MiR-193b promoter methylation accurately detects prostate cancer in urine sediments and miR-34b/c or miR-129-2 promoter methylation define subsets of clinically aggressive tumors

Background: Contemporary challenges of prostate cancer (PCa) include overdiagnosis and overtreatment, entailing the need for novel clinical tools to improve risk stratification and therapy selection. PCa diagnosis and prognostication might be perfected using epigenetic biomarkers, among which aberrant DNA methylation of microRNA promoters has not been systematically explored. Herein, we identified aberrantly methylated microRNAs promoters in PCa and assessed its diagnostic and prognostic biomarker potential. Methods: Using HumanMethylation450 BeadChip-based analysis differentially methylated CpGs in microRNA promoters were identified. Promoter methylation of six microRNAs (miR-34b/c, miR-129-2, miR-152, miR-193b, miR-663a and miR-1258) was analyzed by qMSP in three sets (180 prostatectomies, 95 urine sediments and 74 prostate biopsies). Biomarkers’ diagnostic (validity estimates) and prognostic [disease-free (DFS) and disease-specific survival (DSS)] performance was assessed. Results: Significantly higher promoter methylation levels in PCa were confirmed for six candidate microRNAs. Except for miR-152, all displayed AUC values higher than 0.90, with miR-1258 and miR-193b disclosing the best performance (AUC = 0.99 and AUC = 0.96, respectively). In urine samples, miR-193b showed the best performance (91.6% sensitivity, 95.7% specificity, AUC = 0.96). Moreover, higher miR-129-2 independently predicted for shorter DSS and miR−34b/c methylation levels independently predicted for shorter DFS and DSS. Conclusions: Quantitative miR-193b, miR-129-2 and miR-34b/c promoter methylation might be clinically useful PCa biomarkers for non-invasive detection/diagnosis and prognostication, both in tissue and urine samples.The authors would like to acknowledge funding attributed to this study, namely research grants from Research Center of Portuguese Oncology Institute of Porto (CI-IPOP 4–2012; CI-IPOP 19–2016)) and by Federal funds through Programa Operacional Temático Factores de Competitividade (COMPETE) with co-participation from the European Community Fund (FEDER) and by national funds through Fundação para a Ciência e Tecnología (FCT) under the projects EXPL/BIM-ONC/0556/2012. JRC was supported by a FCT-Fundação para a Ciência e a Tecnologia fellowship (SFRH/BD/71293/2010)

H3K4me1 marks DNA regions hypomethylated during aging in human stem and differentiated cells

In differentiated cells, aging is associated with hypermethylation of DNA regions enriched in repressive histone post-translational modifications. However, the chromatin marks associated with changes in DNA methylation in adult stem cells during lifetime are still largely unknown. Here, DNA methylation profiling of mesenchymal stem cells (MSCs) obtained from individuals aged 2 to 92 yr identified 18,735 hypermethylated and 45,407 hypomethylated CpG sites associated with aging. As in differentiated cells, hypermethylated sequences were enriched in chromatin repressive marks. Most importantly, hypomethylated CpG sites were strongly enriched in the active chromatin mark H3K4me1 in stem and differentiated cells, suggesting this is a cell type–independent chromatin signature of DNA hypomethylation during aging. Analysis of scedasticity showed that interindividual variability of DNA methylation increased during aging in MSCs and differentiated cells, providing a new avenue for the identification of DNA methylation changes over time. DNA methylation profiling of genetically identical individuals showed that both the tendency of DNA methylation changes and scedasticity depended on nongenetic as well as genetic factors. Our results indicate that the dynamics of DNA methylation during aging depend on a complex mixture of factors that include the DNA sequence, cell type, and chromatin context involved and that, depending on the locus, the changes can be modulated by genetic and/or external factors

沃度保兒謨ニ因セル濕疹

Evaluation of CNA-IC50 correlations by known cancer driver mutations. Distributions of PCCs for cancer cell lines with mutated or wild-type proto-oncogenes or tumor suppressors as depicted in each figure. The rank position of negatively correlated drugs (p < 0.10) is shown. (EPS 975 kb

Novel Insights into DNA Methylation Features in Spermatozoa: Stability and Peculiarities

