Dataset Information

Hemimethylation Patterns in Breast Cancer Cell Lines.

ABSTRACT: DNA methylation is an epigenetic event that involves adding a methyl group to the cytosine (C) site, especially the one that pairs with a guanine (G) site (ie, CG or CpG site), in a human genome. This event plays an important role in both cancerous and normal cell development. Previous studies often assume symmetric methylation on both DNA strands. However, asymmetric methylation, or hemimethylation (methylation that occurs only on 1 DNA strand), does exist and has been reported in several studies. Due to the limitation of previous DNA methylation sequencing technologies, researchers could only study hemimethylation on specific genes, but the overall genomic hemimethylation landscape remains relatively unexplored. With the development of advanced next-generation sequencing techniques, it is now possible to measure methylation levels on both forward and reverse strands at all CpG sites in an entire genome. Analyzing hemimethylation patterns may potentially reveal regions related to undergoing tumor growth. For our research, we first identify hemimethylated CpG sites in breast cancer cell lines using Wilcoxon signed rank tests. We then identify hemimethylation patterns by grouping consecutive hemimethylated CpG sites based on their methylation states, methylation "M" or unmethylation "U." These patterns include regular (or consecutive) hemimethylation clusters (eg, "MMM" on one strand and "UUU" on another strand) and polarity (or reverse) clusters (eg, "MU" on one strand and "UM" on another strand). Our results reveal that most hemimethylation clusters are the polarity type, and hemimethylation does occur across the entire genome with notably higher numbers in the breast cancer cell lines. The lengths or sizes of most hemimethylation clusters are very short, often less than 50?base pairs. After mapping hemimethylation clusters and sites to corresponding genes, we study the functions of these genes and find that several of the highly hemimethylated genes may influence tumor growth or suppression. These genes may also indicate a progressing transition to a new tumor stage.

SUBMITTER: Sun S

PROVIDER: S-EPMC6716185 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Hemimethylation Patterns in Breast Cancer Cell Lines.

Sun Shuying S Lee Yu Ri YR Enfield Brittany B

Cancer informatics 20190829

DNA methylation is an epigenetic event that involves adding a methyl group to the cytosine (C) site, especially the one that pairs with a guanine (G) site (ie, CG or CpG site), in a human genome. This event plays an important role in both cancerous and normal cell development. Previous studies often assume symmetric methylation on both DNA strands. However, asymmetric methylation, or hemimethylation (methylation that occurs only on 1 DNA strand), does exist and has been reported in several studi ...[more]

PMID: 31496635

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Project description:BackgroundDNA methylation is an epigenetic event involving the addition of a methyl-group to a cytosine-guanine base pair (i.e., CpG site). It is associated with different cancers. Our research focuses on studying non-small cell lung cancer hemimethylation, which refers to methylation occurring on only one of the two DNA strands. Many studies often assume that methylation occurs on both DNA strands at a CpG site. However, recent publications show the existence of hemimethylation and its significant impact. Therefore, it is important to identify cancer hemimethylation patterns.MethodsIn this paper, we use the Wilcoxon signed rank test to identify hemimethylated CpG sites based on publicly available non-small cell lung cancer methylation sequencing data. We then identify two types of hemimethylated CpG clusters, regular and polarity clusters, and genes with large numbers of hemimethylated sites. Highly hemimethylated genes are then studied for their biological interactions using available bioinformatics tools.ResultsIn this paper, we have conducted the first-ever investigation of hemimethylation in lung cancer. Our results show that hemimethylation does exist in lung cells either as singletons or clusters. Most clusters contain only two or three CpG sites. Polarity clusters are much shorter than regular clusters and appear less frequently. The majority of clusters found in tumor samples have no overlap with clusters found in normal samples, and vice versa. Several genes that are known to be associated with cancer are hemimethylated differently between the cancerous and normal samples. Furthermore, highly hemimethylated genes exhibit many different interactions with other genes that may be associated with cancer. Hemimethylation has diverse patterns and frequencies that are comparable between normal and tumorous cells. Therefore, hemimethylation may be related to both normal and tumor cell development.ConclusionsOur research has identified CpG clusters and genes that are hemimethylated in normal and lung tumor samples. Due to the potential impact of hemimethylation on gene expression and cell function, these clusters and genes may be important to advance our understanding of the development and progression of non-small cell lung cancer.

