19 research outputs found
Genetic background influences murine prostate gene expression: implications for cancer phenotypes
Microarray analyses to quantitate transcript levels in the prostates of five inbred mouse strains identified differences in gene expression in benign epithelium that correlated with the differentiation state of adjacent tumors
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Performance of PCA3 and TMPRSS2:ERG urinary biomarkers in prediction of biopsy outcome in the Canary Prostate Active Surveillance Study (PASS).
BackgroundFor men on active surveillance for prostate cancer, biomarkers may improve prediction of reclassification to higher grade or volume cancer. This study examined the association of urinary PCA3 and TMPRSS2:ERG (T2:ERG) with biopsy-based reclassification.MethodsUrine was collected at baseline, 6, 12, and 24 months in the multi-institutional Canary Prostate Active Surveillance Study (PASS), and PCA3 and T2:ERG levels were quantitated. Reclassification was an increase in Gleason score or ratio of biopsy cores with cancer to β₯34%. The association of biomarker scores, adjusted for common clinical variables, with short- and long-term reclassification was evaluated. Discriminatory capacity of models with clinical variables alone or with biomarkers was assessed using receiver operating characteristic (ROC) curves and decision curve analysis (DCA).ResultsSeven hundred and eighty-two men contributed 2069 urine specimens. After adjusting for PSA, prostate size, and ratio of biopsy cores with cancer, PCA3 but not T2:ERG was associated with short-term reclassification at the first surveillance biopsy (ORβ=β1.3; 95% CI 1.0-1.7, pβ=β0.02). The addition of PCA3 to a model with clinical variables improved area under the curve from 0.743 to 0.753 and increased net benefit minimally. After adjusting for clinical variables, neither marker nor marker kinetics was associated with time to reclassification in subsequent biopsies.ConclusionsPCA3 but not T2:ERG was associated with cancer reclassification in the first surveillance biopsy but has negligible improvement over clinical variables alone in ROC or DCA analyses. Neither marker was associated with reclassification in subsequent biopsies
The Effects of Aging on the Molecular and Cellular Composition of the Prostate Microenvironment
Advancing age is associated with substantial increases in the incidence rates of common diseases affecting the prostate gland including benign prostatic hyperplasia (BPH) and prostate carcinoma. The prostate is comprised of a functional secretory epithelium, a basal epithelium, and a supporting stroma comprised of structural elements, and a spectrum of cell types that includes smooth muscle cells, fibroblasts, and inflammatory cells. As reciprocal interactions between epithelium and stromal constituents are essential for normal organogenesis and serve to maintain normal functions, discordance within the stroma could permit or promote disease processes. In this study we sought to identify aging-associated alterations in the mouse prostate microenvironment that could influence pathology.We quantitated transcript levels in microdissected glandular-adjacent stroma from young (age 4 months) and old (age 20-24 months) C57BL/6 mice, and identified a significant change in the expression of 1259 genes (p<0.05). These included increases in transcripts encoding proteins associated with inflammation (e.g., Ccl8, Ccl12), genotoxic/oxidative stress (e.g., Apod, Serpinb5) and other paracrine-acting effects (e.g., Cyr61). The expression of several collagen genes (e.g., Col1a1 and Col3a1) exhibited age-associated declines. By histology, immunofluorescence, and electron microscopy we determined that the collagen matrix is abundant and disorganized, smooth muscle cell orientation is disordered, and inflammatory infiltrates are significantly increased, and are comprised of macrophages, T cells and, to a lesser extent, B cells.These findings demonstrate that during normal aging the prostate stroma exhibits phenotypic and molecular characteristics plausibly contributing to the striking age associated pathologies affecting the prostate
Mouse prostate strain-associated gene expression and analysis in human prostate tissues: FVB/N and C57BL/6
Genes differentially expressed in prostates of FVB/N and C57BL/6 strains. Heat map colors reflect fold ratio values between sample and reference pool. Columns 1-4 represent biological replicates for each strain. Rows represent individual genes. Values shown in red are relatively larger than the overall mean; values shown in green are relatively smaller than the overall mean. