Homo sapiens
Ontology highlight
ABSTRACT:
OTHER RELATED OMICS DATASETS IN: E-GEOD-3325
PROVIDER: PRJNA93223 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:An integrative analysis of this compendium of proteomic alterations and transcriptomic data was performed revealing only 48-64% concordance between protein and transcript levels. Importantly, differential proteomic alterations between metastatic and clinically localized prostate cancer that mapped concordantly to gene transcripts served as predictors of clinical outcome in prostate cancer as well as other solid tumors. Keywords: prostate cancer progression 13 individual benign prostate, primary and metastatic prostate cancer samples and 6 pooled samples from benign,primary or metastatic prostate cancer tissues.
2005-09-20 | E-GEOD-3325 | biostudies-arrayexpress
Project description:An integrative analysis of this compendium of proteomic alterations and transcriptomic data was performed revealing only 48-64% concordance between protein and transcript levels. Importantly, differential proteomic alterations between metastatic and clinically localized prostate cancer that mapped concordantly to gene transcripts served as predictors of clinical outcome in prostate cancer as well as other solid tumors. Keywords: prostate cancer progression
2005-09-20 | GSE3325 | GEO
Project description:Using laser capture microdissection to isolate over 100 specific cell populations, we report the profiling of prostate cancer progression from benign epithelium to metastatic disease. By analyzing these expression signatures in the context of over 15,000 “molecular concepts”, or sets of biologically connected genes, we generated an integrative model of prostate cancer progression. Keywords: disease state analysis
2006-12-17 | GSE6099 | GEO
Project description:Transcription profiling by array of human benign prostate, primary and metastatic prostate cancer samples to reveal signatures of metastatic progression
2014-07-03 | E-GEOD-3325 | ExpressionAtlas
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:Integrative Analysis of Genomic Aberrations Associated with Prostate Cancer Progression
| PRJNA100833 | ENA
Project description:Integrative Molecular Concepts Modeling of Prostate Cancer Progression
| PRJNA97661 | ENA
Project description:Current knowledge of prostate cancer genomes is largely based on relatively small patient cohorts using single modality analysis platforms. Here we report concordant assessment of DNA copy number, mRNA and microRNA expression and focused exon resequencing in prostate tumors from 218 patients with primary or metastatic prostate cancer with a median of 5 years clinical follow-up, now made available as a public resource. Mutations in known, commonly mutated oncogenes and tumor suppressor genes such as PIK3CA, KRAS, BRAF and TP53 are present but generally rare. However, integrative analysis of mutations with copy number alterations (CNAs) and expression changes reveal alterations in the PI3K, RAS/RAF and androgen receptor (AR) pathways in nearly all metastatic samples and in a higher frequency of primary samples than previously suspected based on single-gene studies. Other new findings include evidence that the nuclear receptor coactivator NCOA2 functions as a driver oncogene in ~20 percent of primaries. Tumors with the androgen-driven TMPRSS2-ERG fusion were significantly associated with a small, previously unrecognized, prostate-specific 3p14 deletion that, through mRNA expression and resequencing analysis, implicates FOXP1, RYBP and SHQ1 as candidate cooperative tumor suppressors. Comparison of transcriptome and DNA copy number data from primary tumors for prognostic impact revealed that CNAs robustly define clusters of low- and high-risk disease beyond that achieved by Gleason score. In sum, this integrative genomic analysis of a substantial cohort of tumors clarifies the role of several known cancer pathways in prostate cancer, implicates several new ones, reveals a previously unappreciated role for CNAs in prognosis and provides a blueprint for clinical development of pathway inhibitors. Human prostate samples were profiled on Agilent microRNA V2 arrays per manufacturer's instructions.
2010-06-24 | E-GEOD-21036 | biostudies-arrayexpress
Project description:Samples of benign prostate tissue, localized prostate cancer tissue, and metastatic prostate cancer tissue are profiled to study expression changes in diagnosis and progression of prostate cancer. Each tissue sample is also profiled for metabolomics data Keywords: Cancer Progression 41 samples were analyzed (16 benign prostate tissue, 12 local prostate cancer tissue, 13 metastatic prostate cancer tissue)
2011-03-30 | E-GEOD-8511 | biostudies-arrayexpress
Project description:The current view of cellular transformation and cancer progression supports the notion that cancer cells must reprogram their metabolism in order to survive and progress in different microenvironments. Master co-regulators of metabolism orchestrate the modulation of multiple metabolic pathways through transcriptional programs, and hence constitute a probabilistically parsimonious mechanism for general metabolic rewiring. Here we show that the transcriptional co-activator PGC1α suppresses prostate cancer progression and metastasis. A metabolic co-regulator data mining analysis unveiled that PGC1α is consistently down-regulated in multiple prostate cancer patient datasets and its alteration is associated with reduced disease-free survival and metastasis. Genetically engineered mouse model studies revealed that compound prostate epithelium-specific deletion of Pgc1a and Pten promotes prostate cancer progression and metastasis, whereas, conversely, PGC1α expression in cell lines inhibits the pre-existing metastatic capacity. Through the application of integrative metabolomics and transcriptomics we demonstrate that PGC1α expression in prostate cancer is sufficient to elicit a global metabolic rewiring that opposes cell growth, consisting of sustained oxidative metabolism at the expense of anabolism. This metabolic program is regulated downstream the Oestrogen-related receptor alpha (ERRα), and PGC1α mutants lacking ERRα activation capacity lack metabolic rewiring capacity and metastasissuppressive function. Importantly, an ERRα signature in prostate cancer recapitulates the prognostic features of PGC1A. Our findings uncover an unprecedented causal contribution of PGC1α to the metabolic switch in prostate cancer and to the suppression of metastatic dissemination. Total RNA was isolated from prostate cancer cell line PC3 expressing or not PGC1a (for induction, cells were treated with doxycycline for 2 passages)
2016-03-16 | E-GEOD-75193 | biostudies-arrayexpress