Epigenome-Wide Tobacco-Related Methylation Signature Identification and Their Multilevel Regulatory Network Inference for Lung Adenocarcinoma
Joint Authors
Song, Kai
Dong, Yan-Mei
Li, Ming
He, Qi-En
Tong, Yi-Fan
Gao, Hong-Zhi
Zhang, Yi-Zhi
Wu, Ya-Meng
Hu, Jun
Zhang, Ning
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-04-27
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
Tobacco exposure is one of the major risks for the initiation and progress of lung cancer.
The exact corresponding mechanisms, however, are mainly unknown.
Recently, a growing body of evidence has been collected supporting the involvement of DNA methylation in the regulation of gene expression in cancer cells.
The identification of tobacco-related signature methylation probes and the analysis of their regulatory networks at different molecular levels may be of a great help for understanding tobacco-related tumorigenesis.
Three independent lung adenocarcinoma (LUAD) datasets were used to train and validate the tobacco exposure pattern classification model.
A deep selecting method was proposed and used to identify methylation signature probes from hundreds of thousands of the whole epigenome probes.
Then, BIMC (biweight midcorrelation coefficient) algorithm, SRC (Spearman’s rank correlation) analysis, and shortest path tracing method were explored to identify associated genes at gene regulation level and protein-protein interaction level, respectively.
Afterwards, the KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway analysis and GO (Gene Ontology) enrichment analysis were used to analyze their molecular functions and associated pathways.
105 probes were identified as tobacco-related DNA methylation signatures.
They belong to 95 genes which are involved in hsa04512, hsa04151, and other important pathways.
At gene regulation level, 33 genes are uncovered to be highly related to signature probes by both BIMC and SRC methods.
Among them, FARSB and other eight genes were uncovered as Hub genes in the gene regulatory network.
Meanwhile, the PPI network about these 33 genes showed that MAGOH, FYN, and other five genes were the most connected core genes among them.
These analysis results may provide clues for a clear biological interpretation in the molecular mechanism of tumorigenesis.
Moreover, the identified signature probes may serve as potential drug targets for the precision medicine of LUAD.
American Psychological Association (APA)
Dong, Yan-Mei& Li, Ming& He, Qi-En& Tong, Yi-Fan& Gao, Hong-Zhi& Zhang, Yi-Zhi…[et al.]. 2020. Epigenome-Wide Tobacco-Related Methylation Signature Identification and Their Multilevel Regulatory Network Inference for Lung Adenocarcinoma. BioMed Research International،Vol. 2020, no. 2020, pp.1-12.
https://search.emarefa.net/detail/BIM-1132526
Modern Language Association (MLA)
Dong, Yan-Mei…[et al.]. Epigenome-Wide Tobacco-Related Methylation Signature Identification and Their Multilevel Regulatory Network Inference for Lung Adenocarcinoma. BioMed Research International No. 2020 (2020), pp.1-12.
https://search.emarefa.net/detail/BIM-1132526
American Medical Association (AMA)
Dong, Yan-Mei& Li, Ming& He, Qi-En& Tong, Yi-Fan& Gao, Hong-Zhi& Zhang, Yi-Zhi…[et al.]. Epigenome-Wide Tobacco-Related Methylation Signature Identification and Their Multilevel Regulatory Network Inference for Lung Adenocarcinoma. BioMed Research International. 2020. Vol. 2020, no. 2020, pp.1-12.
https://search.emarefa.net/detail/BIM-1132526
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1132526