Prostate Cancer Upgrading Reference Set
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ABSTRACT:
PROVIDER: PRJNA1120958 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Prostate Cancer Upgrading Reference Set
| PRJNA1120957 | ENA
Project description:Prostate cancer is one of the most commonly diagnosed cancers among men in the world and the pathogenesis of prostate cancer remains poorly understood. In this study, we intended to disclose genes that might be involved in tumorigenesis using cDNA microarray technology. Keywords: disease state analysis A total of 28 experiments were performed without replicates, using a pool of unrelated fetal tissues as common references. 25 experiments were done for prostate cancer versus common reference and 3 for normal prostate versus common reference. Prostate cancer and normal prostate samples were labeled with Cy5-dUTP. Common references were labeled with Cy3-dUTP.
2008-09-25 | E-GEOD-5957 | biostudies-arrayexpress
Project description:A set of 17 prostate cancer patient-derived xenografts (PDX, Lin et al 2014, Cancer research) was analyzed by mass spectrometry-based proteomics to characterize the effects of castration in vivo, and the proteome differences between NEPC and prostate adenocarcinomas.
2019-09-11 | PXD009636 | Pride
Project description:Reference Proteome-Based Stomach Cancer Quantitative Proteome Analysis
2022-07-05 | PXD027082 | JPOST Repository
Project description:In this study, comparison of gene expression profiles in benign epithelia from men with prostate cancer to those of men without prostate cancer reveal differences in several genes associated with prostate cancer. Custom Agilent 44K whole human genome expression oligonucleotide microarrays were used to profile benign epithelium from prostate needle biopsies from 15 men with high grade(Gleason 8-10) prostate cancer and 14 age- and BMI-matched controls. All samples were laser-capture microdissected and total RNA isolated and amplified prior to hybridization against a common reference pool of prostate tumor cell lines
2010-10-18 | E-GEOD-24171 | biostudies-arrayexpress
Project description:Prostate adenocarcinoma and matched adjacent normal samples were profiled by deep transcriptional sequencing to analyze transcription-induced chimeras and gene fusions. Reference samples from the MAQC and brain and universal reference libraries were also sequenced.
2010-09-23 | GSE24283 | GEO
Project description:Reference Set of Mycobacterium tuberculosis Clinical Strains: A tool for research and product development
| PRJEB27802 | ENA
Project description:Background Understanding the heterogeneous genotypes and phenotypes of prostate cancer is fundamental to improving the way we treat this disease. As yet, there are no validated descriptions of prostate cancer subgroups derived from integrated genomics linked with clinical outcome. Methods In a study of 482 tumour, benign and germline samples from 259 men with primary prostate cancer, we used integrative analysis of copy number alterations (CNA) and array transcriptomics to identify genomic loci that affect expression levels of mRNA in an expression quantitative trait loci (eQTL) approach, to stratify patients into subgroups that we then associated with future clinical behavior, and compared with either CNA or transcriptomics alone. Findings We identified five separate patient subgroups with distinct genomic alterations and expression profiles based on 100 discriminating genes in our separate discovery and validation sets of 125 and 99 men. These subgroups were able to consistently predict biochemical relapse (p=0.0017 and p=0.016 respectively) and were further validated in a third cohort with long-term follow-up (p=0.027). We show the relative contributions of gene expression and copy number data on phenotype, and demonstrate the improved power gained from integrative analyses. We confirm alterations in six genes previously associated with prostate cancer (MAP3K7, MELK, RCBTB2, ELAC2, TPD52, ZBTB4) in prostate cancer, and also identify 94 genes not previously linked to prostate cancer progression that would not have been detected using either transcript or copy number data alone. We confirm a number of previously published molecular changes associated with high risk disease, including MYC amplification, and NKX3-1, RB1 and PTEN deletions, as well as over-expression of PCA3 and AMACR, and loss of MSMB in tumour tissue. A subset of the 100 genes outperforms established clinical predictors of poor prognosis (PSA, Gleason score), as well as previously published gene signatures (p=0•0001). We further show how our molecular profiles can be used for the early detection of aggressive cases in a clinical setting, and inform treatment decisions. Interpretation For the first time this study demonstrates the importance of integrated genomic analyses incorporating both benign and tumour tissue data in identifying molecular alterations leading to generation of robust gene sets that are predictive of clinical outcome in independent patient cohorts. A total of 482 samples from 289 men with prostate cancer from two cohorts were included in this study. The discovery cohort comprised 125 tumour samples from radical prostatectomy (RP) with 118 matched benign samples, and 85 matched blood samples. An additional 4 benign samples from men undergoing Holmium laser enucleation of the prostate (HoLEP) and 16 radical prostatectomy samples from men with castrate-resistant prostate cancer, with 13 matched blood samples were also included. These were assayed on several platforms, including Illumina HT12v4 gene expression arrays, Illumina OMNI2.5M genotyping arrays and Affymetrix SNP6 genotyping arrays. The validation cohort comprised 103 tumour tissue samples from men with prostate cancer, with 99 matched benign tissue samples and 103 matched blood samples. This datasheet describes samples in the DISCOVERY COHORT only, with complete, QCd Illumina HT12v4 data for 13 CRPC samples, 113 tumour samples and 73 matched benign samples.
2015-09-15 | E-GEOD-73012 | biostudies-arrayexpress