Dataset Information

Differential DNA methylation analysis of breast cancer reveals the impact of immune signaling in radiation therapy.

ABSTRACT: Radiotherapy (RT) is a central treatment modality for breast cancer patients. The purpose of our study was to investigate the DNA methylation changes in tumors following RT, and to identify epigenetic markers predicting treatment outcome. Paired biopsies from patients with inoperable breast cancer were collected both before irradiation (n = 20) and after receiving 10-24 Gray (Gy) (n = 19). DNA methylation analysis was performed by using Illumina Infinium 27K arrays. Fourteen genes were selected for technical validation by pyrosequencing. Eighty-two differentially methylated genes were identified in irradiated (n = 11) versus nonirradiated (n = 19) samples (false discovery rate, FDR = 1.1%). Methylation levels in pathways belonging to the immune system were most altered after RT. Based on methylation levels before irradiation, a panel of five genes (H2AFY, CTSA, LTC4S, IL5RA and RB1) were significantly associated with clinical response (p = 0.041). Furthermore, the degree of methylation changes for 2,516 probes correlated with the given radiation dose. Within the 2,516 probes, an enrichment for pathways involved in cellular immune response, proliferation and apoptosis was identified (FDR < 5%). Here, we observed clear differences in methylation levels induced by radiation, some associated with response to treatment. Our study adds knowledge on the molecular mechanisms behind radiation response.

SUBMITTER: Halvorsen AR

PROVIDER: S-EPMC4298788 | biostudies-literature | 2014 Nov

REPOSITORIES: biostudies-literature

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Differential DNA methylation analysis of breast cancer reveals the impact of immune signaling in radiation therapy.

Halvorsen Ann Rita AR Helland Aslaug A Fleischer Thomas T Haug Karen Marie KM Grenaker Alnaes Grethe Irene GI Nebdal Daniel D Syljuåsen Randi G RG Touleimat Nizar N Busato Florence F Tost Jörg J Saetersdal Anna B AB Børresen-Dale Anne-Lise AL Kristensen Vessela V Edvardsen Hege H

International journal of cancer 20140405 9

Radiotherapy (RT) is a central treatment modality for breast cancer patients. The purpose of our study was to investigate the DNA methylation changes in tumors following RT, and to identify epigenetic markers predicting treatment outcome. Paired biopsies from patients with inoperable breast cancer were collected both before irradiation (n = 20) and after receiving 10-24 Gray (Gy) (n = 19). DNA methylation analysis was performed by using Illumina Infinium 27K arrays. Fourteen genes were selected ...[more]

PMID: 24658971

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Project description:Background: DNA methylation played essential roles in regulating gene expression. The impact of DNA methylation status on the occurrence and development of cancers has been well demonstrated. However, little is known about its prognostic role in breast cancer (BC). Materials: The Illumina Human Methylation450 array (450k array) data of BC was downloaded from the UCSC xena database. Transcriptomic data of BC was downloaded from the Cancer Genome Atlas (TCGA) database. Firstly, we used univariate and multivariate Cox regression analysis to screen out independent prognostic CpGs, and then we identified methylation-associated prognosis subgroups by consensus clustering. Next, a methylation prognostic model was developed using multivariate Cox analysis and was validated with the Illumina Human Methylation27 array (27k array) dataset of BC. We then screened out differentially expressed genes (DEGs) between methylation high-risk and low-risk groups and constructed a methylation-based gene prognostic signature. Further, we validated the gene signature with three subgroups of the TCGA-BRCA dataset and an external dataset GSE146558 from the Gene Expression Omnibus (GEO) database. Results: We established a methylation prognostic signature and a methylation-based gene prognostic signature, and there was a close positive correlation between them. The gene prognostic signature involved six genes: IRF2, KCNJ11, ZDHHC9, LRP11, PCMT1, and TMEM70. We verified their expression in mRNA and protein levels in BC. Both methylation and methylation-based gene prognostic signatures showed good prognostic stratification ability. The AUC values of 3-years, 5-years overall survival (OS) were 0.737, 0.744 in the methylation signature and 0.725, 0.715 in the gene signature, respectively. In the validation groups, high-risk patients were confirmed to have poorer OS. The AUC values of 3 years were 0.757, 0.735, 0.733 in the three subgroups of TCGA dataset and 0.635 in GSE146558 dataset. Conclusion: This study revealed the DNA methylation landscape and established promising methylation and methylation-based gene prognostic signatures that could serve as potential prognostic biomarkers and therapeutic targets.

