MethMarkerDB: a comprehensive cancer DNA methylation biomarker database-Reference-Cited by-同舟云学术

MethMarkerDB: a comprehensive cancer DNA methylation biomarker database

Published:2023-10-27 Issue:D1 Volume:52 Page:D1380-D1392
ISSN:0305-1048
Container-title:Nucleic Acids Research
language:en
Short-container-title:

Author:

Zhu Zhixian¹²,Zhou Qiangwei¹²,Sun Yuanhui¹²,Lai Fuming¹²,Wang Zhenji¹²,Hao Zhigang¹²,Li Guoliang¹²^ORCID

Affiliation:

1. National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University , Wuhan 430070 , China

2. Agricultural Bioinformatics Key Laboratory of Hubei Province, Hubei Engineering Technology Research Center of Agricultural Big Data, Key Laboratory of Smart Farming for Agricultural Animals, 3D Genomics Research Center, College of Informatics, Huazhong Agricultural University , Wuhan 430070 , China

Abstract

Abstract DNA methylation plays a crucial role in tumorigenesis and tumor progression, sparking substantial interest in the clinical applications of cancer DNA methylation biomarkers. Cancer-related whole-genome bisulfite sequencing (WGBS) data offers a promising approach to precisely identify these biomarkers with differentially methylated regions (DMRs). However, currently there is no dedicated resource for cancer DNA methylation biomarkers with WGBS data. Here, we developed a comprehensive cancer DNA methylation biomarker database (MethMarkerDB, https://methmarkerdb.hzau.edu.cn/), which integrated 658 WGBS datasets, incorporating 724 curated DNA methylation biomarker genes from 1425 PubMed published articles. Based on WGBS data, we documented 5.4 million DMRs from 13 common types of cancer as candidate DNA methylation biomarkers. We provided search and annotation functions for these DMRs with different resources, such as enhancers and SNPs, and developed diagnostic and prognostic models for further biomarker evaluation. With the database, we not only identified known DNA methylation biomarkers, but also identified 781 hypermethylated and 5245 hypomethylated pan-cancer DMRs, corresponding to 693 and 2172 genes, respectively. These novel potential pan-cancer DNA methylation biomarkers hold significant clinical translational value. We hope that MethMarkerDB will help identify novel cancer DNA methylation biomarkers and propel the clinical application of these biomarkers.

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Publisher

Oxford University Press (OUP)

Subject

Genetics

Link

https://academic.oup.com/nar/article-pdf/52/D1/D1380/55040407/gkad923.pdf

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