Exploring breast carcinogenesis through integrative genomics and epigenomics analyses

Minning,Chin; Mokhtar,Norfilza  Mohd; Abdullah,Norlia; Muhammad,Rohaizak; Emran,Nor  Aina; Ali,Siti  Aishah Md; Harun,Roslan; Jamal,Rahman

doi:10.3892/ijo.2014.2625

Exploring breast carcinogenesis through integrative genomics and epigenomics analyses

Authors:
- Chin Minning
- Norfilza Mohd Mokhtar
- Norlia Abdullah
- Rohaizak Muhammad
- Nor Aina Emran
- Siti Aishah Md Ali
- Roslan Harun
- Rahman Jamal
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Affiliations: UKM Medical Molecular Biology Institute, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia, Department of Surgery, Faculty of Medicine, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia, Department of Surgery, Hospital Kuala Lumpur, Kuala Lumpur, Malaysia, Department of Pathology, Faculty of Medicine, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia, Department of Medicine, Faculty of Medicine, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
Published online on: August 27, 2014 https://doi.org/10.3892/ijo.2014.2625
Pages: 1959-1968
Copyright: © Minning et al. This is an open access article distributed under the terms of Creative Commons Attribution License [CC BY_NC 3.0].

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Abstract

There have been many DNA methylation studies on breast cancer which showed various methylation patterns involving tumour suppressor genes and oncogenes but only a few of those studies link the methylation data with gene expression. More data are required especially from the Asian region and to analyse how the epigenome data correlate with the transcriptome. DNA methylation profiling was carried out on 76 fresh frozen primary breast tumour tissues and 25 adjacent non-cancerous breast tissues using the Illumina Infinium® HumanMethylation27 BeadChip. Validation of methylation results was performed on 7 genes using either MS-MLPA or MS-qPCR. Gene expression profiling was done on 15 breast tumours and 5 adjacent non-cancerous breast tissues using the Affymetrix GeneChip® Human Gene 1.0 ST array. The overlapping genes between DNA methylation and gene expression datasets were further mapped to the KEGG database to identify the molecular pathways that linked these genes together. Supervised hierarchical cluster analysis revealed 1,389 hypermethylated CpG sites and 22 hypomethylated CpG sites in cancer compared to the normal samples. Gene expression microarray analysis using a fold-change of at least 1.5 and a false discovery rate (FDR) at p>0.05 identified 404 upregulated and 463 downregulated genes in cancer samples. Integration of both datasets identified 51 genes with hypermethylation with low expression (negative association) and 13 genes with hypermethylation with high expression (positive association). Most of the overlapping genes belong to the focal adhesion and extracellular matrix-receptor interaction that play important roles in breast carcinogenesis. The present study displayed the value of using multiple datasets in the same set of tissues and how the integrative analysis can create a list of well-focused genes as well as to show the correlation between epigenetic changes and gene expression. These gene signatures can help us understand the epigenetic regulation of gene expression and could be potential targets for therapeutic intervention in the future.

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