Project description:Overexpression of the oncogene HER2/neu (c-erbB-2) occurs in up to 30% of breast cancers and is correlated with reduced survival, especially in node-positive disease. The aim of this study was to identify genes associated with the aggressive phenotype of HER2/neu-positive breast cancer cells using cDNA microarrays. RNA was extracted from three HER2/neu-positive and three HER2/neu-negative breast cancer cell lines. Pooled RNA was hybridized in duplicate to the breast specific microarray filters from Research Genetics containing 5184 unique cDNAs. Subsequently, a similar comparison was performed for pooled RNAs from 10 node-positive, ER-positive invasive ductal carcinomas, half of which were HER2/neu overexpressers. In HER2/neu overexpressing breast cancer cell lines, 90 (1.7%) genes were up-regulated and 46 (0.9%) were down-regulated, compared to cell lines with low HER2/neu protein levels. In contrast, in HER2/neu overexpressing primary breast cancers, more genes were down-regulated (N = 132, 2.5%) than up-regulated (N = 19, 0.4%). Many of the differentially expressed genes have previously not been known to play a role in human neoplasia, and some of them may represent novel tumor suppressor or oncogenes. No genes were up-regulated, and only a small number of genes were down-regulated both in cell lines and in carcinomas with high HER2/neu protein levels. These included transforming acidic coiled-coil containing protein 1, glycogen phosphorylase BB, complement 1q and one EST. The differential expression of select genes was confirmed by Northern blotting (trefoil factor 3) or by immunocytochemistry (glycogen phosphorylase BB, vimentin, KAI1). In an extended validation study, 18 of 41 ER-negative, but none of 46 ER-positive, breast carcinomas were found to express vimentin, and all but one of the vimentin-positive tumors were confined to the HER2/neu-negative subgroup (P = 0.0019). Our findings support an important role of the mammary stroma in determining the clinical breast cancer phenotype.

Project description:BackgroundRecent landmark studies have profiled cancer cell lines for molecular features, along with measuring the corresponding growth inhibitory effects for specific drug compounds. These data present a tool for determining which subsets of human cancer might be more responsive to particular drugs. To this end, the NCI-DREAM-sponsored DREAM7: Drug Sensitivity Prediction Challenge (sub-challenge 1) set out to predict the sensitivities of 18 breast cancer cell lines to 31 previously untested compounds, on the basis of molecular profiling data and a training subset of cell lines.Methods and resultsWith 47 teams submitting blinded predictions, team Creighton scored third in terms of overall accuracy. Team Creighton's method was simple and straightforward, incorporated multiple expression data types (RNA-seq, gene array, RPPA), and incorporated all profiled features (not only the "best" predictive ones). As an extension of the approach, cell line data, from public datasets of expression profiling coupled with drug sensitivities (Barretina, Garnett, Heiser) were used to "predict" the drug sensitivities in human breast tumors (using data from The Cancer Genome Atlas). Drug sensitivity correlations within human breast tumors showed differences by expression-based subtype, with many associations in line with the expected (e.g. Lapatinib sensitivity in HER2-enriched cancers) and others inviting further study (e.g. relative resistance to PI3K inhibitors in basal-like cancers).ConclusionsMolecular patterns associated with drug sensitivity are widespread, with potentially hundreds of genes that could be incorporated into making predictions, as well as offering biological clues as to the mechanisms involved. Applying the cell line patterns to human tumor data may help generate hypotheses on what tumor subsets might be more responsive to therapies, where multiple cell line datasets representing various drugs may be used, in order to assess consistency of patterns.

