Project description:Genome-wide DNA Methylation Data from Illumina HumanMethylationEPIC arrays for whole blood samples from 570 healthy individuals. Raw IDAT files are available for a subset of 403 samples on EGA. Raw data (IDAT files) and associated phenotype information are available for all individuals included in this study (n=570) directly from CIBMTR. Data are available under controlled access release upon reasonable request and execution of a data use agreement. Requests should be submitted to CIBMTR at info-request@mcw.edu and include the study reference IB17-04.
Project description:We report RNA-sequencing data of 283 blood platelet samples, including 228 tumor-educated platelet (TEP) samples collected from patients with six different malignant tumors (non-small cell lung cancer, colorectal cancer, pancreatic cancer, glioblastoma, breast cancer and hepatobiliary carcinomas). In addition, we report RNA-sequencing data of blood platelets isolated from 55 healthy individuals. This dataset highlights the ability of TEP RNA-based 'liquid biopsies' in patients with several types with cancer, including the ability for pan-cancer, multiclass cancer and companion diagnostics.
Project description:Neuroepigenetics considers genetic sequences and the interplay with environmental influences to elucidate vulnerability risk for various neurological and psychiatric disorders. However, evaluating DNA methylation of brain tissue is challenging owing to the issue of tissue specificity. Consequently, peripheral surrogate tissues were used, resulting in limited progress compared with other epigenetic studies, such as cancer research. Therefore, we developed databases to establish correlations between the brain and peripheral tissues in the same individuals. Four tissues, resected brain tissue, blood, saliva, and buccal mucosa (buccal), were collected from 19 patients (aged 13–73 years) who underwent neurosurgery. Moreover, their genome-wide DNA methylation was assessed using the Infinium HumanMethylationEPIC BeadChip arrays to determine the cross-tissue correlation of each combination. These correlation analyses were conducted with all methylation sites and with variable CpGs, and with when these were adjusted for cellular proportions. For the averaged data for each CpG across individuals, the saliva–brain correlation (r = 0.90) was higher than that for blood–brain (r = 0.87) and buccal–brain (r = 0.88) comparisons. Among individual CpGs, blood had the highest proportion of CpGs correlated to the brain at nominally significant levels (19.0%), followed by saliva (14.4%) and buccal (9.8%). These results were similar to the previous IMAGE-CpG results; however, the correlation analysis between the correlation coefficients of the datasets revealed a relatively low degree of correlation (brain vs. blood: r = 0.27, saliva; r = 0.18, and buccal; r = 0.24). To the best of our knowledge, this is the fourth study in the literature initiating the development of databases for correlations between the brain and peripheral tissues in the same individuals. We present the first database developed from an Asian population, specifically Japanese samples (AMAZE-CpG), which would contribute to interpreting individual epigenetic study results from various Asian populations.
Project description:DNA methylation alterations have similar patterns in normal aging tissue and in cancer. In this study, we investigated breast tissue-specific age-related DNA methylation alterations and used those methylation sites to identify individuals with outlier phenotypes. Outlier phenotype is identified by unsupervised anomaly detection algorithms and is defined by individuals who have normal tissue age-dependent DNA methylation levels that vary dramatically from the population mean. To identify age-dependent DNA methylation sites, we generated DNA methylation sequencing data for 29 purified normal adjacent human breast epithelia (age range 33-82 years old) using Digital Restriction Enzyme Analysis of Methylation (DREAM). Next, we validated the age-related sites in publicly available DNA methylation (450K array) of 97 normal adjacent TCGA samples. We found that hypermethylation in normal breast tissue is the best predictor of hypermethylation in cancer. Using unsupervised anomaly detection approaches, we found that about 10% of the individuals (39 /427) were outliers for DNA methylation from 6 publicly available DNA methylation datasets (GSE88883, GSE74214, GSE101961, GSE69914(normal), GSE69914(normal-adjacent), TCGA (Firehose Legacy)). We also found that there were significantly more outlier samples in normal-adjacent to cancer (24/139, 17.3%) then in normal samples (15/228, 5.2%). Additionally, we found significant differences between predicted ages based on DNA methylation and the chronological ages among outliers and not-outliers. Additionally, we found that accelerated outliers (older predicted age) were more frequent in normal-adjacent to cancer (14/17, 82%) compared to normal samples from individuals without cancer (3/17, 18%). Furthermore, in matched samples, the epigenome of the outliers in the pre-malignant tissue was as severely altered as in cancer.
