Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA147105 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Screening of differentially expressed genes between benign and prostate tumors with respect to different prostate cancer gleason score 6 and 8 Keywords: disease subtype analysis
2010-03-31 | GSE15484 | GEO
Project description:To study feasibility of gene expression profiling from FFPE tissues using NuGen amplified mRNA hybridized on Affymetrix GeneChip Human Gene 1.0 ST arrays, we designed a pilot study utilizing samples from prostate cancer cohort. We selected samples from large-scale epidemiologic studies and clinical trials representative of a wide variety of fixation times, block ages and block storage conditions. We profiled seven paired tumor and adjacent normal prostate tissue samples from three patients with Gleason score 8, one with Gleason score 7 and three with Gleason 6 disease. 11 samples had two or three technical replicates.
2014-07-01 | E-GEOD-54808 | biostudies-arrayexpress
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.
2009-03-27 | GSE15298 | GEO
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:The transcriptomic heterogeneity of the prostate cancer was tested by profiling histologically distinct but equally graded (Gleason score 4+5=9/10) cancer nodules from a surgically removed prostate cancer. We found that not only that the genes were differently regulated in the two nodules but also that expression fluctuations were differently controlled and the gene networks differently remodeled.
2021-09-12 | GSE183889 | GEO
Project description:Purpose: Clinicopathologic features and biochemical recurrence are sensitive, but not specific, predictors of metastatic disease and lethal prostate cancer. We hypothesize that a genomic expression signature detected in the primary tumor represents true biological potential of aggressive disease and provides improved prediction of early prostate cancer metastasis. Methods: A nested case-control design was used to select 639 patients from the Mayo Clinic tumor registry that underwent radical prostatectomy between 1987 and 2001. A genomic classifier (GC) was developed by modeling differential RNA expression using 1.4 million feature high-density expression arrays of men enriched for rising PSA after prostatectomy, including 213 that experienced early clinical metastasis after biochemical recurrence. A training set was used to develop a random forest classifier of 22 markers to predict for cases - men with early clinical metastasis after rising PSA. Performance of GC was compared to prognostic factors such as Gleason score and previous gene expression signatures in a withheld validation set. Results: Expression profiles were generated from 545 unique patient samples, with median follow-up of 16.9 years. GC achieved an area under the receiver operating characteristic curve of 0.75 (0.67 - 0.83) in validation, outperforming clinical variables and gene signatures. GC was the only significant prognostic factor in multivariable analyses. Within Gleason score groups, cases with high GC scores experienced earlier death from prostate cancer and reduced overall survival. The markers in the classifier were found to be associated with a number of key biological processes in prostate cancer metastatic disease progression. Conclusion: A genomic classifier was developed and validated in a large patient cohort enriched with prostate cancer metastasis patients and a rising PSA that went on to experience metastatic disease. This early metastasis prediction model based on genomic expression in the primary tumor may be useful for identification of aggressive prostate cancer. 545 formalin-fixed paraffin-embedded (FFPE) tissue samples from primary prostate cancer obtained from Radical Prostatectomy.
2013-07-01 | E-GEOD-46691 | 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:Prostate tumors are among the most heterogeneous of cancers, both histologically and clinically. Microarray expression analysis was used to determine whether global biological differences underlie common pathological features of prostate cancer and to identify genes that might anticipate the clinical behavior of this disease. While no expression correlates of age, serum prostate specific antigen (PSA), and measures of local invasion were found, a set of genes was identified that strongly correlated with the state of tumor differentiation as measured by Gleason score. Moreover, a model using gene expression data alone accurately predicted patient outcome following prostatectomy. These results support the notion that the clinical behavior of prostate cancer is linked to underlying gene expression differences that are detectable at the time of diagnosis. golub-00142 Assay Type: Gene Expression Provider: Affymetrix Array Designs: HG_U95Av2 Organism: Homo sapiens (ncbitax)
2015-05-15 | E-GEOD-68907 | biostudies-arrayexpress
Project description:Prostate tumors are among the most heterogeneous of cancers, both histologically and clinically. Microarray expression analysis was used to determine whether global biological differences underlie common pathological features of prostate cancer and to identify genes that might anticipate the clinical behavior of this disease. While no expression correlates of age, serum prostate specific antigen (PSA), and measures of local invasion were found, a set of genes was identified that strongly correlated with the state of tumor differentiation as measured by Gleason score. Moreover, a model using gene expression data alone accurately predicted patient outcome following prostatectomy. These results support the notion that the clinical behavior of prostate cancer is linked to underlying gene expression differences that are detectable at the time of diagnosis.
2015-05-15 | GSE68907 | GEO