Unknown,Transcriptomics,Genomics,Proteomics

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Candidate prostate cancer genes through comparative expression-profiling of seminal vesicle

ABSTRACT: 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).

ORGANISM(S): Homo sapiens

SUBMITTER: Jonathan Pollack

PROVIDER: E-GEOD-11376 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Identification of candidate prostate cancer genes through comparative expression-profiling of seminal vesicle.

Thompson Maxwell M Lapointe Jacques J Choi Yoon-La YL Ong David E DE Higgins John P JP Brooks James D JD Pollack Jonathan R JR

The Prostate 20080801 11

<h4>Background</h4>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.<h4>Method ...[more]

PMID: 18500686

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Project description:These 95 arrays are the basis for Figure 2 of our manuscript "An interferon-response induced by tumor-stroma interaction in a subset of human breast cancers". Abstract:Background Communication between different cell types is a cardinal feature of multi-cellular organisms and perturbations in these cell-cell interactions are a key feature of cancer. However, little is known about the systematic effects of cell-cell interaction on global gene expression in cancer. Methods and Findings We used an ex vivo culture model to simulate tumor-stroma interaction by systematically co-cultivating breast cancer cells with stromal fibroblasts and determined associated gene expression changes with cDNA microarrays. The picture of heterotypic interaction effects that emerged from this analysis is complex, reflecting the variation in signaling capacities and responsiveness of the involved cells. A frequent and prominent response to epithelial-mesenchymal interaction was an induction of interferon-response genes, observed in 4 of the 7 breast cancer cell lines in response to co-culture with fibroblasts, but not in normal mammary epithelial cells. In response to close contact with these breast cancer cells, the fibroblasts secreted type I interferons, which, in turn, induced expression of the IRGs in the tumor cells. Immunohistochemical analysis of human breast cancer tissues showed that STAT1, the key transcriptional activator of the interferon-response genes, and itself an IRG, was expressed in a subset of the cancers, with a striking pattern of elevated expression in the cancer cells in contact with, or close proximity to, the tumor stroma ? paralleling the response seen in our ex vivo model. In vivo, expression of the interferon-response genes was remarkably coherent, providing a basis for segregation of the 295 early-stage breast cancers into two groups. Tumors with high expression levels (n=161) of IRG were associated with significantly shorter overall survival; 59 % at 10 years versus 80% for tumors with low interferon-response gene expression levels (n=134) (log-rank p=0.001). Conclusion Our results suggest that an interaction between some breast cancer cells and stromal fibroblasts can induce an interferon response, and that this response may be associated with a greater propensity for tumor progression. Set of arrays organized by shared biological context, such as organism, tumors types, processes, etc. Computed

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Candidate prostate cancer genes through comparative expression-profiling of seminal vesicle

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Identification of candidate prostate cancer genes through comparative expression-profiling of seminal vesicle.

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