Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA162649 | ENA |
REPOSITORIES: ENA
Similar Datasets
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:Twenty-nine radical prostatectomy samples were laser capture microdissected (LCM) to obtain the most common Gleason patterns (patterns 3, 4, and 5) and matched benign adjacent luminal prostate epithelial cells. We performed cDNA microarrays on matched cancer and adjacent normal samples and identified an 86-gene model capable of distinguishing low Gleason grade (pattern 3) from high Gleason grade (pattern 4 and 5) cancers, which contributes a set of potential targets for modulating the development and progression of the lethal prostate cancer phenotype. Keywords: disease state analysis
2006-07-14 | GSE5132 | GEO
Project description:Molecular Correlate to Gleason Grade in Prostate Adenocarcinoma
| PRJNA96639 | ENA
Project description:Obese men are at higher risk of developing advanced prostate cancer and have higher rates of cancer-specific mortality. However, the biological mechanisms explaining these associations are unknown. Using gene expression data, we aimed to identify molecular alterations in prostate cancer tissue associated with obesity. Gene Set Enrichment Analysis identified fifteen gene sets up-regulated in the tumor tissue of obese prostate cancer patients (N=84) compared to healthy weight patients (N=192), five of which were related to chromatin remodeling. These gene sets were not identified in an analysis of adjacent normal tissue. Patients with tumors with high expression of chromatin remodeling genes had worse clinical characteristics (Gleason grade >7, 41% versus 17%, p-trend = 3.21 x 10-4) and poorer prostate cancer-specific survival independent of Gleason grade (lethal outcome, OR = 5.01, 95% CI = 2.31 to 11.38). Mediation analysis further supported a role for chromatin remodeling in the obesity-lethal prostate cancer relationship.
2017-03-01 | GSE79021 | GEO
Project description:Pairwise Gene Expression Comparison between Gleason 3 and Gleason 4 Prostate Cancer
| PRJNA229382 | ENA
Project description:Gleason grading is an important prognostic indicator for prostate adenocarcinoma and is crucial for patient treatment decisions. However, intermediate-risk patients diagnosed in Gleason Grade Groups (GG) 2 and GG3 can harbour either aggressive or non-aggressive disease, resulting in under- or over-treatment of a significant number of patients. Here, we performed proteomic, differential expression, machine learning, and survival analyses for 1,348 matched tumour and benign samples from 278 patients. Three proteins (F5, TMEM126B and EARS2) were identified as candidate biomarkers in patients with biochemical recurrence. Multivariate Cox regression yielded 18 proteins, from which a risk score was constructed to dichotomise prostate cancer patients into low- and high-risk groups. This 18-protein signature is prognostic for the risk of biochemical recurrence and completely independent of the intermediate GG. Our results suggest that markers generated by computational proteomic profiling have the potential for clinical applications including integration into prostate cancer management.
2023-11-30 | PXD041005 | Pride
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