Discovery of novel hypermethylated gene loci in prostate cancer using genome wide coverage CpG island microarrays
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE15298 | GEO | 2009/03/27
SECONDARY ACCESSION(S): PRJNA116593
REPOSITORIES: GEO
Similar Datasets
Project description:In order to identify methylation changes in prostate cancer, we performed a genome-wide analysis of DNA methylation using Agilent human CpG island arrays. We then chose specific genes to validate methylation both in the same cases as were hybridized to the array (using quantitative EpiTYPER analysis) and in an independent series of prostate cancer samples (using MethyLight quantitative methylation specific PCR). We specifically chose low grade (Gleason score 6 cases) and high grade (Gleason score 8 cases) to discover methylated genes/loci that may be involved in the progression to a higher grade of prostate cancer. We collected 20 specimens consisting of 10 Gleason 6 and 10 Gleason 8 prostate cancers, and compared these to a reference lymphocyte pool (6 age matched, healthy men) to determine cancer associated methylation changes as well as disease progression associated methylation changes. We performed the differential methylation hybridization procedure as described by Yan et al. (Methods, 2002) on each case to enrich for methylated DNA. Each specimen in the reference pool underwent the same enrichment with amplicons being pooled at the end of the procedure. Each prostate cancer case was subsequently co-hybridized to the microarray with the reference pool.
2009-03-26 | E-GEOD-15298 | biostudies-arrayexpress
Project description: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). MBD-isolated Genome Sequencing (MiGS) for groups of benign prostate (from cystoprostatectomy), low grade prostate cancer (from radical prostatectomy with Gleason Score 6), and high grade prostate cancer (from radical prostatectomy with Gleason Scores 8 to 10) in both European Americans and African Americans
2015-11-01 | E-GEOD-66505 | biostudies-arrayexpress
Project description: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).
2015-11-01 | GSE66505 | GEO
Project description:PSA screening has led to enormous overtreatment of prostate cancer, due to the inability to distinguish potentially lethal disease at diagnosis. We reasoned that by identifying an mRNA signature of Gleason grade, the best predictor of prognosis, we could improve prediction of lethal disease among men with moderate Gleason 7 tumors, the most common grade, and most indeterminate in terms of prognosis. Using the complementary DNA (cDNA)–mediated annealing, selection, extension, and ligation assay, we measured the mRNA expression of 6,100 genes in prostate tumor tissue in the Swedish Watchful Waiting cohort (N=358) and Physicians’ Health Study (PHS; N=109). We developed an mRNA signature of Gleason comparing individuals with Gleason ≤6 to those with Gleason ≥8 tumors, and applied the model among Gleason 7 cases to discriminate lethal cases. We built a157-gene signature using the Swedish data that predicted Gleason with low misclassification (AUC=0.91); when this signature was tested in the PHS validation set, the discriminatory ability remained high (AUC=0.94). In men with Gleason 7 tumors, who were excluded from the model building, the signature significantly improved the prediction of lethal disease beyond knowing whether the Gleason score was 4+3 or 3+4 (p=0.006). Our expression signature and the genes identified may improve our understanding of the de-differentiation process of prostate tumors. Additionally, the signature may have clinical applications among men with Gleason 7, by further estimating their risk of lethal prostate cancer and thereby guiding therapy decisions to improve outcomes and reduce overtreatment.
2012-05-01 | GSE37663 | GEO
Project description:PSA screening has led to enormous overtreatment of prostate cancer, due to the inability to distinguish potentially lethal disease at diagnosis. We reasoned that by identifying an mRNA signature of Gleason grade, the best predictor of prognosis, we could improve prediction of lethal disease among men with moderate Gleason 7 tumors, the most common grade, and most indeterminate in terms of prognosis. Using the complementary DNA (cDNA)M-bM-^@M-^Smediated annealing, selection, extension, and ligation assay, we measured the mRNA expression of 6,100 genes in prostate tumor tissue in the Swedish Watchful Waiting cohort (N=358) and PhysiciansM-bM-^@M-^Y Health Study (PHS; N=109). We developed an mRNA signature of Gleason comparing individuals with Gleason M-bM-^IM-$6 to those with Gleason M-bM-^IM-%8 tumors, and applied the model among Gleason 7 cases to discriminate lethal cases. We built a157-gene signature using the Swedish data that predicted Gleason with low misclassification (AUC=0.91); when this signature was tested in the PHS validation set, the discriminatory ability remained high (AUC=0.94). In men with Gleason 7 tumors, who were excluded from the model building, the signature significantly improved the prediction of lethal disease beyond knowing whether the Gleason score was 4+3 or 3+4 (p=0.006). Our expression signature and the genes identified may improve our understanding of the de-differentiation process of prostate tumors. Additionally, the signature may have clinical applications among men with Gleason 7, by further estimating their risk of lethal prostate cancer and thereby guiding therapy decisions to improve outcomes and reduce overtreatment. 198 cases from the population-based Swedish-Watchful Waiting cohort. The cohort consists of men with localized prostate cancer (clinical stage T1-T2, Mx, N0); expression profiles from tumors with Gleason M-bM-^IM-%8 (N=89) were compared to those from tumors with Gleason M-bM-^IM-$6 (N=109)
2012-04-30 | E-GEOD-37663 | biostudies-arrayexpress
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).
