Aim: We thoroughly discuss the interaction between the stemness index and DNA methylation in pancreatic cancer (PC). Materials & methods: First, the stemness indices of PC (denoted mRNAsi and mDNAsi) were calculated using a one-class logistic regression machine-learning algorithm. Second, we screened the central methylation sites associated with stemness and screened out the key genes. We investigated the DNA methylation regulators associated with the key genes. Finally, using CIBERSORT and TIMER, we assessed the influence of stemness indexes and key genes on PC microenvironment formation. Results: In this study we quantified the stemness indices for PC and screened 20 related central DNA methylation sites. Further analysis of the methylation site cg22687244, located in the 3' UTR, revealed that it promoted the expression of the key gene FAM81A. We show that FAM81A may be regulated by DNA methylation regulators. Furthermore, immune cells were found to be more abundant in PC microenvironments with high expression of FAM81A. Conclusion: We report for the first time that the 3' UTR methylation of FAM81A is closely related to PC stemness and contributes to tumor immune infiltration. Therefore FAM81A may serve as a potential marker to guide the treatment of PC.
Keywords: DNA methylation; WGCNA; machine learning; pancreatic cancer; prognosis; tumor immunity.