MPC_ Deep Sequencing Reveals Distinct Pattern of DNA Methylation in Prostate Cancer
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ABSTRACT:
PROVIDER: PRJNA188512 | ENA |
REPOSITORIES: ENA
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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 selected prostate tissues and cell lines using Methylplex-Next Generation Sequencing (M-NGS). Hidden Markov Model based next generation sequence analysis identified ~68,000 methylated regions per sample. While global CpG Island (CGI) methylation was not differential between benign adjacent and cancer samples, overall promoter CGI methylation increased from ~12.6% in benign samples to 19.3% and 21.8% in localized and metastatic cancer tissues, respectively. We found distinct patterns of promoter methylation around transcription start sites, where methylation occurred not only on the CGIs, but also on flanking regions and CGI sparse promoters. Among the 6,691 methylated promoters in prostate tissues, 2481 differentially methylated regions (DMRs) are cancer specific, including numerous novel DMRs. A novel cancer specific DMR in WFDC2 promoter showed heavy methylation in cancer (17/22 tissues, 6/6 cell lines), but not in the benign tissues (0/10) and normal PrEC cells. Integration of LNCaP DNA methylation and H3K4me3 data suggested an epigenetic mechanism for alternate transcription start site utilization and these modifications segregated into distinct regions when present on the same promoter. Finally, we observed differences in repeat element methylation, particularly LINE-1, between ERG gene fusion positive and negative cancers. This comprehensive methylome map will further our understanding of epigenetic regulation in prostate cancer progression. This SuperSeries is composed of the SubSeries listed below.
2011-05-03 | GSE27619 | GEO
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 select prostate tissues and cell lines using MethylPlex-next-generation sequencing (M-NGS). Hidden Markov model-based next-generation sequence analysis identified ?68,000 methylated regions per sample. While global CpG island (CGI) methylation was not differential between benign adjacent and cancer samples, overall promoter CGI methylation significantly increased from ~12.6% in benign samples to 19.3% and 21.8% in localized and metastatic cancer tissues, respectively (P-value < 2 × 10(-16)). We found distinct patterns of promoter methylation around transcription start sites, where methylation occurred not only on the CGIs, but also on flanking regions and CGI sparse promoters. Among the 6691 methylated promoters in prostate tissues, 2481 differentially methylated regions (DMRs) are cancer-specific, including numerous novel DMRs. A novel cancer-specific DMR in the WFDC2 promoter showed frequent methylation in cancer (17/22 tissues, 6/6 cell lines), but not in the benign tissues (0/10) and normal PrEC cells. Integration of LNCaP DNA methylation and H3K4me3 data suggested an epigenetic mechanism for alternate transcription start site utilization, and these modifications segregated into distinct regions when present on the same promoter. Finally, we observed differences in repeat element methylation, particularly LINE-1, between ERG gene fusion-positive and -negative cancers, and we confirmed this observation using pyrosequencing on a tissue panel. This comprehensive methylome map will further our understanding of epigenetic regulation in prostate cancer progression.
| S-EPMC3129246 | biostudies-literature
Project description:Prostate adenocarcinoma and matched adjacent normal samples were profiled by deep transcriptional sequencing to analyze transcription-induced chimeras and gene fusions. Reference samples from the MAQC and brain and universal reference libraries were also sequenced. Two-condition experiment plus reference samples: Prostate adenocarcinoma versus matched normal from three separate patients, plus brain and universal reference samples from the MAQC project.
2010-09-23 | E-GEOD-24283 | biostudies-arrayexpress
Project description:Prostate adenocarcinoma and matched adjacent normal samples were profiled by deep transcriptional sequencing to analyze transcription-induced chimeras and gene fusions. Reference samples from the MAQC and brain and universal reference libraries were also sequenced.
2010-09-23 | GSE24283 | GEO
Project description:This SuperSeries is composed of the following subset Series: GSE24282: CGH microarray analysis of human prostate adenocarcinoma and normal samples GSE24283: Deep transcriptional sequencing analysis of human prostate adenocarcinoma and reference samples Refer to individual Series
2010-09-22 | E-GEOD-24284 | biostudies-arrayexpress
Project description:Distinct mesenchymal cell states mediate prostate cancer progression
| PRJNA1022035 | ENA
Project description:MPC_ Deep Sequencing Reveals Distinct Pattern of DNA Methylation in Prostate Cancer
| PRJNA188782 | ENA
Project description:Deep mutagenesis reveals the distinct mutational landscape of ADan and ABri amyloid nucleation
| PRJNA1023889 | ENA
Project description:Background: Despite the significant global loss of DNA hydroxymethylation marks in prostate cancer tissues, the locus-specific role of hydroxymethylation in prostate tumorigenesis is unknown. We characterized hydroxymethylation and methylation marks by performing whole-genome next generation sequencing in representative normal and prostate cancer-derived cell lines in order to determine functional pathways and key genes regulated by these epigenomic modifications in cancer. Results: Our cell line model shows disruption of hydroxymethylation distribution in cancer, with global loss and highly specific gain in promoter and CpG island regions. Significantly, we observed locus-specific retention of hydroxymethylation marks in specific intronic and intergenic regions which may play a novel role in the regulation of gene expression in critical functional pathways, such as BARD1 signaling and steroid hormone receptor signaling in cancer. We confirm a modest correlation of hydroxymethylation with expression in intragenic regions in prostate cancer, while identifying an original role for intergenic hydroxymethylation in differentially expressed regulatory pathways in cancer. We also demonstrate a successful strategy for the identification and validation of key candidate genes from differentially regulated biological pathways in prostate cancer. Conclusion: Our results indicate a distinct function for aberrant hydroxymethylation within each genomic feature in cancer, suggesting a specific and complex role for the deregulation of hydroxymethylation in tumorigenesis, similar to methylation. Subsequently, our characterization of key cellular pathways exhibiting dynamic enrichment patterns for methylation and hydroxymethylation marks may allow us to identify differentially epigenetically modified target genes implicated in prostate cancer tumorigenesis. Methylation profiles of representative normal prostate cell line RWPE-1 and prostate adenocarcinoma cell line 22Rv1 were generated by MBD capture followed by high-throughput sequencing on the HiSeq 2500 (Illumina), in triplicate. Hydroxymethylation profiles of RWPE-1 and 22Rv1 were generated by hMeSeal followed by high-throughput sequencing on the HiSeq 2500 (one replicate each). Additional hydroxymethylation profiling for RWPE-1 was generated by hMeDIP followed by high-throughput sequencing on the HiSeq 2000 (Illumina).
2016-03-15 | E-GEOD-74464 | biostudies-arrayexpress
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.
2013-08-01 | E-GEOD-45000 | biostudies-arrayexpress