ABSTRACT DNA methylation levels are intimately associated with tumor development, progression, and therapeutic outcomes. Accurate analysis of the relationship between DNA methylation levels and tumor prognosis facilitates comprehensive investigation of tumor development mechanisms, enabling optimization of clinical decision‐making and subsequent enhancement of cancer patient survival rates. However, current web‐based tools for analyzing tumor methylation levels and survival prognosis exhibit significant limitations. We have developed a web‐based tool called Pan‐cancer DNA Methylation Survival Analysis (PDMSA) implemented in Shiny, which integrates DNA methylation data and clinical information from large public databases (TCGA and GEO). PDMSA currently encompasses tumor DNA methylation data from 30 TCGA datasets and 15 GEO datasets, consisting of 16 205 211 records that span 39 cancer types, 45 datasets, 19 909 genes, and 8369 samples. The tool executes prognostic Kaplan–Meier survival analysis and Cox regression analysis utilizing two distinct cutoff value grouping methods, offering customizable visualization options for the results. As a user‐friendly analytical platform, PDMSA serves as a comprehensive tool for biomedical researchers to investigate the relationship between methylation levels at specific gene loci and tumor survival outcomes, thereby facilitating the advancement of precision medicine in oncology. Access PDMSA at robinl‐lab.com/PDMSA.
Guo et al. (2026) studied this question.