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GSE104786
Homo sapiens
12 Downloadable Samples
Affymetrix Human Exon 1.0 ST Array [transcript (gene) version (huex10st)
Description
Neuroendocrine prostate cancer (NEPC) is rare historically but may be increasingin prevalence as patients potentially develop resistance to contemporary anti-androgen treatment through a neuroendocrine phenotype. Diagnosis can be straightforward when classic morphological features are accompanied by a prototypical immunohistochemistry profile, however there is increasing recognition of disease heterogeneity and hybrid phenotypes. In the primary setting, small cell prostatic carcinoma (SCPC) is frequently admixed with adenocarcinomas that may be clonally related, while a small fraction of SCPCs express markers typical of prostatic adenocarcinoma. Gene expression patterns may eventually help elucidate the biology underlying equivocal cases with discordant IHC, however studies to date have focused on prototypical cases and been based on few patients due to disease rarity.
Publication Title
Gene expression signatures of neuroendocrine prostate cancer and primary small cell prostatic carcinoma.
Sample Metadata Fields
Subject
View Samples- Homo sapiens
- 199 Downloadable Samples
- Affymetrix Human Exon 1.0 ST Array [probe set (exon) version (huex10st)
Description
Purpose: Selecting muscle-invasive bladder cancer patients for adjuvant therapy is currently based on clinical variables with limited power. We hypothesized that genomic-based signatures can outperform clinical models to identify patients at higher risk. Method:Transcriptome-wide expression profiles were generated using 1.4 million feature-arrays on archival tumors from 225 patients who underwent radical cystectomy and had muscle-invasive and/or node-positive bladder cancer. A 15-feature GC was developed on the discovery set with area under curve (AUC) of 0.77 in the validation set.
Publication Title
Discovery and validation of novel expression signature for postcystectomy recurrence in high-risk bladder cancer.
Sample Metadata Fields
Specimen part
View Samples- Homo sapiens
- 130 Downloadable Samples
- Affymetrix Human Exon 1.0 ST Array [probe set (exon) version (huex10st)
Description
To test the hypothesis that a genomic classifier (GC) would predict biochemical failure (BF) and distant metastasis (DM) in men receiving radiation therapy (RT) after radical prostatectomy (RP).
Publication Title
The Landscape of Prognostic Outlier Genes in High-Risk Prostate Cancer.
Sample Metadata Fields
Age
View Samples- Homo sapiens
- 85 Downloadable Samples
- Affymetrix Human Exon 1.0 ST Array [probe set (exon) version (huex10st)
Description
BACKGROUND: Due to their varied outcomes, men with biochemical recurrence (BCR) following radical prostatectomy (RP) present a management dilemma. Here, we evaluate Decipher, a genomic classifier (GC), for its ability to predict metastasis following BCR.
Publication Title
A genomic classifier predicting metastatic disease progression in men with biochemical recurrence after prostatectomy.
Sample Metadata Fields
Specimen part
View Samples- Homo sapiens
- 147 Downloadable Samples
- Affymetrix Human Exon 1.0 ST Array [transcript (gene) version (huex10st)
Description
Molecular and genomic analysis of microscopic quantities of tumor from formalin-fixed and paraffin-embedded (FFPE) biopsies has many unique challenges. Here we evaluated the feasibility of obtaining transcriptome-wide RNA expression to measure prognostic classifiers from diagnostic prostate needle core biopsies.
Publication Title
Application of a Clinical Whole-Transcriptome Assay for Staging and Prognosis of Prostate Cancer Diagnosed in Needle Core Biopsy Specimens.
Sample Metadata Fields
Specimen part, Subject
View Samples- Homo sapiens
- 545 Downloadable Samples
- Affymetrix Human Exon 1.0 ST Array [probe set (exon) version (huex10st)
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.
Publication Title
Discovery and validation of a prostate cancer genomic classifier that predicts early metastasis following radical prostatectomy.
Sample Metadata Fields
No sample metadata fields
View Samples- Homo sapiens
- 260 Downloadable Samples
Affymetrix Human Exon 1.0 ST Array [probe set (exon) version (huex10st)
Description
Radical prostatectomy (RP) is a primary treatment option for men with intermediate- and high-risk prostate cancer. Although many are effectively cured with local therapy alone, these men are by definition at higher risk of adverse pathologic features. It has been shown previously that genomic data can be used to predict tumor aggressiveness. Our objective was to evaluate genomic data and it's relationship to pathological stage and grade in a cohort of men that received no treatment other than radical prostatectomy surgery.
