Deep sequencing reveals distinct patterns of DNA methylation in prostate cancer

Michigan Center for Translational Pathology, University of Michigan Medical School, Ann Arbor, MI 48109, USA.
Genome Research (Impact Factor: 14.63). 07/2011; 21(7):1028-41. DOI: 10.1101/gr.119347.110
Source: PubMed


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.

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Available from: John R Prensner, Jul 20, 2014
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    • "Recently, a gene-expression-based assay using biopsy tissues has provided a genomically derived aggressiveness measure that clinicians can use in conjunction with clinicopathologic risk factors for supporting clinical decision-making (Klein et al., 2014). Still, knowledge about the molecular and biological differences between indolent and aggressive prostate cancer can be increased further, as most genome-wide studies of copy-number variation, somatic mutations, DNA methylation (Kim et al., 2011; Yu et al., 2013), and gene expression have focused on tumor versus normal comparisons rather than stratifying by aggressiveness subtypes. We sought to uncover molecular mechanisms behind aggressive prostate cancer by comparing DNA methylation profiles between benign prostate, indolent prostate cancer, and aggressive prostate cancer. "
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    ABSTRACT: A critical need in understanding the biology of prostate cancer is characterizing the molecular differences between indolent and aggressive cases. Because DNA methylation can capture the regulatory state of tumors, we analyzed differential methylation patterns genome-wide among benign prostatic tissue and low-grade and high-grade prostate cancer and found extensive, focal hypermethylation regions unique to high-grade disease. These hypermethylation regions occurred not only in the promoters of genes but also in gene bodies and at intergenic regions that are enriched for DNA-protein binding sites. Integration with existing RNA-sequencing (RNA-seq) and survival data revealed regions where DNA methylation correlates with reduced gene expression associated with poor outcome. Regions specific to aggressive disease are proximal to genes with distinct functions from regions shared by indolent and aggressive disease. Our compendium of methylation changes reveals crucial molecular distinctions between indolent and aggressive prostate cancer.
    Full-text · Article · Nov 2015 · Cell Reports
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    • "Furthermore, the false-negative rate of the 6-and 12-core biopsy techniques performed ex vivo on prostates removed due to biopsy-proven cancer was 425% (Svetec et al, 1998; Fink et al, 2001; Serefoglu et al, 2013). Thus, underdiagnosis of PCa is not uncommon and, therefore, standard hematoxylin and eosin (H&E) staining of core biopsies could be assisted by monitoring differentially expressed genes (Hessels et al, 2004; Bhavsar et al, 2013) and patterns of DNA methylation (Kim et al, 2011a; Day and Bianco–Miotto, 2013) as an initial biopsy strategy. Here, we analysed critically the potential usefulness of selected biomarkers for supporting conventional histological tests for PCa diagnosis. "
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    ABSTRACT: Background: We analysed critically the potential usefulness of RNA- and DNA-based biomarkers in supporting conventional histological diagnostic tests for prostate carcinoma (PCa) detection. Methods: Microarray profiling of gene expression and DNA methylation was performed on 16 benign prostatic hyperplasia (BPH) and 32 cancerous and non-cancerous prostate samples extracted by radical prostatectomy. The predictive value of the selected biomarkers was validated by qPCR-based methods using tissue samples extracted from the 58 prostates and, separately, using 227 prostate core biopsies. Results: HOXC6, AMACR and PCA3 expression showed the best discrimination between PCa and BPH. All three genes were previously reported as the most promising mRNA-based markers for distinguishing cancerous lesions from benign prostate lesions; however, none were sufficiently sensitive and specific to meet the criteria for a PCa diagnostic biomarker. By contrast, DNA methylation levels of the APC, TACC2, RARB, DGKZ and HES5 promoter regions achieved high discriminating sensitivity and specificity, with area under the curve (AUCs) reaching 0.95-1.0. Only a small overlap was detected between the DNA methylation levels of PCa-positive and PCa-negative needle biopsies, with AUCs ranging between 0.854 and 0.899. Conclusions: DNA methylation-based biomarkers reflect the prostate malignancy and might be useful in supporting clinical decisions for suspected PCa following an initial negative prostate biopsy.
    Full-text · Article · Jun 2014 · British Journal of Cancer
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    • "Next generation sequencing can yield millions of single molecule reads and has been used to determine DNA methylation (Taylor et al., 2007; Bibikova and Fan, 2010; Laird, 2010; Feng et al., 2011; Kim et al., 2011; Komori et al., 2011; Ku et al., 2011; Nejman et al., 2014). Supplemented with DNA barcoding technology, which incorporates a unique index sequence into each PCR segment, this approach can provide a rapid way to simultaneously determine DNA methylation at the single-molecule level in large numbers of samples. "
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    ABSTRACT: Invasive cervix cancer (ICC) is the third most common malignant tumor in women and human papillomavirus 16 (HPV16) causes more than 50% of ICC. DNA methylation is a covalent modification predominantly occurring at CpG dinucleotides and increased methylation across the HPV16 genome is strongly associated with ICC development. Next generation (Next Gen) sequencing has been proposed as a novel approach to determine DNA methylation. However, utilization of this method to survey CpG methylation in the HPV16 genome is not well described. Moreover, it provides additional information on methylation "haplotypes." In the current study, we chose 12 random samples, amplified multiple segments in the HPV16 bisulfite treated genome with specific barcodes, inspected the methylation ratio at 31 CpG sites for all samples using Illumina sequencing, and compared the results with quantitative pyrosequencing. Most of the CpG sites were highly consistent between the two approaches (overall correlation, r = 0.92), thus verifying that Next Gen sequencing is an accurate and convenient method to survey HPV16 methylation and thus can be used in clinical samples for risk assessment. Moreover, the CpG methylation patterns (methylation haplotypes) in single molecules identified an excess of complete-and non-methylated molecules and a substantial amount of partial-methylated ones, thus indicating a complex dynamic for the mechanisms of HPV16 CpG methylation. In summary, the advantages of Next Gen sequencing compared to pyrosequencing for HPV genome methylation analyses include higher throughput, increased resolution, and improved efficiency of time and resources.
    Full-text · Article · Jun 2014 · Frontiers in Genetics
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