Project 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.

| S-EPMC9738683 | biostudies-literature

DNA methylation-based classification of sinonasal tumors

Project description:DNA methylation-based classification of sinonasal tumors

| PRJNA803926 | ENA

DNA methylation profiling for molecular classification of adult diffuse lower‑grade gliomas

Project description:DNA methylation profiling has become a powerful tool for neuro-oncology diagnostics. We investigated the value of using DNA methylation profiling to achieve molecular diagnosis in adult primary diffuse lower-grade gliomas according to WHO 2016 classification system of central nervous system tumors. We further evaluated the use of methylation profiling for improved molecular characterization of the tumors and identify prognostic differences beyond histological grade and molecular markers (IDH mutation and 1p/19q codeletion status).

2023-02-27 | GSE175877 | GEO

DNA methylation-based classification of common renal tumors

Project description:DNA methylation-based classification of common renal tumors

| PRJNA1064051 | ENA

Sarcoma Classification by DNA-methylation profiling

Project description:DNA methylation classification reference set (1077) and validation set (428) of 1505 sarcoma samples using Illumina HumanMethylation450 BeadChips or Illumina Infinium HumanMethylation850 BeadChips

2020-03-01 | GSE140686 | GEO

Intra-Tumor DNA Methylation Heterogeneity in Glioblastoma Implications for DNA Methylation-based Classification

Project description:Intra-Tumor DNA Methylation Heterogeneity in Glioblastoma Implications for DNA Methylation-based Classification

| PRJNA478049 | ENA

Contribution of DNA methylation profiling in the classification of TRIO::TERT sarcomas

Project description:DNA methylation profiling has emerged as a valuable tool for tumor classification, exemplified by the German Cancer Research Center's creation of online classifiers for CNS tumors and sarcomas. Identification of rare molecular events, such as TRIO::TERT fusion in undifferentiated sarcomas, through DNA methylation profiling and transcriptome analysis aims to define distinct molecular subgroups within sarcomas of uncertain diagnosis, potentially improving classification and treatment strategies.In this study, we present 8 cases of sarcomas characterized by TRIO::TERT fusion, establishing it as a distinct molecular subtype of sarcomas. This fusion represents a consistent molecular feature across all analyzed tumors, suggesting its pivotal role in sarcomatogenesis. Identifying TRIO::TERT transcript sarcoma as a new tumor type may enhance diagnostic strategies for improved patient management.

2024-05-31 | GSE261891 | GEO

DNA methylation-based classification of sinonasal tumors [test set]

Project description:DNA methylation-based classification of sinonasal tumors [test set]

| PRJNA803928 | ENA