Publication Title
Tissue-based Genomics Augments Post-prostatectomy Risk Stratification in a Natural History Cohort of Intermediate- and High-Risk Men.
Sample Metadata Fields
Age, Specimen part
View Samples- Homo sapiens
- 17 Downloadable Samples
- Affymetrix Human Exon 1.0 ST Array [probe set (exon) version (huex10st)
Description
Standard clinicopathological variables are inadequate for optimal management of prostate cancer patients. While genomic classifiers have improved patient risk classification, the multifocality and heterogeneity of prostate cancer can confound pre-treatment assessment. The objective is to investigate the association of multiparametric (mp)MRI quantitative features with prostate cancer risk gene expression profiles in mpMRI-guided biopsies tissues.
Publication Title
Association of multiparametric MRI quantitative imaging features with prostate cancer gene expression in MRI-targeted prostate biopsies.
Sample Metadata Fields
Age, Specimen part
View Samples- Homo sapiens
- 235 Downloadable Samples
- Affymetrix Human Exon 1.0 ST Array [probe set (exon) version (huex10st)
Description
Purpose: Patients with locally advanced prostate cancer after radical prostatectomy are candidates for secondary therapy. However, this higher risk population is heterogeneous. Many cases do not metastasize even when conservatively managed. Given the limited specificity of pathological features to predict metastasis, newer risk prediction models are needed. We report a validation study of a genomic classifier that predicts metastasis after radical prostatectomy in a high risk population. Method:A case-cohort design was used to sample 1,010 patients after radical prostatectomy at high risk for recurrence who were treated from 2000 to 2006. Patients had preoperative prostate specific antigen greater than 20 ng/ml, Gleason 8 or greater, pT3b or a Mayo Clinic nomogram score of 10 or greater. Patients with metastasis at diagnosis or any prior treatment for prostate cancer were excluded from analysis. A 20% random sampling created a subcohort that included all patients with metastasis. We generated 22-marker genomic classifier scores for 235 patients with available genomic data. ROC and decision curves, competing risk and weighted regression models were used to assess genomic classifier performance.
Publication Title
Validation of a genomic classifier that predicts metastasis following radical prostatectomy in an at risk patient population.
Sample Metadata Fields
Age
View Samples- Homo sapiens
- 12 Downloadable Samples
IlluminaHiSeq2000
Description
Prostate cancer is the most common male cancer and androgen receptor (AR) is the major driver of the disease. Here we show that Enoyl-CoA delta isomerase 2 (ECI2) is a novel AR-target that promotes prostate cancer cell survival. Increased ECI2 expression predicts mortality in prostate cancer patients (p=0.0086). ECI2 encodes for an enzyme involved in lipid metabolism, and we use multiple metabolite profiling platforms and RNA-seq to show that inhibition of ECI2 expression leads to decreased glucose utilization, accumulation of fatty acids and down-regulation of cell cycle related genes. In normal cells, decrease in fatty acid degradation is compensated by increased consumption of glucose, and here we demonstrate that prostate cancer cells are not able to respond to decreased fatty acid degradation. Instead, prostate cancer cells activate incomplete autophagy, which is followed by activation of the cell death response. Finally, we identified a clinically approved compound, perhexiline, which inhibits fatty acid degradation, and replicates the major findings for ECI2 knockdown. This work shows that prostate cancer cells require lipid degradation for survival and identifies a small molecule inhibitor with therapeutic potential. Overall design: Two biological replicates for prostate cancer cell line (LNCaP) and cell line representing normal prostate epithelium (RWPE-1), transfected with scrambled siRNA or two different siRNAs targeting ECI2. RNA was extracted and used for RNA-sequencing. The processed files provided are compressed folders containing multiple output files from CuffDiff runs estimating differentially expressed transcripts between the indicated ECI2 siRNA treated cells versus cells treated with Scrambled siRNAs.
Publication Title
Lipid degradation promotes prostate cancer cell survival.
Sample Metadata Fields
No sample metadata fields
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