Methylation profiling: unmasking CAEBV's lymphoma connection.

<div><p>Dedifferentiated chondrosarcoma (DDCS) is a rare high-grade chondrosarcoma characterized by a well-differentiated chondrosarcoma (WDCS) component that abruptly transitions to a high-grade, noncartilaginous sarcomatous component. To date, the molecular pathogenesis of DDCS and its distinction from conventional chondrosarcoma remain poorly understood. By targeted sequencing, we examined the mutational and copy-number profiles of 18 DDCS, including macrodissected WDCS components, compared with 55 clinically sequenced conventional chondrosarcomas. In conjunction with publicly available external data, we analyzed the methylation and expression profiles of 34 DDCS and 94 conventional chondrosarcomas. Isocitrate dehydrogenase 1/isocitrate dehydrogenase 2 (<i>IDH1/IDH2)</i> mutations were present in 36% conventional chondrosarcomas and 71% DDCS. Compared with conventional chondrosarcomas, DDCS had higher frequencies of <i>TP53</i> and <i>TERT</i> promoter mutations and <i>CDKN2A/B</i> copy-number losses. Paired analysis of macrodissected WDCS and the high-grade components revealed <i>TERT</i> promoter mutations as early events. Despite phenotypic similarities, the percentage of genome with copy-number alterations in DDCS was significantly lower than that in other high-grade sarcomas. Differential methylation analysis revealed reduction of <i>IDH1/IDH2</i>-associated global hypermethylation characteristically seen in conventional chondrosarcoma and a distinct methylation profile in DDCS. The WDCS and high-grade components in DDCS showed similar methylation profiles. These CpG sites were associated with upregulated expression of genes involved in G<sub>2</sub>–M checkpoints and E2F targets. Genomic profiling revealed enrichment of <i>TP53</i>, <i>TERT</i> promoter, and <i>CDKN2A/B</i> alterations in DDCS. Integrated methylation and gene expression analysis revealed distinct <i>IDH1/IDH2</i>-associated methylation and transcriptional profiles as early events in DDCS, which may underlie the pathogenesis of dedifferentiation in chondrosarcomas.</p>Significance:<p>DDCS is a rare, high-grade chondrosarcoma with a dismal prognosis. About 50%–80% of DDCS harbor IDH1/IDH2 mutations. We uncover a significant alteration of IDH-associated methylation profile in DDCS, which we propose is key to the progression to dedifferentiation. In this context, the potential effect of the use of IDH inhibitors is unclear but important to address, as clinical trials of selective IDH1 inhibitors showed worse outcome in DDCS.</p></div>

Dedifferentiated chondrosarcoma (DDCS) is a rare high-grade chondrosarcoma characterized by a well-differentiated chondrosarcoma (WDCS) component that abruptly transitions to a high-grade, noncartilaginous sarcomatous component. To date, the molecular pathogenesis of DDCS and its distinction from conventional chondrosarcoma remain poorly understood. By targeted sequencing, we examined the mutational and copy-number profiles of 18 DDCS, including macrodissected WDCS components, compared with 55 clinically sequenced conventional chondrosarcomas. In conjunction with publicly available external data, we analyzed the methylation and expression profiles of 34 DDCS and 94 conventional chondrosarcomas. Isocitrate dehydrogenase 1/isocitrate dehydrogenase 2 (IDH1/IDH2) mutations were present in 36% conventional chondrosarcomas and 71% DDCS. Compared with conventional chondrosarcomas, DDCS had higher frequencies of TP53 and TERT promoter mutations and CDKN2A/B copy-number losses. Paired analysis of macrodissected WDCS and the high-grade components revealed TERT promoter mutations as early events. Despite phenotypic similarities, the percentage of genome with copy-number alterations in DDCS was significantly lower than that in other high-grade sarcomas. Differential methylation analysis revealed reduction of IDH1/IDH2-associated global hypermethylation characteristically seen in conventional chondrosarcoma and a distinct methylation profile in DDCS. The WDCS and high-grade components in DDCS showed similar methylation profiles. These CpG sites were associated with upregulated expression of genes involved in G2–M checkpoints and E2F targets. Genomic profiling revealed enrichment of TP53, TERT promoter, and CDKN2A/B alterations in DDCS. Integrated methylation and gene expression analysis revealed distinct IDH1/IDH2-associated methylation and transcriptional profiles as early events in DDCS, which may underlie the pathogenesis of dedifferentiation in chondrosarcomas.Significance:DDCS is a rare, high-grade chondrosarcoma with a dismal prognosis. About 50%–80% of DDCS harbor IDH1/IDH2 mutations. We uncover a significant alteration of IDH-associated methylation profile in DDCS, which we propose is key to the progression to dedifferentiation. In this context, the potential effect of the use of IDH inhibitors is unclear but important to address, as clinical trials of selective IDH1 inhibitors showed worse outcome in DDCS.

