Search

The diagnosis of malignant pleural mesothelioma (MPM) is challenging because of its potential overlap with other neoplasms or even with reactive conditions. DNA methylation analysis is effective in diagnosing tumors. In the present study, this approach was tested for use in MPM diagnosis. The DNA methylation patterns of a discovery cohort and an independent-validation cohort of MPMs were compared to those of 202 cases representing malignant and benign diagnostic mimics (angiosarcoma, desmoid-type fibromatosis, epithelioid sarcoma, leiomyosarcoma, lung adenocarcinoma, lung squamous cell carcinoma, melanoma, nodular fasciitis, reactive mesothelial hyperplasia, sclerosing fibrous pleuritis, solitary fibrous tumor, and synovial sarcoma). By both unsupervised hierarchical clustering and t-distributed stochastic neighbor embedding analysis, MPM samples in the discovery cohort exhibited a DNA methylation profile different from those of other neoplastic and reactive mimics. These results were confirmed in the independent validation cohort and by in silico analysis of the MPM-The Cancer Genome Atlas data set. Copy number variation profiles were also inferred to identify molecular hallmarks of MPM, including CDKN2A and NF2 deletions. Methylation profiling was effective in the diagnosis of MPM, although caution is advised in samples with low tumor cell content., (Copyright © 2021 Association for Molecular Pathology and American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.)

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.

Purpose: Recent studies revealed divergent gene expression patterns in Ewing sarcoma (EwS) with canonical EWSR1-ETS gene fusions and undifferentiated round cell sarcomas (URCS) with EWSR1 rearrangements fused to the non-ETS gene NFATc2. Thus, the question arises whether the latter tumors really belong to EwS., Methods: We collected five cases matching the group of URCS with EWSR1-NFATc2 fusion and performed DNA methylation and copy number profiling. Results were compared to methylation data of 30 EwS with various EWSR1-ETS fusions and one EwS with FUS-ERG fusion, 16 URCS with CIC rearrangement and 10 URCS with BCOR alteration and a total of 81 EWSR1-associated soft tissue sarcomas including 7 angiomatoid fibrous histiocytomas, 7 clear cell sarcomas of the soft tissue, 28 desmoplastic small round cell tumors, 10 extraskeletal myxoid chondrosarcomas and 29 myxoid liposarcomas., Results: Unsupervised hierarchical clustering and t-distributed stochastic neighbor embedding analysis of DNA methylation data revealed a homogeneous methylation cluster for URCS with EWSR1-NFATc2 fusion, which clearly segregated from EwS and the other subtypes. Copy number profiles of EWSR1-NFATc2 cases showed recurrent losses on chromosome 9q and segmental gains on 20q13 and 22q12 involving the EWSR1 and NFATc2 loci, respectively., Conclusion: In summary, URCS with EWSR1-NFATc2 fusion share a distinct DNA methylation signature and carry characteristic copy number alterations, which emphasizes that these sarcomas should be considered separately from EwS.

Hepatoblastoma (HB) is the most common liver tumor in children under the age of 3 years worldwide. While many patients achieve good outcomes with surgical resection and conventional chemotherapy, there is still a high‑risk population that exhibits a poor treatment response and unfavorable prognosis, which warrants the search for novel treatment options. In recent years, it has become clear that genetic events alone are not sufficient to explain the aggressive phenotype of this embryonal malignancy. Instead, epigenetic modifications and aberrant gene expression seem to be key drivers of HB. In the present study, expression analyses such as reverse transcription‑quantitative polymerase chain reaction revealed that the oncogene, MYCN proto‑oncogene basic‑helix‑loop‑helix transcription factor (MYCN) was upregulated in HB and other pediatric liver tumors, due to the transcriptional activity of its antisense transcript MYCN opposite strand (MYCNOS). Pyrosequencing demonstrated the hypomethylated regions in the promoter of MYCN and MYCNOS, suggesting that an epigenetic mechanism may underlie the induction of aberrant expression. Transient MYCN knockdown in HB cells resulted in growth inhibition over time. In addition, treating HB cells with the MYCN inhibitors JQ1 and MLN8237 led to the significant downregulation of MYCN either at the mRNA or protein levels, respectively. The underlying mechanism of action of the two inhibitors was revealed to be associated with the induction of dose‑dependent growth arrest, by arresting cells at either the G1/G0 or G2 phase. Furthermore, MLN8237 and JQ1 were able to cause spindle disturbances and/or apoptosis in HB cells. The present results suggest that MYCN may be a promising biomarker for HB and a potential therapeutic target in patients with tumors overexpressing MYCN.

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.

Background: Hepatoblastoma (HB) is the most common liver tumor of childhood and occurs predominantly within the first 3 years of life. In accordance to its early manifestation, HB has been described to display an extremely low mutation rate. As substitute, epigenetic modifiers seem to play an exceptional role in its tumorigenesis, which holds promise to develop targeted therapies and establish biomarkers for patient risk stratification. Results: We examined the role of a newly described protein complex consisting of three epigenetic regulators, namely E3 ubiquitin-like containing PHD and RING finger domain 1 (UHRF1), ubiquitin-specific-processing protease 7 (USP7), and DNA methyltransferase 1 (DNMT1), in HB. We found the complex to be located on the promoter regions of the pivotal HB-associated tumor suppressor genes (TSGs) HHIP, IGFBP3, and SFRP1 in HB cells, thereby leading to strong repression through DNA methylation and histone modifications. Consequently, knockdown of UHRF1 led to DNA demethylation and loss of the repressive H3K9me2 histone mark at the TSG loci with their subsequent transcriptional reactivation. The observed growth impairment of HB cells upon UHRF1 knockdown could be attributed to reduced expression of genes involved in cell cycle progression, negative regulation of cell death, LIN28B signaling, and the adverse 16-gene signature, as revealed by global RNA sequencing. Clinically, overexpression of UHRF1 in primary tumor tissues was significantly associated with poor survival and the prognostic high-risk 16-gene signature. Conclusion: These findings suggest that UHRF1 is critical for aberrant TSG silencing and sustained growth signaling in HB and that UHRF1 overexpression levels might serve as a prognostic biomarker and potential molecular target for HB patients. [ABSTRACT FROM AUTHOR]