<HashMap><database>biostudies-literature</database><scores/><additional><omics_type>Unknown</omics_type><volume>14(23)</volume><submitter>Gaiser T</submitter><pubmed_abstract>Thymomas are malignant thymic epithelial tumors that are difficult to diagnose due to their rarity and complex diagnostic criteria. They represent a morphologically heterogeneous class of tumors mainly defined by "organo-typical" architectural features and cellular composition. The diagnosis of thymoma is burdened with a high level of inter-observer variability and the problem that some type-specific morphological alterations are more on the continuum than clear-cut. Methylation pattern-based classification may help to increase diagnostic precision, particularly in borderline cases. We applied array-based DNA methylation analysis to a set of 113 thymomas with stringent histological annotation. Unsupervised clustering and t-SNE analysis of DNA methylation data clearly segregated thymoma samples mainly according to the current WHO classification into A, AB, B1, B2, B2/B3, B3, and micronodular thymoma with lymphoid stroma. However, methylation analyses separated the histological subgroups AB and B2 into two methylation classes: mono-/bi-phasic AB-thymomas and conventional/"B1-like" B2-thymomas. Copy number variation analysis demonstrated methylation class-specific patterns of chromosomal alterations. Our study demonstrates that the current WHO classification is generally well reflected at the methylation level but suggests that B2- and AB-thymomas are (epi)genetically heterogeneous. Methylation-based classifications could help to refine diagnostic criteria for thymoma classification, improve reproducibility, and may affect treatment decisions.</pubmed_abstract><journal>Cancers</journal><pagination>5876</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC9738683</full_dataset_link><repository>biostudies-literature</repository><pubmed_title>DNA-Methylation Analysis as a Tool for Thymoma Classification.</pubmed_title><pmcid>PMC9738683</pmcid><pubmed_authors>Sahm F</pubmed_authors><pubmed_authors>Gaiser T</pubmed_authors><pubmed_authors>Hirsch D</pubmed_authors><pubmed_authors>Strobel P</pubmed_authors><pubmed_authors>von Deimling A</pubmed_authors><pubmed_authors>Porth I</pubmed_authors><pubmed_authors>Marx A</pubmed_authors></additional><is_claimable>false</is_claimable><name>DNA-Methylation Analysis as a Tool for Thymoma Classification.</name><description>Thymomas are malignant thymic epithelial tumors that are difficult to diagnose due to their rarity and complex diagnostic criteria. They represent a morphologically heterogeneous class of tumors mainly defined by "organo-typical" architectural features and cellular composition. The diagnosis of thymoma is burdened with a high level of inter-observer variability and the problem that some type-specific morphological alterations are more on the continuum than clear-cut. Methylation pattern-based classification may help to increase diagnostic precision, particularly in borderline cases. We applied array-based DNA methylation analysis to a set of 113 thymomas with stringent histological annotation. Unsupervised clustering and t-SNE analysis of DNA methylation data clearly segregated thymoma samples mainly according to the current WHO classification into A, AB, B1, B2, B2/B3, B3, and micronodular thymoma with lymphoid stroma. However, methylation analyses separated the histological subgroups AB and B2 into two methylation classes: mono-/bi-phasic AB-thymomas and conventional/"B1-like" B2-thymomas. Copy number variation analysis demonstrated methylation class-specific patterns of chromosomal alterations. Our study demonstrates that the current WHO classification is generally well reflected at the methylation level but suggests that B2- and AB-thymomas are (epi)genetically heterogeneous. Methylation-based classifications could help to refine diagnostic criteria for thymoma classification, improve reproducibility, and may affect treatment decisions.</description><dates><release>2022-01-01T00:00:00Z</release><publication>2022 Nov</publication><modification>2025-04-20T03:32:30.969Z</modification><creation>2025-04-20T03:32:30.969Z</creation></dates><accession>S-EPMC9738683</accession><cross_references><pubmed>36497358</pubmed><doi>10.3390/cancers14235876</doi></cross_references></HashMap>