Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA298905 | ENA |
REPOSITORIES: ENA
Similar Datasets
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Project description:mRNA expression profiling of pancreatic cancer, comparing adjacent normal tissue, patient tumour and first generation patient derived xenograft tumours Fresh tumour samples for human pancreatic adenocarcinoma patients were implanted in SCID mice. 70% of these pancreatic ductal adenocarcinoma patients grew as PDX tumours, confirmed by histopathology. Frozen samples from F1 PDX tumours could be later successful passaged in SCID mice to F2 PDX tumours. The human origin of the PDX was confirmed using human specific antibodies; however, the stromal component was replaced by murine cells. Cell lines were successfully developed from three PDX tumours. RNA was extracted from 8 PDX tumours and where possible, corresponding primary tumour and adjacent normal tissues. mRNA profiles of tumour vs F1 PDX and normal vs tumour were compared by Affymetric microarray analysis
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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.
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Project description:Genome wide DNA methylation profiling of tumor adjacent normal tissue from patients with invasive breast cancer, as well as tissue from women undergoing reduction mammoplasty or prophylactic surgery. The Illumina Infinium 450k Human DNA methylation Beadchip was used to obtain DNA methylation profiles across approximately 485,577 CpGs in snap frozen breast tissue. Samples included 70 tumor-adjacent normal breast tissue with invasive disease, 8 tissues from breast prophylactic patients, and 18 tissues from breast reduction patients.
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