Prediction of epigenetically regulated genes in breast cancer cell lines

Abstract

BackgroundMethylation of CpG islands within the DNA promoter regions is one mechanism that leads to aberrant gene expression in cancer. In particular, the abnormal methylation of CpG islands may silence associated genes. Therefore, using high-throughput microarrays to measure CpG island methylation will lead to better understanding of tumor pathobiology and progression, while revealing potentially new biomarkers. We have examined a recently developed high-throughput technology for measuring genome-wide methylation patterns called mTACL. Here, we propose a computational pipeline for integrating gene expression and CpG island methylation profles to identify epigenetically regulated genes for a panel of 45 breast cancer cell lines, which is widely used in the Integrative Cancer Biology Program (ICBP). The pipeline (i) reduces the dimensionality of the methylation data, (ii) associates the reduced methylation data with gene expression data, and (iii) ranks methylation-expression associations according to their epigenetic regulation. Dimensionality reduction is performed in two steps: (i) methylation sites are grouped across the genome to identify regions of interest, and (ii) methylation profles are clustered within each region. Associations between the clustered methylation and the gene expression data sets generate candidate matches within a fxed neighborhood around each gene. Finally, the methylation-expression associations are ranked through a logistic regression, and their significance is quantified through permutation analysis.ResultsOur two-step dimensionality reduction compressed 90% of the original data, reducing 137,688 methylation sites to 14,505 clusters. Methylation-expression associations produced 18,312 correspondences, which were used to further analyze epigenetic regulation. Logistic regression was used to identify 58 genes from these correspondences that showed a statistically signifcant negative correlation between methylation profles and gene expression in the panel of breast cancer cell lines. Subnetwork enrichment of these genes has identifed 35 common regulators with 6 or more predicted markers. In addition to identifying epigenetically regulated genes, we show evidence of differentially expressed methylation patterns between the basal and luminal subtypes.ConclusionsOur results indicate that the proposed computational protocol is a viable platform for identifying epigenetically regulated genes. Our protocol has generated a list of predictors including COL1A2, TOP2A, TFF1, and VAV3, genes whose key roles in epigenetic regulation is documented in the literature. Subnetwork enrichment of these predicted markers further suggests that epigenetic regulation of individual genes occurs in a coordinated fashion and through common regulators.

Genome-Wide DNA Methylation Profiling of CpG Islands in Breast Cancer Identifies Novel Genes Associated with Tumorigenicity

“…COL1A2 methylation was also associated with ER/ PR receptor status in our breast cancer cohort, was cancer specific, and could be reversed in methylated breast tumor cell lines following treatment with 5-azadc. Using computational protocols, Loss and colleagues recently showed COL1A2 methylation in breast tumor cell lines (28). In medulloblastoma COL1A2 methylation was found to be subgroup specific, and in bladder cancer COLIA2 gene inactivation due to methylation was shown to contribute to cell proliferation and migration of bladder cancer cells (29,30).…”

Vav3 oncogene is upregulated and a poor prognostic factor in breast cancer patients

“…Vav3 is an upstream mediator of Ras-related C3 botulinum toxin substrate 1, which enhances the transcriptional activity of estrogen receptor α (ER-α) in breast cancer cells (9). In addition, Vav3 is epigenetically regulated during the development of breast cancer (10). Thus, it is intriguing to postulate that the progression and maintenance of breast cancer relies on the deregulation of the Vav3 oncogene.…”

Hypermethylation of collagen α2 (I) gene (COL1A2) is an independent predictor of survival in head and neck cancer

“…Structural integrity and coordinated biosynthesis of the two chains are critically important for tissue morphogenesis, growth, homeostasis, and repair [11]. Hypermethylation of COL1A2 has been described in many cancers, mainly adenocarcinomas, including colorectal cancer [12], melanoma [13], bladder cancer [14], neuroblastoma [15], medulloblastoma [16,17], breast cancer [18], and hepatoma [19]. The investigation for oncogenic mechanism by COL1A2 gene inactivation was also recently progressing.…”