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

ABSTRACT: 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.

SUBMITTER: Li C

PROVIDER: S-EPMC6019806 | biostudies-other | 2018

REPOSITORIES: biostudies-other

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

Li Catherine C Lee Juyon J Ding Jessica J Sun Shuying S

BioData mining 20180625

<h4>Background</h4>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.<h4>Results</h4>T ...[more]

PMID: 29983747

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Project description:Breast cancer is a genetically and phenotypically complex disease. To understand the role of microRNAs in this molecular complexity, we performed miRNA expression analysis in a cohort of molecularly well-characterized human breast cancer (BC) cell lines to discover miRNAs associated with the most common molecular subtypes and the most frequent genetic aberrations.Using a microarray carrying LNA™ modified oligonucleotide capture probes (Exiqon), expression levels of 725 human miRNAs were measured in 51 BC cell lines. MiRNA expression was explored by unsupervised cluster analysis and then associated with the molecular subtypes and genetic aberrations commonly present in breast cancer. Unsupervised cluster analysis using the most variably expressed miRNAs divided the 51 BC cell lines into a major and a minor cluster predominantly mirroring the luminal and basal intrinsic subdivision of BC cell lines. One hundred and thirteen miRNAs were differentially expressed between these two main clusters of which half were related to the ER-status of the cell lines. Forty miRNAs were differentially expressed between basal-like and normal-like/claudin-low cell lines. Within the luminal-group of cell lines, 39 miRNAs were associated with ERBB2 overexpression and 24 miRNAs with E-cadherin gene mutations, which are frequent in this subtype of BC cell lines. In contrast, 31 different miRNAs were associated with E-cadherin promoter hypermethylation, which, contrary to E-cadherin mutation, is exclusively observed in BC cell lines that are not of luminal origin. The differential expression of 30 miRNAs were associated with p16INK4 status while only a few differentially expressed miRNAs were associated with BRCA1, or PIK3CA/PTEN, TP53 mutation status of the cell lines (P-value < 0.05). Twelve miRNAs were associated with DNA copy number variation of the respective locus. Luminal-basal and epithelial-mesenchymal associated miRNAs determine the overall subdivision of miRNA transcriptome of BC cell lines. Specific sets of miRNAs were associated with ERBB2 overexpression, p16INK4aor E-cadherin mutation or E-cadherin methylation status, which implies that these miRNAs may contribute to the driver role of the genetic aberrations. Additionally, miRNAs, which are located in a genomic region showing recurrent genetic aberrations, may themselves play a driver role in breast carcinogenesis or contribute to a driver gene in their vicinity. In short, our study provides detailed molecular miRNA portraits of BC cell lines, which can be exploited for functional studies of clinically important miRNAs. Affymetrix plus2PM arrays were hybridized according to the manufacturer's procedure using RNA extracted from 52 cultured breast cancer cell lines. Most cellines were analyzed in triplicate. Gene expression data in log2 scale arrays were calculated and associated with diverse characteristics. This submission represents the gene expression component of the study only

Dataset Information

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

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

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