Pleural mesothelioma (PM) is a rare and aggressive cancer primarily caused by asbestos exposure. Its late diagnosis, due to non-specific symptoms and challenges in distinguishing it from other lung diseases, contributes to poor patient outcomes. Recent advancements in DNA methylation analysis offer new opportunities for improving PM diagnostics. This thesis investigates the potential of DNA methylation as a diagnostic tool, presenting novel approaches for early and accurate detection of PM. The first part of the research identifies methylation biomarkers for PM using EPIC methylation arrays on 11 PM samples and 29 healthy pleura samples, supplemented by public datasets of other lung-related diseases. The study reveals 81,968 differentially methylated CpG sites between PM and healthy pleura. Importantly, these methylation profiles enable clear differentiation of PM from other lung cancers, addressing a critical diagnostic challenge. To facilitate cost-effective and scalable methylation analysis, a novel technology, IMPRESS (Improved Methylation Profiling using Restriction Enzymes and smMIP Sequencing), was developed. IMPRESS combines methylation-sensitive restriction enzymes and single-molecule Molecular Inversion Probes to analyze thousands of CpG sites. Validation on a multi-cancer assay targeting 1,791 CpGs across eight cancer types achieved a sensitivity of 95% and specificity of 91%. This technology demonstrated high potential for non-invasive diagnostics using liquid biopsies. In the final part, the identified PM-specific methylation biomarkers were integrated into IMPRESS to develop an assay for distinguishing PM from healthy pleura and other pleural pathologies. A stepwise diagnostic model achieved sensitivities of 88.9% and 80.8% and specificities of 93.3% and 100% for differentiating PM from non-tumoral conditions and pleural metastases, respectively. This thesis highlights the promise of DNA methylation analysis for PM diagnostics. The combination of novel biomarkers and the IMPRESS platform offers a robust, cost-effective, and scalable solution for early cancer detection. These findings provide a foundation for integrating methylation-based assays into clinical practice, potentially improving early diagnosis, treatment, and patient outcomes in PM and other cancers.