Project description:Canine mammary gland tumors (CMTs) have been suggested as promising cancer models to human breast cancer due to their many biological and clinical similarities. Here, we collected 222 samples consist of 158 tumor samples and 64 matched normal samples of CMTs. Fresh tissue samples were transferred in to RNAlater, and refrigerated overnight at 4°C and then stored at -80°C. Total RNA was extracted from tissues using RNeasy mini kit. We aligned RNA-Seq raw data from 222 samples to canine reference genome CanFam3.1 using Tophat. We assembled transcript and calculated FPKM values using Cufflinks. All tumor samples were evaluated by histopathological characteristics including histopathological subtype, grade, and lymphatic invasion, and annotated with corresponding sequencing data. The histopathological classification and the histological grading system of CMTs were adopted from those of human breast cancer. In addition, immunohistochemical evaluation was performed in samples for estrogen receptor (ER) and human epidermal growth factor receptor 2 (HER2) status. DISCLAIMER: Using this dataset became freely available on Jul 22, 2019. On the other hand, we are now preparing a key paper about comparative analysis of canine and human breast cancer based on this dataset. If you plan to submit a similar paper using this dataset before the main paper is published, please feel free to contact the submitter (swkim@yuhs.ac) to coordinate submission.
Project description:Inter-individual variability in DNA methylation has been hypothesized to contribute to complex phenotypes through epigenetic modulation of gene expression levels. Population epigenetic studies have been examining differences in DNA methylation in a variety of accessible tissues for association with specific diseases or exposures, but relatively little is known about how this inter-individual variation differs between tissues. This study presents an analysis of global DNA methylation differences between matched peripheral blood mononuclear cells and buccal epithelial cells; specifically it examines differential DNA methylation, probe-wise DNA methylation variance, and how methylation relates to a number of demographic factors across the two tissues. We found that peripheral blood mononuclear cells have overall higher DNA methylation than buccal epithelial cells, and regions of the genome that are differently methylated between the tissues tend to have low CpG density. We also discovered that although both tissues show extensive probe-wise variability, the specific regions and magnitude of variability differed between tissues. Finally, we observed that while both buccal epithelial and peripheral mononuclear blood cell DNA methylation was associated with gender, only methylation of the latter was associated with body mass index. The work presented here offers insight into variability of DNA methylation between individuals and across tissues and the suitability of buccal epithelial and peripheral mononuclear cells for the biological questions explored by epigenome-wide association studies in human populations. This cohort consist of genomic DNA extracted from the peripheral blood mononuclear cells and buccal epithelial cells of 25 individuals, bisulphite converted and hybridized to the Illumina GoldenGate Methylation Cancer Panel for genome wide DNA methylation profiling
Project description:A tissue like buccal mucosa (from cheek swabs) would be an ideal sample material for rapid, easy collection for testing of biomarkers as an alternative to blood. A limited number of studies, primarily in the smoker/oral cancer literature, address this tissue's efficacy for quantitative PCR or microarray gene expression analysis. In this study both qPCR and microarray analyses were used to evaluate gene expression in buccal cells. An initial study comparing blood and buccal cells from the same individuals looked at relative amounts of four genes. The RNA isolated from buccal cells was degraded but was of sufficient quality to be used with RT-qPCR to detect expression of specific genes. Second, buccal cell RNA was used for microarray-based differential gene expression studies by comparing gene expression between smokers and nonsmokers. The isolation and amplification protocol allowed use of 150-fold less buccal cell RNA than had been reported previously with human microarrays. We report here the finding of a small number of significant gene expression differences between smokers and nonsmokers, using buccal cells as target material. Additionally, Gene Set Enrichment Analysis confirmed that these genes were changing expression in the same pattern as seen in an earlier buccal cell study performed by another group. Our results suggest that in spite of a high degree of RNA degradation, buccal cells from cheek mucosa could be used to detect differential gene expression between smokers and nonsmokers. However the RNA degradation, increase in sample variability and microarray failure rate show that buccal samples should be used with caution as source material in expression studies. Samples were collected from eight subjects, four smokers (Sm)and four nonsmokers (NS). Each cheek was sampled creating an a and b sample for each subject which is reflected in the array name. All samples were isolated separately for total RNA. Each was hybridzed to microarrays to examine for differential gene expression between smokers and nonsmokers. There are 14 total samples in the main dataset (Set 2). One cheek sample failed in microarray analysis for two individuals, 08BCNS23 a and 08BCSm27 a, and so are not included here. A sample set (Set 1) was created which contains the four samples shown in this file. They represent repeated sampling of both cheeks for two individuals to test for reproducibility. There is a separate RMA file and metadata file (this file) for these data. These included samples 08BC11Sm a and b, a smoker, and 08BC12NSa and b a nonsmoker.