BackgroundThe clinical course of cutaneous melanoma (CM) can differ significantly for patients with identical stages of disease, defined clinico-pathologically, and no molecular markers differentiate patients with such a diverse prognosis. This study aimed to define the prognostic value of whole genome DNA methylation profiles in stage III CM.MethodsGenome-wide methylation profiles were evaluated by the Illumina Human Methylation 27 BeadChip assay in short-term neoplastic cell cultures from 45 stage IIIC CM patients. Unsupervised K-means partitioning clustering was exploited to sort patients into 2 groups based on their methylation profiles. Methylation patterns related to the discovered groups were determined using the nearest shrunken centroid classification algorithm. The impact of genome-wide methylation patterns on overall survival (OS) was assessed using Cox regression and Kaplan-Meier analyses.ResultsUnsupervised K-means partitioning by whole genome methylation profiles identified classes with significantly different OS in stage IIIC CM patients. Patients with a “favorable” methylation profile had increased OS (P = 0.001, log-rank = 10.2) by Kaplan-Meier analysis. Median OS of stage IIIC patients with a “favorable” vs. “unfavorable” methylation profile were 31.5 and 10.4 months, respectively. The 5 year OS for stage IIIC patients with a “favorable” methylation profile was 41.2% as compared to 0% for patients with an “unfavorable” methylation profile. Among the variables examined by multivariate Cox regression analysis, classification defined by methylation profile was the only predictor of OS (Hazard Ratio = 2.41, for “unfavorable” methylation profile; 95% Confidence Interval: 1.02-5.70; P = 0.045). A 17 gene methylation signature able to correctly assign prognosis (overall error rate = 0) in stage IIIC patients on the basis of distinct methylation-defined groups was also identified.ConclusionsA discrete whole-genome methylation signature has been identified as molecular marker of prognosis for stage IIIC CM patients. Its use in daily practice is foreseeable, and promises to refine the comprehensive clinical management of stage III CM patients.

The placental methylation pattern is crucial for the regulation of genes involved in trophoblast invasion and placental development, both key events for fetal growth. We investigated LINE-1 methylation and methylome profiling using a methylation EPIC array and the targeted methylation sequencing of 154 normal, full-term pregnancies, stratified by birth weight percentiles. LINE-1 methylation showed evidence of a more pronounced hypomethylation in small neonates compared with normal and large for gestational age. Genome-wide methylation, performed in two subsets of pregnancies, showed very similar methylation profiles among cord blood samples while placentae from different pregnancies appeared very variable. A unique methylation profile emerged in each placenta, which could represent the sum of adjustments that the placenta made during the pregnancy to preserve the epigenetic homeostasis of the fetus. Investigations into the 1000 most variable sites between cord blood and the placenta showed that promoters and gene bodies that are hypermethylated in the placenta are associated with blood-specific functions, whereas those that are hypomethylated belong mainly to pathways involved in cancer. These features support the functional analogies between a placenta and cancer. Our results, which provide a comprehensive analysis of DNA methylation profiling in the human placenta, suggest that its peculiar dynamicity can be relevant for understanding placental plasticity in response to the environment.

Acute myeloid leukemia (AML) is a hematologic malignancy characterized by abnormal proliferation and a lack of differentiation of myeloid blasts. Considering the dismal prognosis this disease presents, several efforts have been made to better classify it and offer a tailored treatment to each subtype. This has been formally done by the World Health Organization (WHO) with the AML classification schemes from 2008 and 2016. Nonetheless, there are still mutations that are not currently included in the WHO AML classification, as in the case of some mutations that influence methylation. In this regard, the present study aimed to determine if some of the mutations that influence DNA methylation can be clustered together regarding methylation, expression, and clinical profile. Data from the TCGA LAML cohort were downloaded via cBioPortal. The analysis was performed using R 3.5.2, and the necessary packages for classical statistics, dimensionality reduction, and machine learning. We included only patients that presented mutations in DNMT3A, TET2, IDH1/2, ASXL1, WT1, and KMT2A. Afterwards, mutations that were present in too few patients were removed from the analysis, thus including a total of 57 AML patients. We observed that regarding expression, methylation, and clinical profile, patients with mutated TET2, IDH1/2, and WT1 presented a high degree of similarity, indicating the equivalence that these mutations present between themselves. Nonetheless, we did not observe this similarity between DNMT3A- and KMT2A-mutated AML. Moreover, when comparing the hypermethylating group with the hypomethylating one, we also observed important differences regarding expression, methylation, and clinical profile. In the current manuscript we offer additional arguments for the similarity of the studied hypermethylating mutations and suggest that those should be clustered together in further classifications. The hypermethylating and hypomethylating groups formed above were shown to be different from each other considering overall survival, methylation profile, expression profile, and clinical characteristics. In this manuscript, we present additional arguments for the similarity of the effect generated by TET2, IDH1/2, and WT1 mutations in AML patients. Thus, we hypothesize that hypermethylating mutations skew the AML cells to a similar phenotype with a possible sensitivity to hypermethylating agents.

