RESUMEN
The hyperplasia-carcinoma sequence is a stepwise tumourigenic programme towards endometrial cancer in which normal endometrial epithelium becomes neoplastic through non-atypical endometrial hyperplasia (NAEH) and atypical endometrial hyperplasia (AEH), under the influence of unopposed oestrogen. NAEH and AEH are known to exhibit polyclonal and monoclonal cell growth, respectively; yet, aside from focal PTEN protein loss, the genetic and epigenetic alterations that occur during the cellular transition remain largely unknown. We sought to explore the potential molecular mechanisms that promote the NAEH-AEH transition and identify molecular markers that could help to differentiate between these two states. We conducted target-panel sequencing on the coding exons of 596 genes, including 96 endometrial cancer driver genes, and DNA methylome microarrays for 48 NAEH and 44 AEH lesions that were separately collected via macro- or micro-dissection from the endometrial tissues of 30 cases. Sequencing analyses revealed acquisition of the PTEN mutation and the clonal expansion of tumour cells in AEH samples. Further, across the transition, alterations to the DNA methylome were characterised by hypermethylation of promoter/enhancer regions and CpG islands, as well as hypo- and hyper-methylation of DNA-binding regions for transcription factors relevant to endometrial cell differentiation and/or tumourigenesis, including FOXA2, SOX17, and HAND2. The identified DNA methylation signature distinguishing NAEH and AEH lesions was reproducible in a validation cohort with modest discriminative capability. These findings not only support the concept that the transition from NAEH to AEH is an essential step within neoplastic cell transformation of endometrial epithelium but also provide deep insight into the molecular mechanism of the tumourigenic programme. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.
Asunto(s)
Carcinoma Endometrioide , Metilación de ADN , Hiperplasia Endometrial , Neoplasias Endometriales , Epigénesis Genética , Fosfohidrolasa PTEN , Femenino , Humanos , Neoplasias Endometriales/genética , Neoplasias Endometriales/patología , Carcinoma Endometrioide/genética , Carcinoma Endometrioide/patología , Fosfohidrolasa PTEN/genética , Hiperplasia Endometrial/genética , Hiperplasia Endometrial/patología , Hiperplasia Endometrial/metabolismo , Lesiones Precancerosas/genética , Lesiones Precancerosas/patología , Mutación , Regulación Neoplásica de la Expresión Génica , Persona de Mediana Edad , Biomarcadores de Tumor/genética , Biomarcadores de Tumor/metabolismo , Islas de CpG/genética , AncianoRESUMEN
Aim: Gene set analysis has commonly been used to interpret DNA methylome data. However, summarizing the DNA methylation level of a gene is challenging due to variability in the number, density and methylation levels of CpG sites, and the numerous intergenic CpGs. Instead, we propose to use region sets to annotate the DNA methylome. Methods: We developed single sample region-set enrichment analysis for DNA methylome (methyl-ssRSEA) to conduct sample-wise, region-set enrichment analysis. Results: Methyl-ssRSEA can handle both microarray- and sequencing-based platforms and reproducibly recover the known biology from the methylation profiles of peripheral blood cells and breast cancers. The performance was superior to existing tools for region-set analysis in discriminating blood cell types. Conclusion: Methyl-ssRSEA offers a novel way to functionally interpret the DNA methylome in the cell.
Lay abstract Gene set analysis has been a common way to understand the meaning of DNA methylome data. However, organizing the DNA methylation level of a gene is challenging due to variation in the number, density and extent of methylation, of methylation sites, and the substantial number of methylation sites between genes. Instead, we propose to use region sets for the organization. We developed single sample region-set enrichment analysis for DNA methylome (methyl-ssRSEA) to conduct region-set analysis for every sample. Methyl-ssRSEA can handle both microarray- and sequencing-based methods and repeatedly find the known characters from the methylation patterns of peripheral blood cells and breast cancers. The performance was better than existing tools for region-set analysis in differentiating blood cell types. Methyl-ssRSEA offers a novel way to find the features of DNA methylome in the cell.