Project description:BackgroundThis study aims to determine whether NEFM (neurofilament medium) DNA methylation correlates with immune infiltration and prognosis in breast cancer (BRCA) and to explore NEFM-connected immune gene signature.MethodsNEFM transcriptional expression was analyzed in BRCA and normal breast tissues using Oncomine and Tumor Immune Estimation Resource (TIMER) databases. The relationship between NEFM DNA methylation and NEFM transcriptional expression was investigated in TCGA. Potential influence of NEFM DNA methylation/expression on clinical outcome was evaluated using TCGA BRCA, The Human Protein Atlas and Kaplan-Meier plotter databases. Association of NEFM transcriptional expression/DNA methylation with cancer immune infiltration was investigated using TIMER and TISIDB databases.ResultsHigh expression of NEFM correlated with better overall survival (OS) and recurrence-free survival (RFS) in TCGA BRCA and Kaplan-Meier plotter, whereas NEFM DNA methylation with worse OS in TCGA BRCA. NEFM transcriptional expression negatively correlated with DNA methylation. NEFM DNA methylation significantly negatively correlated with infiltrating levels of B, CD8+ T/CD4+ T cells, macrophages, neutrophils and dendritic cells in TIMER and TISIDB. NEFM expression positively correlated with macrophage infiltration in TIMER and TISIDB. After adjusted with tumor purity, NEFM expression weekly negatively correlated with infiltration level of B cells, whereas positively correlated with CD8+ T cell infiltration in TIMER gene modules. NEFM expression/DNA methylation correlated with diverse immune markers in TCGA and TISIDB.ConclusionsNEFM low-expression/DNA methylation correlates with poor prognosis. NEFM expression positively correlates with macrophage infiltration. NEFM DNA methylation strongly negatively correlates with immune infiltration in BRCA. Our study highlights novel potential functions of NEFM expression/DNA methylation in regulation of tumor immune microenvironment.

Project description:Estrogen signaling and epigenetic modifications, in particular DNA methylation, are involved in regulation of gene expression in breast cancers. Here we investigated a potential regulatory cross-talk between these two pathways by identifying their common target genes and exploring potential underlying molecular mechanisms in human MCF7 breast cancer cells. Principal Findings: Gene expression profiling revealed that the expression of approximately 150 genes was influenced by both 17β-estradiol (E2) and a hypomethylating agent 5-aza-2’-deoxycytidine (DAC). Based on gene ontology (GO), CpG island prediction analysis and previously reported estrogen receptor (ER) binding regions, we selected six genes for further analysis (BTG3, FHL2, PMAIP1, BTG2, CDKN1A and TGFB2). GO analysis suggests that these genes are involved in intracellular signaling cascades, regulation of cell proliferation and apoptosis, while CpG island prediction of promoter regions reveals that the promoters of these genes contain at least one CpG island. Using chromatin immunoprecipitation, we show that ERα is recruited to CpG islands in promoters, but neither in an E2- nor in a DAC-dependent fashion. DAC treatment reactivates the expression of all selected genes although only the promoters of BTG3 and FHL2 genes are methylated, with E2 treatment showing no effect on the methylation status of these promoters. Conclusions: We identified a set of genes regulated by both estrogen signaling and DNA methylation. However, our data does not support a direct molecular interplay of mediators of estrogen and epigenetic signaling at promoters of regulated genes. The aim of the study was to identify genes regulated by estrogen signaling and DNA methylation, using microarray approach. We compared the effects of E2 and DAC on global gene expression profiles in MCF7 cells. By comparing C_E2 (MP5-MP8 average) with C_EtOh samples (MP1-MP4 average), 802 genes were identified as up-regulated by E2, while 851 genes were identified as down-regulated by E2. 1017 genes were identified as up-regulated by DAC, by comparing A_EtOh (MP9-MP12 average) samples with C_EtOh, suggesting that DNA methylation is involved in their regulation. To identify possible common targets, we have compared the DAC up-regulated genes with E2-regulated genes. 88 annotated genes are found to be up-regulated by both E2 and DAC, suggesting that E2 has a hypomethylation-like effect on the regulation of these genes. 58 annotated genes are found to be down-regulated by E2 and up-regulated by DAC, suggesting that E2 has a hypermethylation-like effect on the regulation of these genes.

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Differential DNA methylation analysis of breast cancer reveals the impact of immune signaling in radiation therapy.

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Differential DNA methylation analysis of breast cancer reveals the impact of immune signaling in radiation therapy.

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