Methylation change plays an important role in many cellular systems, including cancer development. During recent years, genome-wide or large-scale methylation data has become available thanks to rapid advances in high-throughput biotechnologies. So far, researchers have always used gene expression profiling to study disease subtypes and related therapies. In this study, we investigated methylation profiles in 30 breast cancer cell lines using methylation data generated by microarray technologies. Strong variation of the number of methylation peaks was found among these 30 cell lines; however, more peaks were found in the upstream regions than in downstream regions of genes. We further grouped the methylation profiles of these cell lines into three consensus clusters. Finally, we performed an integrative analysis of breast cancer cell lines using both methylation and gene-expression profiling data. There was no significant correlation between methylation-profiling subtypes and gene-expression profiling subtypes, suggesting the complex nature of methylation in the regulation of gene expression. However, we found basal B cell lines appeared exclusively in two methylation clusters. Although these results are preliminary, this study suggests that methylation profiling might be promising in disease subtype classification and the development of therapeutic strategies.

Background:The prognosis of adrenocortical carcinoma (ACC) is heterogeneous. Genomic studies have identified ACC subgroups characterized by specific molecular alterations, including features measured at DNA level (somatic mutations, chromosome alterations, DNA methylation), which are closely associated with outcome. The aim of this study was to evaluate intratumor heterogeneity of prognostic molecular markers at the DNA level.Methods:Two different tissue samples (primary tumor, local recurrence or metastasis) were analyzed in 26 patients who underwent surgery for primary or recurrent ACC. DNA-related biomarkers with prognostic role were investigated in frozen and paraffin-embedded samples. Somatic mutations of p53/Rb and Wnt/β-catenin pathways were assessed using next-generation sequencing (n = 26), chromosome alteration profiles were determined using SNP arrays (n = 14) and methylation profiles were determined using four-gene bisulfite pyrosequencing (n = 12).Results:Somatic mutations for ZNRF3, TP53, CTNN1B and CDKN2A were found in 7, 6, 6 and 4 patients, respectively, with intratumor heterogeneity in 8/26 patients (31%). Chromosome alteration profiles were ‘Noisy’ (numerous and anarchic alterations) in 8/14 and ‘Chromosomal’ (extended patterns of loss of heterozygosity) in 5/14 of the study samples. For these profiles, no intratumor heterogeneity was observed. Methylation profiles were hypermethylated in 5/12 and non-hypermethylated in 7/12 of the study samples. Intratumor heterogeneity of methylation profiles was observed in 2/12 patients (17%).Conclusions:Intratumor heterogeneity impacts DNA-related molecular markers. While somatic mutation can differ, prognostic DNA methylation and chromosome alteration profile seem rather stable and might be more robust for the prognostic assessment.

