Abstract
Aim: To explore the mechanism of cancer by employing a comprehensive analysis of DNA methylationpatterns and variations among pan-cancer cohorts. Materials&methods: This research focused on the discovery of universally specific or common biomarkers by mathematical statistics and machine learning methods in The Cancer Genome Atlas. Results: We found 138 differently methylated CpGs (DMCs)with a common methylation trend and eight common differently methylated regionsin different cancer cohorts. Additionally, we found 99 DMCs to distinguish 32 different cancer cohorts in random forestanalysis because of the specificity mechanism, but each DMC still had high instability. Conclusion: Our results could facilitate the development of biomarkers that are universally specific and common features across pan-cancer cohorts.
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