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

BioMed Research International

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

Medicine

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