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Validation of Illumina 450 K DNA methylation bead array by Pyrosequencing. Correlations between Illumina 450 K array data and pyrosequence analysis. Representative data for CpG sites in cg27182070 (RPA2), cg16624210 (TPPP), cg19761014 (LRRC37B2), cg00481259 (DECR2), cg07271186 (TRY2P), cg01252526 (WDR9), and genes is shown 

Validation of Illumina 450 K DNA methylation bead array by Pyrosequencing. Correlations between Illumina 450 K array data and pyrosequence analysis. Representative data for CpG sites in cg27182070 (RPA2), cg16624210 (TPPP), cg19761014 (LRRC37B2), cg00481259 (DECR2), cg07271186 (TRY2P), cg01252526 (WDR9), and genes is shown 

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Background: Immune surveillance acts as a defense mechanism in cancer, and its disruption is involved in cancer progression. DNA methylation reflects the phenotypic identity of cells and recent data suggested that DNA methylation profiles of T cells and peripheral blood mononuclear cells (PBMC) are altered in cancer progression. Methods: We enro...

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... determined a correlation between DNA methylation levels obtained from Illumina 450 K and pyrosequenc- ing. Pyrosequencing analysis was limited by the remaining amount of T-cell DNA. A few representative samples were used for validation purposes. Nine normal and five breast cancer T-cell DNA samples were sub- jected to bisulphite conversion and pyrosequencing ana- lysis. Seven CG probes that varied across the samples were randomly selected. Figure 3 shows the correlation between values obtained by Illumina analysis and pyro- sequencing for these CGs. Correlations were significant for all probes with r values between 0.5 and 0.8 ( Fig. ...
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... determined a correlation between DNA methylation levels obtained from Illumina 450 K and pyrosequenc- ing. Pyrosequencing analysis was limited by the remaining amount of T-cell DNA. A few representative samples were used for validation purposes. Nine normal and five breast cancer T-cell DNA samples were sub- jected to bisulphite conversion and pyrosequencing ana- lysis. Seven CG probes that varied across the samples were randomly selected. Figure 3 shows the correlation between values obtained by Illumina analysis and pyro- sequencing for these CGs. Correlations were significant for all probes with r values between 0.5 and 0.8 ( Fig. ...
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... gene panel shown in Fig. 3 was further ana- lyzed using the KM plotter (Kaplan-Meier plotter) data- base of breast cancer patients in order to investigate the prognostic significance of the genes in breast cancer relapse-free survival. The KM-plotter database was gen- erated by Gyorffy et al. using the NCBI Gene Expression Omnibus (GEO) repository of gene expression and pa- tient survival information [21], and is often used to investigate the clinical significance of particular gene(s) in several common cancers. Using gene expression data from 1764 breast cancer patients, an association between the decreased expression of genes identified and vali- dated in Fig. 3 was observed with a lower incidence of relapse-free or disease-free survival (Fig. 4). The high or low expression groups were classified according to whether the combined expression of the genes was greater than their median ...
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... gene panel shown in Fig. 3 was further ana- lyzed using the KM plotter (Kaplan-Meier plotter) data- base of breast cancer patients in order to investigate the prognostic significance of the genes in breast cancer relapse-free survival. The KM-plotter database was gen- erated by Gyorffy et al. using the NCBI Gene Expression Omnibus (GEO) repository of gene expression and pa- tient survival information [21], and is often used to investigate the clinical significance of particular gene(s) in several common cancers. Using gene expression data from 1764 breast cancer patients, an association between the decreased expression of genes identified and vali- dated in Fig. 3 was observed with a lower incidence of relapse-free or disease-free survival (Fig. 4). The high or low expression groups were classified according to whether the combined expression of the genes was greater than their median ...
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... list of 89 CGs clusters all individuals by their cancer stage, pointing to the possibility of using a combination of CG methylation states to detect and stage breast cancer early noninvasively. It is important to note that these CGs detect early stages of breast cancer and no association was found with allergy, immune mediated disorders or inflam- mation [30,31]. Genes validated in Fig. 3 are involved in DNA replication and repair, cell cycle, mitosis, oligo- dendrocyte differentiation, tubulin polymerization, signal transduction, transcription regulation, autophagy, apop- tosis and regulation of lipid metabolism, which collectively play an important role in several malignancies including breast cancer. The uniqueness of the identified signatures was further confirmed by the survival-curve generated from their gene expression profile in breast cancer (Fig. 4). Future prospective clinical studies are required to determine whether they can detect breast cancer earlier than currently available imaging methods. In these cases, loss of DNA methylation associated with advanced breast cancer stage may in fact reflect the demethylation of pro-metastatic genes as previously described by us [32][33][34][35]. Results from these studies are in line with identi- fied CpG probes which showed a change in DNA methy- lation and correlation with disease progression in liver cancer patients [16]. We also observed overlap of probes among DCIS, mixed and invasive breast cancer, their asso- ciation with canonical pathways and upstream regulators of gene expression (Additional file 1: Tables ...

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... Previous studies have found alterations in DNA methylation patterns of peripheral blood leukocytes in the liver [8], prostate [9], and breast cancers [10]. Due to the excellent stability of DNA compared to other biological materials, such as RNAs or proteins, DNA methylation can be easily detected in small specimens, making it suitable for largescale epidemiological studies. ...
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... Furthermore, the transcription start sites (TSS) of BC patients were hypomethylated compared with normal controls (Fig. 2c), which may be related to the immune activation in BC patients. This finding is consistent with the results from ref. 30. The differentially methylated genes were then subjected to pathway analysis. ...
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... In several studies, blood-based DNA methylation has been pro led to develop a robust diagnostic marker for cancer. The blood-based methylation studies are broadly divided into investigating global DNA methylation [29] and gene-speci c targeted DNA methylation [18]. In addition, according to the source of DNA, these studies mainly targeted circulating tumor cells (CTCs) and cell-free DNA in serum or plasma [30]. ...
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Full-text available
Background Genome-wide dysregulation of CpG methylation accompanies tumor progression and characteristic states of cancer cells, prompting a rationale for biomarker development. Understanding how the archetypic epigenetic modification determines systemic contributions of immune cell types is the key to further clinical benefits. Results In this study, we characterized the differential DNA methylome landscapes of peripheral blood mononuclear cells (PBMCs) from 76 canines using methylated CpG-binding domain sequencing (MBD-seq). Through gene set enrichment analysis, we discovered that genes involved in the growth and differentiation of T- and B-cells are highly methylated in tumor PBMCs. We also revealed the increased methylation at single CpG resolution and reversed expression in representative marker genes regulating immune cell proliferation (BACH2, SH2D1A, TXK, UHRF1). Furthermore, we utilized the PBMC methylome to effectively differentiate between benign and malignant tumors and the presence of mammary gland tumors through a machine-learning approach. Conclusions This research contributes to a better knowledge of the comprehensive epigenetic regulation of circulating immune cells responding to tumors and suggests a new framework for identifying benign and malignant cancers using genome-wide methylome.
... As we know, the methylation status is dynamic. External factors, such as viral infection, burn, and tobacco, could alter the methylation status (26)(27)(28)(29). Furthermore, several studies have shown early changes of Alu element methylation in cancer (28,30). ...
... External factors, such as viral infection, burn, and tobacco, could alter the methylation status (26)(27)(28)(29). Furthermore, several studies have shown early changes of Alu element methylation in cancer (28,30). Moreover, this alteration in methylation has also been found preclinically (22). ...
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