Gliomatosis cerebri (GC) is presently considered a distinct astrocytic glioma entity according to the WHO classification for CNS tumors. It is characterized by widespread, typically bilateral infiltration of the brain involving three or more lobes. Genetic studies of GC have to date been restricted to the analysis of individual glioma-associated genes, which revealed mutations in the isocitrate dehydrogenase 1 (IDH1) and tumor protein p53 (TP53) genes in subsets of patients. Here, we report on a genome-wide analysis of DNA methylation and copy number aberrations in 25 GC patients. Results were compared with those obtained for 105 patients with various types of conventional, i.e., non-GC gliomas including diffuse astrocytic gliomas, oligodendrogliomas and glioblastomas. In addition, we assessed the prognostic role of methylation profiles and recurrent DNA copy number aberrations in GC patients. Our data reveal that the methylation profiles in 23 of the 25 GC tumors corresponded to either IDH mutant astrocytoma (n=6), IDH mutant and 1p/19q codeleted oligodendroglioma (n=5), or IDH wild-type glioblastoma including various molecular subgroups, i.e., H3F3A-G34 mutant (n=1), receptor tyrosine kinase 1 (RTK1, n=4), receptor tyrosine kinase 2 (classic) (RTK2, n=2) or mesenchymal (n=5) glioblastoma groups. Two tumors showed methylation profiles of normal brain tissue due to low tumor cell content. While histological grading (WHO grade IV vs. WHO grade II and III) was not prognostic, the molecular classification as classic/RTK2 or mesenchymal glioblastoma was associated with worse overall survival. Multivariate Cox regression analysis revealed MGMT promoter methylation as a positive prognostic factor. Taken together, DNA-based large-scale molecular profiling indicates that GC comprises a genetically and epigenetically heterogeneous group of diffuse gliomas that carry DNA methylation and copy number profiles closely matching the common molecularly defined glioma entities. These data support the removal of GC as a distinct glioma entity in the upcoming revision of the WHO classification.

Aberrant genomic expression and methylation serve important roles in cancer development. Integrated analysis of genetic and methylation profiles may identify potential tumor marker genes for colorectal cancer (CRC) prediction. In the current study, DNA methylation and mRNA expression profiles associated with CRC were downloaded from The Cancer Genome Atlas database. Differentially expressed mRNAs and methylated genes between tumor samples and adjacent healthy tissues were identified. Candidate tumor marker genes and prognostic clinical factors were screened according to univariable and multivariable Cox regression analysis. A total of 218 DEGs with aberrant methylation levels were screened from tumor samples. A risk prediction model was constructed based on identified genes and clinical factors. Randomization tests were used to evaluate the performance of the prediction model, including area under the curve (AUC) calculation and cross-validation. Cox regression analysis revealed that eight genes and six prognostic clinical factors were significantly associated with survival outcomes. Functional and pathway enrichment analysis revealed that the eight genes were mainly involved in ‘cell adhesion’, ‘fatty acid metabolism’ and ‘cytokine receptor interaction’ pathways. After combining six clinical factors with eight genes, the accuracy of risk prediction model has been increased intensively. The P-values representing the association between risk grouping and prognosis decreased from 0.009 to 0.001 and the AUC increased from 0.992 to 0.999, indicating that the comprehensive risk prediction model exhibited a good performance for disease prognosis prediction. The current study integrated genomic and methylation profiles and identified eight tumor marker genes in CRC. These candidate genes may improve the prediction accuracy of CRC prognosis.

BACKGROUND“Head Start-4” (HS-4) is a prospective, randomized clinic trial that tailors treatment based on medulloblastoma molecular subgroups (WNT, SHH, Group 3, and Group 4) and response to induction chemotherapy, and compares the efficacy of one versus three (tandem) cycles of myeloablative therapy. Here we compare different methodologies used to distinguish between WNT/SHH medulloblastoma (low-risk arm) and non-SHH/non-WNT medulloblastoma (high-risk arm) during the course of the trial. METHODSWhen HS-4 trial began enrolling patients in 2015, in the absence of a CAP-CLIA certified test for methylation and gene expression profile, we utilized histopathology/immunochemistry (HP/IHC) and chromosomal microarray (CMA) via OncoScanTM (Thermo Fisher) to classify medulloblastoma samples into either WNT, SHH, or non-WNT/non-SHH (Subgroups 3 and 4) at the time of diagnosis. Retrospectively, we performed both NanoString based 22-gene assay and DNA methylation profiling on all patient samples. RESULTSWe have HP/IHC, CMA, NanoString and methylation profiling for 54 infants and young children with medulloblastoma enrolled on HS-4. While indeterminate result occurred with CMA in three cases and NanoString in two cases, HP/IHC successfully assigned samples to SHH/WNT and non-SHH/non-WNT arms of the study in all 54 cases. We have HP/IHC, CMA and DNA methylation profiling for additional 33 patients. While pathology/IHC was indeterminate in two cases (one WNT and one group 3 MB), remaining cases accurately categorized medulloblastoma methylation subtype as WNT/SHH and non-WNT/non-SHH. CONCLUSIONDue to the long turnaround time, waiting for medulloblastoma molecular subtype confirmation by DNA methylation array may delay treatment initiation. HS-4 data displays robust prediction of WNT/SHH versus non-WNT/non-SHH molecular subtypes by HP/IHC in comparison to DNA methylation profiling and provides a platform to initiate treatment based on HP/IHC while awaiting molecular information. In addition, these data support relying on histopathology for medulloblastoma subtypes in resource poor countries where methylation profiling is not readily available.

