Integrative analysis of gene expression and methylation data for breast cancer cell lines

The deadly costs of cancer and necessity for an accurate method of early cancer detection have demanded the identification of genetic and epigenetic factors associated with cancer. DNA methylation, an epigenetic event, plays an important role in cancer susceptibility. In this paper, we use DNA methy...

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Bibliographic Details
Published in:BioData mining 2018-06, Vol.11 (1), p.13-13, Article 13
Main Authors: Li, Catherine, Lee, Juyon, Ding, Jessica, Sun, Shuying
Format: Article
Language:English
Subjects:
Analysis
Bioindicators
Bioinformatics
Biomarkers
Breast cancer
Cancer
Cancer cells
Cancer research
Cancer screening
Cancer treatment
Cell cycle
Chromosomes
Data integration
Data processing
Deoxyribonucleic acid
DNA
DNA methylation
Epigenetics
Gene expression
Genes
Genetic aspects
Genomes
Medical screening
Mutation
Pathway analysis
Statistical analysis
Tumor cell lines
Tumors
Variance analysis
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Summary:The deadly costs of cancer and necessity for an accurate method of early cancer detection have demanded the identification of genetic and epigenetic factors associated with cancer. DNA methylation, an epigenetic event, plays an important role in cancer susceptibility. In this paper, we use DNA methylation and gene expression data integration and pathway analysis to further explore and understand the complex relationship between methylation and gene expression. Through linear modeling and analysis of variance, we obtain genes that show a significant correlation between methylation and gene expression. We then examine the functions and relationships of these genes using bioinformatic tools and databases. In particular, using ConsensusPathDB, we analyze the networks of statistically significant genes to identify hub genes, genes with a large number of links to other genes. We identify eight major hub genes, all in strong association with cancer susceptibility. Through further analysis of the function, gene expression level, and methylation level of these hub genes, we conclude that they are novel potential biomarkers for breast cancer. Our findings have various implications for cancer screening, early detection methods, and potential novel treatments for cancer. Researchers can also use our results to develop more effective methods for cancer study.
ISSN:1756-0381
1756-0381
DOI:10.1186/s13040-018-0174-8