Dataset Information

DNA methylation signatures of breast cancer in peripheral T-cells.

ABSTRACT: 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 enrolled 19 females with stage 1 and 2, nine with stage 3 and 4 and 9 age matched healthy women. T cells were isolated from peripheral blood and extracted DNA was subjected to Illumina 450 K DNA methylation array analysis. Raw data was analyzed by BMIQ, ChAMP and ComBat followed by validation of identified genes by pyrosequencing. RESULTS:Analysis of data revealed ~?10,000 sites that correlated with breast cancer progression and established a list of 89 CG sites that were highly correlated (p??0.7, r?

SUBMITTER: Parashar S

PROVIDER: S-EPMC5960123 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature

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DNA methylation signatures of breast cancer in peripheral T-cells.

Parashar Surabhi S Cheishvili David D Mahmood Niaz N Arakelian Ani A Tanvir Imrana I Khan Haseeb Ahmed HA Kremer Richard R Mihalcioiu Catalin C Szyf Moshe M Rabbani Shafaat A SA

BMC cancer 20180518 1

<h4>Background</h4>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.<h4>Methods</h4>We enrolled 19 females with stage 1 and 2, nine with stage 3 and 4 and 9 age matched healthy women. T cells were isolated from peripheral blood and ...[more]

PMID: 29776342

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Project description:BackgroundProstate Cancer (PCa) is the second most common cancer in men where advancements have been made for early detection using imaging techniques, however these are limited by lesion size. Immune surveillance has emerged as an effective approach for early detection and to monitor disease progression. In recent studies, we have shown that host peripheral blood immune cells undergo changes in DNA methylation in liver and breast cancer.MethodsIn the current study, we examined the DNA methylation status of peripheral blood T cells of men with positive biopsy for PCa versus men with negative biopsy having benign prostate tissue, defined as controls. T cells DNA was isolated and subjected to Illumina Infinium methylation EPIC array and validated using Illumina amplicon sequencing and pyrosequencing platforms.ResultsDifferential methylation of 449 CG sites between control and PCa T cell DNA showed a correlation with Gleason score (p < 0.05). Two hundred twenty-three differentially methylated CGs between control and PCa (∆ß +/- 10%, p < 0.05), were enriched in pathways involved in immune surveillance system. Three CGs which were found differentially methylated following DMP (Differentially methylated probes) analysis of ChAMP remained significant after BH (Benjamini-Hochberg) correction, of which, 2 CGs were validated. Predictive ability of combination of these 3 CGs (polygenic methylation score, PMS) to detect PCa had high sensitivity, specificity and overall accuracy. PMS also showed strong positive correlation with Gleason score and tumor volume of PCa patients.ConclusionsResults from the current study provide for the first-time a potential role of DNA methylation changes in peripheral T cells in PCa. This non-invasive methodology may allow for early intervention and stratification of patients into different prognostic groups to reduce PCa associated morbidity from repeat invasive prostate biopsies and design therapeutic strategy to reduce PCa associated mortality.

Project description:Background: Biomarkers predicting response to bevacizumab in breast cancer are still missing. Since epigenetic modifications can contribute to an aberrant regulation of angiogenesis and treatment resistance, we investigated the influence of DNA methylation patterns on bevacizumab efficacy. Methods: Genome-wide methylation profiling using the Illumina Infinium HumanMethylation450 BeadChip was performed in archival FFPE specimens of 36 patients with HER2-negative metastatic breast cancer treated with chemotherapy in combination with bevacizumab as first-line therapy (learning set). Based on objective response and progression-free survival (PFS) and considering ER expression, patients were divided in responders (R) and non-responders (NR). Significantly differentially methylated gene loci (CpGs) with a strong change in methylation levels (??>0.15 or ??<-0.15) between R and NR were identified and further investigated in 80 bevacizumab-treated breast cancer patients (optimization set) and in 15 patients treated with chemotherapy alone (control set) using targeted deep amplicon bisulfite sequencing. Methylated gene loci were considered predictive if there was a significant association with outcome (PFS) in the optimization set but not in the control set using Spearman rank correlation, Cox regression, and logrank test. Results: Differentially methylated loci in 48 genes were identified, allowing a good separation between R and NR (odds ratio (OR) 101, p<0.0001). Methylation of at least one cytosine in 26 gene-regions was significantly associated with progression-free survival (PFS) in the optimization set, but not in the control set. Using information from the optimization set, the panel was reduced to a 9-gene signature, which could divide patients from the learning set into 2 clusters, thereby predicting response with an OR of 40 (p<0.001) and an AUC of 0.91 (LOOCV). A further restricted 3-gene methylation model showed a significant association of predicted responders with longer PFS in the learning and optimization set even in multivariate analysis with an excellent and good separation of R and NR with AUC=0.94 and AUC=0.86, respectively. Conclusion: Both a 9-gene and 3-gene methylation signature can discriminate between R and NR to a bevacizumab-based therapy in MBC and could help identify patients deriving greater benefit from bevacizumab.

Dataset Information

DNA methylation signatures of breast cancer in peripheral T-cells.

Publications

DNA methylation signatures of breast cancer in peripheral T-cells.

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