Methylation profiling defines a widespread field defect in histologically normal prostate tissue associated with prostate cancer
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Bing Yang
PROVIDER: E-GEOD-38982 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
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Project description:We evaluated the presence of genome-wide epigenetic differences at 385,000 loci using Encode HG18 DNA methylation arrays in 5 non-tumor-associated (NTA) and 4 histologically undistinguished tumor-associated (TA) prostate tissues. We identified 615 probes to be differentially methylated (p<0.05) in TA prostate, with 537 (87%) hypomethylated and 78 (13%) hypermethylated.
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Project description:High-throughput analyses of concordant gene methylation and expression events were carried out for 91 human prostate specimens, including prostate cancer (T), matched normal adjacent to tumor (AT), and organ donor (OD). Methylated DNA in genomic DNA was immunoprecipitated with anti-methylcytidine antibodies and detected by Affymetrix human whole genome SNP 6.0 chips. Methylated genomic DNA was purified by 5-hmc antibodies and Affymetrix SNP arrays were performed according to the manufacturer's manual. Copy number analysis of Affymetrix human SNP arrays was performed for both 5mc- and genomic DNA of prostate cancer samples. Methylations of genes were called when the allel amplification was reported in 5_mc DNA, and the background of the detection was suppressed by matched DNA sample. we used copy number of each probe set as baseline to detect the enrichment of methylated DNA from the same sample. Therefore, each specimen has two arrays; one is straight copy number (*SNP.CEL), another methylation enriched DNA (*5MC_SNP.CEL). Each CNV probe is based on the design from Affymetrix but no SNP ID was assigned.
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Project description:Beginning with precursor lesions, aberrant DNA methylation marks the entire spectrum of prostate cancer progression. We mapped the global DNA methylation patterns in prostate tissues (n=17) and cells (n=2) from fifty nanograms of genomic DNA using Methylplex-Next Generation Sequencing (M-NGS). A Hidden Markov Model (HMM)-based algorithm previously used for Chip-Seq data analysis(http://www.sph.umich.edu/csg/qin/HPeak) was used to locate peaks from mapped reads obtained in each sequencing run. The total methylation events in intergenic/intronic regions between benign adjacent and cancer tissues were comparable. While approximately 20% of all CpG islands (CGIs) (68,508) were methylated in tissues, promoter CGI methylation gradually increased from ~12.6% in benign samples to 19.3% and 21.8% in localized and metastatic cancer tissues. We found distinct patterns in promoter methylation around transcription start sites, where methylation occurred directly on the CGIs, flanking regions and on CGI sparse promoters. Among the 6,691 methylated promoters in prostate tissues, 2481 differentially methylated regions (DMRs) are cancer specific and several previously studied targets were among them. A novel cancer specific DMR in WFDC2 promoter showed 77% methylation in cancer (17/22), 100% methylation in transformed prostate cell lines (6/6), none in the benign tissues (0/10) and normal PrEC cells. Integration of LNCaP DNA methylation and H3K4me3 data suggested a role for DNA methylation in alternate transcription start site utilization. While methylated promoters containing CGIs had mutually exclusive H3K4me3 modification, the histone mark was absent in CGI sparse promoters. Finally, we observed difference in methylation of LINE-1 elements between transcription factor ERG positive and negative cancers. The comprehensive methylome map presented here will further our understanding of epigenetic regulation of the prostate cancer genome. We mapped the global DNA methylation patterns in prostate tissues (n=17; data not available in GEO - being deposited in dbGaP for controlled access) and cells (n=2) from fifty nanograms of genomic DNA using Methylplex-Next Generation Sequencing (M-NGS). For replicate analysis in cell lines, a total of 4 runs were completed for PrEC prostate normal cell line, and 5 runs were completed for LNCaP prostate cancer cell line. For tissue samples, 2 benign prostate samples were ran twice on illumina next generation sequencing platform to access overall repeatability of M-NGS.
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Project description:Cancer of the prostate is influenced both by genetic predisposition and environmental factors. The identification of genes capable of modulating cancer development has the potential to unravel disease heterogeneity and aid diagnostic and prevention strategies through improved understanding of gene-environment interactions. To this end, mouse models have been developed to isolate the influences of individual genetic lesions in the context of consistent genotypes and environmental exposures. However, the extent of normal prostatic phenotypic variability dictated by a genetic background potentially capable of influencing the process of carcinogenesis has not been established. In this study we used microarray analysis to quantitate transcript abundance levels in the prostates of five commonly studied inbred mouse strains. We applied a multiclass response t-test to identify genes whose expression in each strain significantly differed from the other four strains. Approximately 13% (932 genes) exhibited significant differential expression (range 1.3 to 190-fold) in one strain relative to other strains (FDRM-bM-^IM-$10%). The pattern of variability in transcript levels did not result from variations unique to a particular strain, but rather represented genetic variability across all five strains assessed. Expression differences were confirmed by qRT-PCR, or immunohistochemistry for several genes previously shown to influence cancer progression such as Psca, Mmp7, and Clusterin. Analyses of human prostate transcripts orthologous to variable murine prostate genes identified differences in gene expression in benign epithelium that correlated with the differentiation state of adjacent tumors. For example, the expression of apolipoprotein D, a gene known to enhance resistance to cell stress in Drosophila, was expressed at significantly greater levels in benign epithelium associated with high-grade versus low-grade cancers. These data support the concept that the cellular, tissue, and organismal context contribute to oncogenesis and suggest that a predisposition to a sequence of events leading to pathology may be determined prior to cancer initiation. Prostates from twelve mice from each of five strains of Mus musculus: C57BL/6J, 129X1/SvJ, BALB/cAnCrl, FVB/NJ and DBA/2NCrl, were resected and individual lobes were dissected: DP: dorsal prostate; LP: lateral prostate; VP: ventral prostate; AP: anterior prostate. Each experimental sample represents a pool of equal amounts of RNA for each prostatic lobe from 3 animals. Four independent experimental samples were created per strain: 12 mice divided into 4 pools of 3 mice each for a total of 4 microarray experiments per strain. Amplified RNA from each experimental sample was hybridized against a reference sample (created by combining equal amounts of RNA from all the samples from all strains) onto custom mouse prostate cDNA microarrays using alternate dye-labeling to account for dye-specific effects.
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