SurvivalMeth: a web server to investigate the effect of DNA methylation-related functional elements on prognosis

Author:

Zhang Chunlong1,Zhao Ning2ORCID,Zhang Xue1,Xiao Jun1,Li Junyi1,Lv Dezhong1,Zhou Weiwei1,Li Yongsheng13,Xu Juan13,Li Xia13

Affiliation:

1. College of Bioinformatics Science and Technology at Harbin Medical University

2. School of Life Sciences and Technology at Harbin Institute of Technology

3. Key Laboratory of Tropical Translational Medicine of Ministry of Education, Hainan Medical University, Haikou, China

Abstract

Abstract Aberrant DNA methylation is a fundamental characterization of epigenetics for carcinogenesis. Abnormality of DNA methylation-related functional elements (DMFEs) may lead to dysfunction of regulatory genes in the progression of cancers, contributing to prognosis of many cancers. There is an urgent need to construct a tool to comprehensively assess the impact of DMFEs on prognosis. Therefore, we developed SurvivalMeth (http://bio-bigdata.hrbmu.edu.cn/survivalmeth) to explore the prognosis-related DMFEs, which documented many kinds of DMFEs, including 309,465 CpG island-related elements, 104,748 transcript-related elements, 77,634 repeat elements, as well as cell-type specific 1,689,653 super enhancers (SE) and 1,304,902 CTCF binding regions for analysis. SurvivalMeth is a convenient tool which collected DNA methylation profiles of 36 cancers and allowed users to query their genes of interest in different datasets for prognosis. Furthermore, SurvivalMeth not only integrated different combinations, including single DMFE, multiple DMFEs, SEs and clinical data, to perform survival analysis on preupload data but also allowed for uploading customized DNA methylation profile of DMFEs from various diseases to analyze. SurvivalMeth provided a comprehensive resource and automated analysis for prognostic DMFEs, including DMFE methylation level, correlation analysis, clinical analysis, differential analysis, DMFE annotation, survival-related detailed result and visualization of survival analysis. In summary, we believe that SurvivalMeth will facilitate prognostic research of DMFEs in diverse cancers.

Funder

National Key Research and Development Program

National Natural Science Foundation of China

Natural Science Foundation for Distinguished Young Scholars of Heilongjiang Province

Heilongjiang Touyan Innovation Team Program

Harbin Medical University Daqing Campus

Harbin Medical University

Publisher

Oxford University Press (OUP)

Subject

Molecular Biology,Information Systems

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