2011-11-10 | E-GEOD-33557 | biostudies-arrayexpress
Project description:Although many genes have been proposed to be involved in prostate carcinogenesis, no single gene or gene profile has shown to have prognostic value. The main challenge for clinical management is to distinguish slowly growing tumors from those that will relapse. In this study, we compared expression profiles of 18 prostate samples (7 with Gleason 6, 8 with Gleason 7 and 3 with Gleason score equal or higher than 8) and 5 non-neoplastic prostate samples, using the GeneChip® Human Exon Array 1.0 ST of Affymetrix. Microarray analysis revealed 99 genes showing statistically significant differences among tumors with Gleason score 6, 7 and 8. In addition, mRNA expression of 29 selected genes was analyzed by qRT-PCR with microfluidic cards in an extended series of 30 prostate tumors. From these, 29 were selected to be validated and the differential expression of 18 of them (62%) was independently confirmed by quantitative real-time RT-PCR (14 upregulated and 4 downregulated in higher Gleason scores) in the extended series. This list was further narrowed down to 12 genes that were differentially expressed in tumors with Gleason score of 6-7 vs 8. Finally, the protein levels of two genes from the 12-gene signature (SEC14L1 and TCEB1) were additionally validated by immunohistochemistry. Strong protein levels of both genes were correlated with Gleason score, stage, and PSA progression. We used microarrays to detail the global programme of gene expression underlying cellularisation and identified distinct classes of up-regulated genes during this process. 23 Samples were analyzed.
2012-10-25 | E-GEOD-30521 | biostudies-arrayexpress
Project description:Although many genes have been proposed to be involved in prostate carcinogenesis, no single gene or gene profile has shown to have prognostic value. The main challenge for clinical management is to distinguish slowly growing tumors from those that will relapse. In this study, we compared expression profiles of 18 prostate samples (7 with Gleason 6, 8 with Gleason 7 and 3 with Gleason score equal or higher than 8) and 5 non-neoplastic prostate samples, using the GeneChip® Human Exon Array 1.0 ST of Affymetrix. Microarray analysis revealed 99 genes showing statistically significant differences among tumors with Gleason score 6, 7 and 8. In addition, mRNA expression of 29 selected genes was analyzed by qRT-PCR with microfluidic cards in an extended series of 30 prostate tumors. From these, 29 were selected to be validated and the differential expression of 18 of them (62%) was independently confirmed by quantitative real-time RT-PCR (14 upregulated and 4 downregulated in higher Gleason scores) in the extended series. This list was further narrowed down to 12 genes that were differentially expressed in tumors with Gleason score of 6-7 vs 8. Finally, the protein levels of two genes from the 12-gene signature (SEC14L1 and TCEB1) were additionally validated by immunohistochemistry. Strong protein levels of both genes were correlated with Gleason score, stage, and PSA progression. We used microarrays to detail the global programme of gene expression underlying cellularisation and identified distinct classes of up-regulated genes during this process.
2012-10-25 | GSE30521 | GEO
Project description:To identify biomarkers predictive of biochemical recurrence, we isolated the RNA from 70 formalin-fixed paraffin-embedded (FFPE) radical prostatectomy specimens with known long term outcome to perform DASL expression profiling with a custom-designed panel of 522 prostate cancer relevant genes that we designed. We identified a panel of ten protein-coding genes and two miRNA genes that could be used to separate patients with and without biochemical recurrence (p < 0.001), as well as for the subset of 42 Gleason score 7 patients (p < 0.001). We performed an independent validation analysis on 40 samples and found that the biomarker panel was also significant at prediction of recurrence for all cases (p = 0.013) and for a subset of 19 Gleason score 7 cases (p = 0.010), both of which were adjusted for relevant clinical information including T-stage, PSA and Gleason score. Importantly, these biomarkers could significantly predict clinical recurrence for Gleason 7 patients. These biomarkers may increase the accuracy of prognostication following radical prostatectomy using formalin-fixed specimens. Total RNA prepared from FFPE cores from prostatectomy samples of 70 patients were used for the training phase (29 with biochemical recurrence and 41 controls). All samples were analyzed by both custom Prostate DASL of 522 genes and by Illumina miRNA microarray. Subsequently in the validation phase, samples from 40 patients were used on the same platforms (13 with biochemical recurrence and 27 controls). For the training set, 45 cases were from Sunnybrook Health Science Center (Toronto, ON), and 25 patients from Emory University. For the validation set, all samples were from Emory University. Relevant clinical metadata included are PSA, T-stage, and Gleason Score.
2011-06-01 | E-GEOD-26245 | biostudies-arrayexpress