Project description:A functional genetic screen to identify genes causing tamoxifen resistance in an estrogen-dependent human breast cancer cell model was performed. By insertion of defective retrovirus into the genome, individual genetic changes were introduced at random in ZR-75-1 cells. Subsequently, infected cells were selected for their ability to proliferate while being exposed to tamoxifen, and from these cultures stable cell lines were established. The retrovirus insertion sites were mapped enabling the identification of several candidate breast cancer anti-estrogen resistance (BCAR) genes. By cDNA transfection of estrogen-dependent cells resulting in their transformation into a tamoxifen-resistant phenotype, proof was provided for the causative role of BCAR genes.A functional genetic screen to identify genes causing tamoxifen resistance in an estrogen-dependent human breast cancer cell model was performed. By insertion of defective retrovirus into the genome, individual genetic changes were introduced at random in ZR-75-1 cells. Subsequently, infected cells were selected for their ability to proliferate while being exposed to tamoxifen, and from these cultures stable cell lines were established. The retrovirus insertion sites were mapped enabling the identification of several candidate breast cancer anti-estrogen resistance (BCAR) genes identified. By cDNA transfection of estrogen-dependent cells resulting in their transformation into a tamoxifen-resistant phenotype, proof was provided for the causative role of BCAR genes (Van Agthoven et al, Breast Cancer Res Treat DOI:10.1007/s10549-008-9969-5, 2008). To elucidate the mechanisms how these individual BCAR genes induce cell proliferation in growth-arrested ZR-75-1 cells, we assessed the gene expression patterns between the different groups of cell lines. Keywords: Expression profiling, reference design RNA was isolated from two independent cultures of 69 tamoxifen-resistant cell lines. Detailed information regarding these cell lines with respect to the viral integration sites, was described previously (Van Agthoven et al, Breast Cancer Res Treat DOI:10.1007/s10549-008-9969-5, 2008). Each sample was hybridized in duplicate/triplicate and once in a dye-swap. The mixture of cell lines used as a reference was detailed previously (Jansen et al, J Clin Oncol 23, 732, 2005).

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

Project description:Membrane vesicles released by neoplastic cells into extracellular medium contain potential of carrying arrays of oncogenic molecules including proteins and microRNAs (miRNA). Extracellular (exosome-like) vesicles play a major role in cell-to-cell communication. Thus, the characterization of miRNAs of exosome-like vesicles is imperative in clarifying intercellular signaling as well as identifying disease markers. microarray analysis identified several oncogenic miRNA between the two types vesicles. Exosome-like vesicles were isolated using gradient centrifugation from MCF-7 and MDA-MB 231 cultures. Sample-derived miRNA expression was analyzed on Miltenyi's miRXplore™ platform. The RNA was isolated from two replicate samples of MDA-MB231 and MCF7 cell lines. The miRNAs extracted from all four samples were labeled with Hy5 and hybridized against Hy3-labeled Universal Reference miRNA (UR). Candidate miRNAs were identified. In this report, the re-ratios of MDA1 or MDA2 relative to a virtual pool of both MCF7 samples 1 and 2 were used for further analyses. 1- Reratio No. 7 MDA 1 vs MCF7 1+2 reratios of (MDA 1 vs UR) and (MCF7 1 vs UR + MCF7 2 vs UR) 7970041, (7970039 + 7970040) 2- Reratio No. 8 MDA 2 vs MCF7 1+2 reratios of (MDA 2 vs UR) and (MCF7 1 vs UR + MCF7 2 vs UR) 7970042, (7970039 + 7970040) Exosome-like vesicles were isolated using gradient centrifugation from MCF-7 and MDA-MB 231 cultures. Sample-derived miRNA expression was analyzed on Miltenyi's miRXplore™ platform. The RNA was isolated from two replicate samples of MDA-MB231 and MCF7 cell lines. The miRNAs extracted from all four samples were labeled with Hy5 and hybridized against Hy3-labeled Universal Reference miRNA (UR). Candidate miRNAs were identified. In this report, the re-ratios of MDA1 or MDA2 relative to a virtual pool of both MCF7 samples 1 and 2 were used for further analyses. 1- Reratio No. 7 MDA 1 vs MCF7 1+2 reratios of (MDA 1 vs UR) and (MCF7 1 vs UR + MCF7 2 vs UR) 7970041, (7970039 + 7970040) 2- Reratio No. 8 MDA 2 vs MCF7 1+2 reratios of (MDA 2 vs UR) and (MCF7 1 vs UR + MCF7 2 vs UR) 7970042, (7970039 + 7970040)

Dataset Information

Hemimethylation Patterns in Breast Cancer Cell Lines.

Publications

Hemimethylation Patterns in Breast Cancer Cell Lines.

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