The human disease methylation database (DiseaseMeth, http://bioinfo.hrbmu.edu.cn/diseasemeth/) is an interactive database that aims to present the most complete collection and annotation of aberrant DNA methylation in human diseases, especially various cancers. Recently, the high-throughput microarray and sequencing technologies have promoted the production of methylome data that contain comprehensive knowledge of human diseases. In this DiseaseMeth update, we have increased the number of samples from 3610 to 32 701, the number of diseases from 72 to 88 and the disease-gene associations from 216 201 to 679 602. DiseaseMeth version 2.0 provides an expanded comprehensive list of disease-gene associations based on manual curation from experimental studies and computational identification from high-throughput methylome data. Besides the data expansion, we also updated the search engine and visualization tools. In particular, we enhanced the differential analysis tools, which now enable online automated identification of DNA methylation abnormalities in human disease in a case-control or disease-disease manner. To facilitate further mining of the disease methylome, three new web tools were developed for cluster analysis, functional annotation and survival analysis. DiseaseMeth version 2.0 should be a useful resource platform for further understanding the molecular mechanisms of human diseases.
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http://dx.doi.org/10.1093/nar/gkw1123 | DOI Listing |
J Cancer
July 2023
Department of Plastic Surgery and Burn Center, Second Affiliated Hospital, Shantou University Medical College, Shantou, Guangdong, China.
Autophagy exerts a pivotal effect on skin cutaneous melanoma (SKCM). This study was aimed to investigate the expression of autophagy related genes (ARGs) in SKCM as well as its clinical value. Differentially expressed (DE) ARGs were downloaded from the intersection of SKCM data in GEPIA2 database and ARGs in Human Autophagy Database (HADB) database, and were verified in SKCM datasets GSE46517 and GSE15605.
View Article and Find Full Text PDFDiscov Oncol
June 2023
Department of Pathology, Xiangya Changde Hospital, Changde, Hunan, China.
Metal regulatory transcription factor 1 (MTF1) has been reported to be correlated with several human diseases, especially like cancers. Exploring the underlying mechanisms and biological functions of MTF1 could provide novel strategies for clinical diagnosis and therapy of cancers. In this study, we conducted the comprehensive analysis to evaluate the profiles of MTF1 in pan-cancer.
View Article and Find Full Text PDFMol Biol Rep
June 2023
Laboratory Center, Affiliated People's Hospital of Jiangsu University, Zhenjiang, People's Republic of China.
Background: Overexpression of lysophosphatidylcholine acyltransferase 1 (LPCAT1) has been found in various solid cancers and is associated with disease progression, metastasis, and recurrence. However, the expression pattern of LPCAT1 in acute myeloid leukemia (AML) bone marrow remains unknown. The present study aimed to compare LPCAT1 expression differences in bone marrow samples from AML patients and healthy controls and assess the clinical relevance of LPCAT1 in AML.
View Article and Find Full Text PDFBiochem Biophys Rep
July 2022
Department of Infectious Diseases and Public Health, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Hong Kong SAR, China.
Background: Esophageal squamous cell carcinoma (ESCC) is a typical Gastro-Intestinal (GI) tract neoplasm. This study was conducted to know the Differential Expressed Genes (DEGs) profile of ESCC along with hub gene screening, lncRNA identification, and drug-genes interactions.
Methods: GSE161533, GSE20347, GSE45670 microarray datasets were retrieved from the NCBI Gene Expression Omnibus (GEO) database.
Bioengineered
December 2021
Department of Nuclear Medicine (Pet Center), Xiangya Hospital, Central South University, Changsha, Hunan, China.
AKT Serine/Threonine Kinase 3 (AKT3) has been reported to play an important role in different tumors. However, its clinical value, biological function, and molecular mechanism in testicular germ cell tumors (TGCT) remains unclear. In the current study, we applied the Gene Set Cancer Analysis (GSCA), UCSC XENA, Gene Expression Omnibus (GEO), the Human Protein Atlas (HPA), LinkedOmics, DiseaseMeth version 2.
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