H3.3 mutant osteosarcomas are largely unknown. METHODS: In this multicentre, retrospective study, a total of 106 conventional high-grade osteosarcomas, across all age groups were re-examined for hotspot mutations in the H3.3 coding genes H3F3A and H3F3B. H3.3 mutant osteosarcomas were re-evaluated in a multidisciplinary manner and analyzed for genome-wide DNA-methylation patterns and DNA copy number aberrations alongside H3.3 wild-type osteosarcomas and H3F3A G34W/L mutant GCTBs. RESULTS: Six osteosarcomas (6/106) carried H3F3A hotspot mutations. No mutations were found in H3F3B. All patients with H3F3A mutant osteosarcoma were older than 30 years with a median age of 65 years. Copy number aberrations that are commonly encountered in high-grade osteosarcomas also occurred in H3F3A mutant osteosarcomas. Unlike a single osteosarcoma with a H3F3A K27M mutation, the DNA methylation profiles of H3F3A G34W/R mutant osteosarcomas were clearly different from H3.3 wild-type osteosarcomas, but more closely related to GCTBs. The most differentially methylated promoters between H3F3A G34W/R mutant and H3.3 wild-type osteosarcomas were in KLLN/PTEN (p < 0.00005) and HIST1H2BB (p < 0.0005). CONCLUSIONS: H3.3 mutations in osteosarcomas may occur in H3F3A at mutational hotspots. They are overall rare, but become more frequent in osteosarcoma patients older than 30 years. Osteosarcomas carrying H3F3A G34W/R mutations are associated with epigenetic dysregulation of KLLN/PTEN and HIST1H2BB.