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DNA Methylation Sequencing of Prostate Tumors Reveals Possible Molecular Mechanisms for Cancer Aggressiveness

ABSTRACT: A major challenge in the clinical management of prostate cancer is the inability to definitively diagnose indolent versus aggressive cases. Contributing to this challenge is a lack of basic science understanding of the molecular basis behind aggressiveness subtypes in prostate cancer. DNA methylation is the epigenetic addition of a methyl group to the DNA base cytosine and has been found to regulate cell proliferation and environmental adaptation. We hypothesized that DNA methylation changes are a mechanism by which an aggressive cancer attains phenotypes that distinguish it from indolent cases via disruption of regulatory networks. This hypothesis was tested by comparing DNA methylation between benign prostate and both low grade (Gleason score 6) and high grade (Gleason score 8 to 10) groups. Methylome-wide next generation sequencing was performed on formalin-fixed paraffin embedded (FFPE) samples from radical prostatectomy cases using MBD-isolated genome sequencing (MiGS). This technique uses a DNA methylation binding protein (MBD) to purify fragments from a genomic library with a high level of CpG DNA methylation. These fragments were then sequenced via next generation sequencing, the reads were aligned to a reference genome, and then the reads were counted within non-overlapping 50bp windows genome wide. Statistical analysis was then performed on these windowed counts to produce differentially methylated regions (DMRs).

ORGANISM(S): Homo sapiens

PROVIDER: GSE66505 | GEO | 2015/11/01

SECONDARY ACCESSION(S): PRJNA277194

REPOSITORIES: GEO

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Project description:Detection of DNA hypermethylation has emerged as a novel molecular biomarker for the evaluation of prostate cancer diagnosis and prognosis, but the use of single gene hypermethylation could produce unspecific results. Defining the specific gene hypermethylation profile for prostate cancer could provide groups of genes that specifically discriminate the patients with indolent and aggressive tumors. To compare the methylation profile of normal and malignant prostate we performed Genome-wide methylation analysis on 83 tumor samples, that included all clinical stages of the disease, 10 normal prostate samples and LNCaP, DU145 and PC3 prostate cancer cell lines using the GoldenGate Methylation Cancer Panel I (Illumina, Inc.) that interrogate for 1505 CpGs. We found 41 genes significantly hypermethylated in more than 20% of the tumors analyzed (p<0.01). Of these we identified GSTM2 and PENK as novel hypermethylated genes in prostate cancer that were simultaneously methylated in 40.9% of the tumors analyzed. We also identified panels of genes more frequently methylated in tumor samples with clinico-pathological indicators of poor prognosis: high Gleason score, elevated Ki-67 or advanced disease. Of these, we found that simultaneous hypermethylation of CFTR and HTR1B is common in patients with high Gleason score and high ki-67 levels and might signal the population at higher risk of therapeutic failure. DNA hypermethylation profile was associated with cancer-specific mortality (log-rank, p=0.007) and biochemical recurrence-free survival (log-rank, p=0.0008). In conclusion, our data strongly indicate that epigenetic silencing of GSTM2 and PENK is a common event in prostate cancer that could be used as a molecular marker for prostate cancer diagnosis. In addition, simultaneous HTR1B and CFTR hypermethylation could help discriminate aggressive from indolent prostate tumors.A DNA hypermethylation profile associated with cancer-specific mortality and biochemical recurrence in patients receiving radical prostatectomy is presented. GST2 and PENK are new hipermethylated genes identified. Simultaneous hypermethylation of CFTR and HTR1B could help discriminate aggressive disease.

Project description:A comprehensive expression analysis of Wnt signaling genes was performed in a panel of prostate cancer cell lines and tissue specimens using TaqMan low density arrays. The effect of DNA methylation on gene expression was investigated using DNMT inhibitor 5-Aza-CdR. Tissue specimens from a range of disease states were used to represent the stepwise progression of prostate cancer, including benign prostatic hyperplasia (BPH), histologically benign epithelium adjacent to tumor (HB), pre-invasive high-grade prostatic intraepithelial neoplasia (HGPIN) and primary localized tumors categorized into low- and high-grade disease. Fifteen Wnt signaling related genes were idenified with significantly altered expression in prostate cancer; the majority of which were upregulated in tumors. Notably, histologically benign tissue from men with prostate cancer appeared more similar to tumour (r=0.76) than to BPH (r=0.57) (P<0.001). Overall, the expression profile was highly similar between tumors of high (M-bM-^IM-%7) and low (M-bM-^IM-$6) Gleason scores. Pharmacological demethylation of PC-3 cells reactivated 38 genes (M-bM-^IM-%2-fold); 40% of which inhibit Wnt signaling. qPCR gene expression profiling using TLDA Human Wnt Gene set v1.0 microfluidic card (Applied Biosystems, Foster City, CA).The TLDA consisted of 4 identical 96-gene sets preconfigured in a 384-well format. Three different malignant cell lines were profiled LNCaP, 22Rv1 and PC3 (+/- 5-Aza-2M-bM-^@M-^YDeoxycytidine). One benign cell line was included for comparative puposes: PWR1E. Patient samples were obtained from FFPE tissue sections from men who underwent radical prostatectomy or transrectal resection of the prostate. To overcome the limited amount of RNA obtained from FFPE tissues, RNA samples were pooled. Five different pools were generated: high grade prostate cancer (Gleason score M-bM-^IM-%7), low grade prostate cancer (Gleason score M-bM-^IM-$6), HGPIN, HB and BPH. Each pool consisted of DNase-treated total RNA (100ng), isolated from microdissected tissue from 4 individual cases, selected on the basis of similar histological and clinical features and previous epigenetic characterization in our laboratory. Two Biological replicates for each pool were prepared. The high capacity cDNA Archive Kit (Applied Biosystems) was used to reverse transcribe pooled RNA (400ng). TaqManM-BM-. reactions were performed in duplicate on a 7900HT Sequence Detection System. RQ data from TLDAs were analyzed using Real Time StatMinerM-BM-. v3.1 (Integromics, Granada, Spain).

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DNA Methylation Sequencing of Prostate Tumors Reveals Possible Molecular Mechanisms for Cancer Aggressiveness

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