BackgroundDNA methylation is an important epigenetic modification that is known to regulate gene expression. Whole-genome bisulfite sequencing (WGBS) is a powerful method for studying cytosine methylation in a whole genome. However, it is difficult to obtain methylation profiles using the WGBS raw reads and is necessary to be proficient in all types of bioinformatic tools for the study of DNA methylation. In addition, recent end-to-end pipelines for DNA methylation analyses are not sufficient for addressing those difficulties.ResultsHere we present msPIPE, a pipeline for DNA methylation analyses with WGBS data seamlessly connecting all the required tasks ranging from data pre-processing to multiple downstream DNA methylation analyses. The msPIPE can generate various methylation profiles to analyze methylation patterns in the given sample, including statistical summaries and methylation levels. Also, the methylation levels in the functional regions of a genome are computed with proper annotation. The results of methylation profiles, hypomethylation, and differential methylation analysis are plotted in publication-quality figures. The msPIPE can be easily and conveniently used with a Docker image, which includes all dependent packages and software related to DNA methylation analyses.ConclusionmsPIPE is a new end-to-end pipeline designed for methylation calling, profiling, and various types of downstream DNA methylation analyses, leading to the creation of publication-quality figures. msPIPE allows researchers to process and analyze the WGBS data in an easy and convenient way. It is available at https://github.com/jkimlab/msPIPE and https://hub.docker.com/r/jkimlab/mspipe.

Analysis of whole genome-wide methylation and gene expression profiles in visceral omental adipose tissue of pregnancies with gestational diabetes mellitus

Aberrant epigenetic patterns are a hallmark of acute myeloid leukemia (AML). Mutations in profound epigenetic regulators DNMT3A and IDH1/2 often occur concurrently in AML. The aim was to analyze DNA methylation, hydroxymethylation and mRNA expression profiles in AML with mutations in DNMT3A and IDH1/2 (individually and in combinations). Infinium MethylationEPIC BeadChip (Illumina) covering 850,000 CpGs was utilized. The validation of hydroxy-/methylation data was done by pyrosequencing. HumanHT-12 v4 Expression BeadChip (Illumina) was used for expression examination. Hierarchical clustering analysis of DNA hydroxy-/methylation data revealed clusters corresponding to DNMT3A and IDH1/2 mutations and CD34+ healthy controls. Samples with concurrent presence of DNMT3A and IDH1/2 mutations displayed mixed DNA hydroxy-/methylation profile with preferential clustering to healthy controls. Numbers and levels of DNA hydroxymethylation were low. Uniformly hypermethylated loci in AML patients with IDH1/2 mutations were enriched for immune response and apoptosis related genes, among which hypermethylation of granzyme B (GZMB) was found to be associated with inferior overall survival of AML patients (P= 0.035). Distinct molecular background results in specific DNA hydroxy-/methylation profiles in AML. Site-specific DNA hydroxymethylation changes are much less frequent in AML pathogenesis compared to DNA methylation. Methylation levels of enhancer located upstream GZMB gene might contribute to AML prognostication models.

Rearrangements of the transcription factors FOS and FOSB have recently been identified as the genetic driver event underlying osteoid osteoma and osteoblastoma. Nuclear overexpression of FOS and FOSB have since then emerged as a reliable surrogate marker despite limitations in specificity and sensitivity. Indeed, osteosarcoma can infrequently show nuclear FOS expression and a small fraction of osteoblastomas seem to arise independent of FOS/FOSB rearrangements. Acid decalcification and tissue preservation are additional factors that can negatively influence immunohistochemical testing and make diagnostic decision-making challenging in individual cases. Particularly aggressive appearing osteoblastomas, also referred to as epithelioid osteoblastomas, and osteoblastoma-like osteosarcoma can be difficult to distinguish, underlining the need for additional markers to support the diagnosis. Methylation and copy number profiling, a technique well established for the classification of brain tumors, might fill this gap. Here, we set out to comprehensively characterize a series of 77 osteoblastomas by immunohistochemistry, fluorescence in-situ hybridization as well as copy number and methylation profiling and compared our findings to histologic mimics. Our results show that osteoblastomas are uniformly characterized by flat copy number profiles that can add certainty in reaching the correct diagnosis. The methylation cluster formed by osteoblastomas, however, so far lacks specificity and can be misleading in individual cases.

Oral tolerance induction in experimental autoimmune encephalomyelitis with Candida expressing a specific Mog peptide