Genome-wide DNA methylation analysis reveals a unique methylation pattern for pleural mesothelioma compared to healthy pleura and other lung diseases.

Abstract

Background: Pleural mesothelioma (PM) is a rare and aggressive cancer type, typically diagnosed at advanced stages. Distinguishing PM from other lung diseases is often challenging. There is an urgent need for biomarkers that can enable early detection. Interest in the field of epigenetics has increased, particularly in the context of tumour development and biomarker discovery. This study aims to identify specific changes in DNA methylation from healthy pleural tissue to PM and to compare these methylation patterns with those found in other lung diseases.

Results: EPIC methylation array data (850 K) were generated for 11 PM and 29 healthy pleura in-house collected samples. This is the first time such a large dataset of healthy pleura samples has been generated. Additional EPIC methylation array data (850 K) for pleural mesothelioma and other lung-related diseases were downloaded from public databases. We conducted pairwise differential methylation analyses across all tissue types, which facilitated the identification of significantly differentially methylated CpG sites. Extensive differential methylation between PM and healthy pleura was observed, identifying 81,968 differentially methylated CpG sites across all genomic regions. Among these, five CpG sites located within four genes (MIR21, RNF39, SPEN and C1orf101) exhibited the most significant and pronounced methylation differences between PM and healthy pleura. Moreover, our analysis delineated distinct methylation patterns specific to PM subtypes. Finally, the methylation profiles of PM were distinctly different from those of other lung cancers, enabling accurate differentiation.

Conclusions: DNA methylation analyses provide a robust method for distinguishing PM from healthy pleural tissues, and specific methylation patterns exist within PM subtypes. These methylation differences underscore their importance in understanding disease progression and may serve as viable biomarkers or therapeutic targets. Moreover, differential methylation patterns between PM and other lung cancers highlights its diagnostic potential. These findings necessitate further translational studies to explore their clinical applications.