Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA244319 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR1232072.fastq.gz | Fastqsanger.gz | |||
| SRR1232073.fastq.gz | Fastqsanger.gz |
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Project description:The objective of this study was to determine whether prostate cancer-associated miRNAs are present in seminal fluid and, if so, evaluate their diagnostic potential. Small RNA sequencing was used to profile and compare miRNAs in the non-sperm cellular fraction of seminal fluid from men with biopsy-proven cancer (one pooled sample from 6 men) and men with elevated serum PSA but negative biopsy results (one pooled sample from 6 men).
2014-04-15 | E-GEOD-56686 | 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:The objective of this study was to determine whether prostate cancer-associated miRNAs are present in seminal fluid and, if so, evaluate their diagnostic potential.
2014-04-15 | GSE56686 | GEO
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
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2010-10-18 | GSE24171 | GEO
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Project description:Candidate prostate cancer genes through comparative expression-profiling of seminal vesicle
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Project description:Prostate-specific antigen, a blood serum biomarker of prostate cancer, lacks specificity and prognostic significance, so considerable efforts are devoted to developing novel biomarkers. Seminal plasma, due to its proximity to prostate, is a promising fluid for biomarker discovery and non-invasive diagnostics. In this study, we investigated if seminal plasma proteins could increase specificity of detecting primary prostate cancer and discriminate between high- and low-grade cancers. To select 148 most promising biomarker candidates, we combined proteins identified through five independent data mining or experimental approaches: tissue transcriptomics, seminal plasma proteomics, cell secretomics, tissue specificity and androgen regulation. A rigorous biomarker development pipeline based on targeted proteomics assays was designed to evaluate the most promising candidates. We qualified 77 and verified 19 proteins in seminal plasma of 67 negative biopsy and 155 prostate cancer patients. Verification revealed a prostate-specific, secreted and androgen-regulated protein-glutamine gamma-glutamyltransferase 4 (TGM4), which could predict prostate cancer on biopsy and outperformed age and serum PSA. Machine-learning approaches also revealed improved multi-marker combinations for diagnosis and prognosis. In the independent verification set measured by an in-house ELISA, TGM4 was up-regulated 3.7-fold (P=0.006) and revealed AUC 0.66 for detecting prostate cancer on biopsy for patients serum PSA≥4 ng/mL and age≥50. Low levels of TGM4 (120 pg/mL) were detected in blood serum, but could not differentiate between negative biopsy, prostate cancer or prostate inflammation. To conclude, performance of TGM4 warrants its further investigation within the distinct genomic subtypes of prostate cancer and evaluation for the inclusion into emerging multi-biomarker panels.
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