<div><p>Data about the entire sperm DNA methylome are limited to two sperm donors whereas studies dealing with a greater number of subjects focused only on a few genes or were based on low resolution arrays. This implies that information about what we can consider as a normal sperm DNA methylome and whether it is stable among different normozoospermic individuals is still missing. The definition of the DNA methylation profile of normozoospermic men, the entity of inter-individual variability and the epigenetic characterization of quality-fractioned sperm subpopulations in the same subject (intra-individual variability) are relevant for a better understanding of pathological conditions. We addressed these questions by using the high resolution Infinium 450K methylation array and compared normal sperm DNA methylomes against somatic and cancer cells. Our study, based on the largest number of subjects (n = 8) ever considered for such a large number of CpGs (n = 487,517), provided clear evidence for i) a highly conserved DNA methylation profile among normozoospermic subjects; ii) a stable sperm DNA methylation pattern in different quality-fractioned sperm populations of the same individual. The latter finding is particularly relevant if we consider that different quality fractioned sperm subpopulations show differences in their structural features, metabolic and genomic profiles. We demonstrate, for the first time, that DNA methylation in normozoospermic men remains highly uniform regardless the quality of sperm subpopulations. In addition, our analysis provided both confirmatory and novel data concerning the sperm DNA methylome, including its peculiar features in respect to somatic and cancer cells. Our description about a highly polarized sperm DNA methylation profile, the clearly distinct genomic and functional organization of hypo- versus hypermethylated loci as well as the association of histone-enriched hypomethylated loci with embryonic development, which we now extended also to hypomethylated piRNAs-linked genes, provides solid basis for future basic and clinical research.</p> </div

Bar graph illustrating the percentage of hypermethylated and hypomethylated CpGs in swim-up sperm samples and B cells.

<p>The number of detected CpGs varies according to the data extrapolation performed separately for each tested group: i) total CpGs, ii) autosomal CpGs, iii) X chromosome-linked CpGs and iv) Y chromosome-linked CpGs. * corresponds to p values <0.05 (the whiskers show the SD; n = 7).</p

Description of CpGs in terms of number and methylation status in the swim-up sperm fraction and in B cells.

<p>The number of hypomethylated and hypermethylated loci are indicated as total, autosomic, X chromosome and Y chromosome-linked. A) Sperm CpG numbers refer singularly to the eight normozoospermic men, while B cells CpG numbers belong to two different subjects. The mean CpG number ± DS and the percentage calculated in respect to the mean total CpG number for each group are reported in the middle panel; B) Number of CpGs conserved among individuals: the first raw reports the number of CpGs shared by individuals, while the second raw reports the percentage of conserved CpGs compared to the mean CpG number reported in panel A.</p

Heatmap displaying the methylation status of CpG loci (n = 297) mapping in 10 selected genes in relation to quality-fractioned sperm populations (i.e. swim-up “up” and swim-down “dn” sperm fractions).

<p>A) The dendrograms above the heatmap show hierarchical clustering based on the methylation data alone. Sperm populations and CpG loci are represented by columns and rows, respectively. Each cell indicates the CpG methylation level for one site in each sample. Methylation levels are represented in the scale on the right side of the heatmap and are referred lowest to highest as green (0.0) to red (1.0). B) Scatter plot reporting CpGs methylation levels between quality-fractioned sperm populations (Up vs Dn) among different individuals. R² = Pearson coefficient. C) List of the 10 analyzed genes, selected because previously reported as differently methylated in infertile men compared to normozoospermic controls.</p

Spermatozoa versus B cell: a 450K DNA methylation portrait.

<p>(A) Graph showing percentages of equally and differentially methylated CpG sites in swim-up sperm samples compared to B cells. (B) Graph showing percentages of hypermethylation and hypomethylation in spermatozoa relating to the differentially methylated CpGs proportion (4,3%). Graphs describing the hypermethylated (C) and hypomethylated (D) sites according to their i) functional genomic distribution; ii) CpG content/neighborhood context and iii) association with RNA transcripts.</p

Representative scatter plots reporting CpG methylation levels between different individuals EC01 and EC10.

<p>(A) swim-up (Up) sperm samples; (B) swim-down (Dn) sperm samples; (C) whole sperm population at 1 h (Ws 1 h) samples; (D) Box plot representing the inter-individual variability of DNA methylation levels in total CpGs from the swim-up, swim-down and whole sperm population at1h samples. The median value is shown. * corresponds to p value = 0.0213; R2  = Pearson coefficient. The boxes describe the lower quartile (Q1, 25%), median (Q2, 50%) and the upper quartile (Q3, 75%); the whiskers extend 1.5 times the IQR from the box.</p

Heatmap displaying the methylation status of CpG loci (n = 2386) mapping in the promoters of 45 imprinted genes in relation to quality-fractioned sperm populations (i.e. swim-up “up” and swim- “dn” sperm fractions).

<p>A) The dendrograms above the heatmap show hierarchical clustering based on the methylation data alone. Sperm populations and CpG loci are represented by columns and rows, respectively. Each cell indicates the CpG methylation level for one site in each sample. Methylation levels are represented in the scale on the right side of the heatmap and are referred lowest to highest as green (0.0) to red (1.0). (B) List of the 45 imprinted gene available in the array.</p