Homo sapiens
Ontology highlight
ABSTRACT:
OTHER RELATED OMICS DATASETS IN: E-GEOD-22260
PROVIDER: PRJNA128733 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Comparative transcriptomic analysis of prostate cancer and matched normal tissue using RNA-seq
2019-05-14 | E-GEOD-22260 | ExpressionAtlas
Project description:To conduct comparative transcriptomic analyses on normal or malignant prostate epithelial cells in response to tissue contextual changes, we cultured immortalized prostate epithelial cells or prostate cancer cells as cell monolayers or three-dimensional organoids and profiled their transcriptomes in respective culture contexts.
2011-07-03 | GSE30304 | GEO
Project description:To conduct comparative transcriptomic analyses on normal or malignant prostate epithelial cells in response to tissue contextual changes, we cultured immortalized prostate epithelial cells or prostate cancer cells as cell monolayers or three-dimensional organoids and profiled their transcriptomes in respective culture contexts. RWPE-1 (immortalized prostate epithelial cells) and LNCaP cells (prostate cancer cells) were seeded on reconstituted basement membrane (rBM)-coated culture plastics or cultured within three-dimensional (3D) rBM gels. Total RNA samples were collected from cell monolayers or 3D cell clusters (formed at day 2) or acini or spheroids (formed at day 6) in the rBM culture, followed by global gene expression profiling.
2011-07-03 | E-GEOD-30304 | biostudies-arrayexpress
Project description:Recurrent point mutations in SPOP define a distinct molecular subclass of prostate cancer. Here, we describe the first mouse model showing that mutant SPOP drives prostate tumorigenesis in vivo. Conditional expression of mutant SPOP in the prostate dramatically altered phenotypes in the setting of Pten loss, with early neoplastic lesions (high-grade prostatic intraepithelial neoplasia) with striking nuclear atypia, and invasive poorly differentiated carcinoma. In mouse prostate organoids, mutant SPOP drove increased proliferation and a transcriptional signature consistent with human prostate cancer. Using these models and human prostate cancer samples, we show that SPOP mutation activates both PI3K/mTOR and androgen receptor (AR) signaling, effectively uncoupling the normal negative feedback between these two pathways. Associated RNA-seq data deposited in GEO: GSE94839.
2017-03-20 | PXD005309 | Pride
Project description:We used RNA-seq to interrogate prostate cancer specific gene fusions, alternative splicings, somatic mutations and novel transcripts. We sequenced the transcriptome (polyA+) of 20 prostate cancer tumors and 10 matched normal tissues using Illumina GAII platform. Then we used bioinformatic approaches to identify prostate cancer specific aberrations which include gene fusion, alternative splicing, somatic mutation, etc.
2011-05-02 | E-GEOD-22260 | biostudies-arrayexpress
Project description:Deregulated expression of miRNAs contributes to prostate cancer progression. This study is aimed to identify which miRNA(S) is (are) asociated with prostate cancer aggressiveness. Prostate cancer tissues and matched adjacent normal tissue were used to isolate total RNA. miRNA expressions were analyzed by miRNA Microarray assay.
2011-12-10 | E-GEOD-34310 | biostudies-arrayexpress
Project description:BACKGROUND: Prostate cancer is the most frequently diagnosed cancer among men in the United States. In contrast, cancer of the seminal vesicle is exceedingly rare, despite that the prostate and seminal vesicle share similar histology, secretory function, androgen dependency, blood supply, and (in part) embryonic origin. We hypothesized that gene-expression differences between prostate and seminal vesicle might inform mechanisms underlying the higher incidence of prostate cancer. METHODS: Whole-genome DNA microarrays were used to profile gene expression of 11 normal prostate and 7 seminal vesicle specimens (including 6 matched pairs) obtained from radical prostatectomy. Supervised analysis was used to identify genes differentially expressed between normal prostate and seminal vesicle, and this list was then cross-referenced to genes differentially expressed between normal and cancerous prostate. Expression patterns of selected genes were confirmed by immunohistochemistry using a tissue microarray. We identified 32 genes that displayed a highly statistically-significant expression pattern with highest levels in seminal vesicle, lower levels in normal prostate, and lowest levels in prostate cancer. Among these genes was the known candidate prostate tumor suppressor GSTP1 (involved in xenobiotic detoxification). The expression pattern of GSTP1 and four other genes, ABCG2 (xenobiotic transport), CRABP2 (retinoic acid signaling), GATA3 (lineage-specific transcription) and SLPI (immune response), was confirmed by immunohistochemistry. CONCLUSIONS: Our findings identify candidate prostate cancer genes whose reduced expression in prostate (compared to seminal vesicle) may be permissive to prostate cancer initiation. Such genes and their pathways may inform mechanisms of prostate carcinogenesis, and suggest new opportunities for prostate cancer prevention. Set of arrays organized by shared biological context, such as organism, tumors types, processes, etc. Disease State: normal prostate vs normal seminal vesicle sample Individual Keywords: Logical Set cDNA microarrays from the Stanford Functional Genomics Facility were used for expression profiling of 11 normal prostate and 7 seminal vesicle specimens (6 of which were matched pairs), against a universal RNA reference. Extracted expression ratios were normalized by array then mean centered by gene, and expression differences between normal prostate and seminal vesicle identified using Significance Analysis of Microarrays (SAM).
2008-05-08 | E-GEOD-11376 | biostudies-arrayexpress
Project description:Mass spectrometry-based proteomic analysis of urinary EV (uEV) in men with benign and malignant prostate disease, profiling the proteome of EV separated from prostate tumor interstitial fluid and matched uEV, and a comparative proteomic analysis with uEV from patients with bladder and renal cancer.
2020-04-09 | PXD015289 | Pride
Project description:To identify new oncogenic drivers in prostate cancer, we performed transcriptome analysis of localized primary prostate cancer samples and the matched normal tissues.
2021-05-01 | GSE114740 | GEO
Project description:We performed RNA-Seq analysis of plasma and urinary EVs collected before and after radical prostatectomy, and matched tumor and normal prostate tissues of 10 patients with prostate cancer. To identify putative cancer-derived RNA biomarkers, we searched for RNAs that were overexpressed in tumor as compared to normal tissues, present in the pre-operation EVs and decreased in the post-operation EVs in each RNA biotype.
2022-11-16 | E-MTAB-11910 | biostudies-arrayexpress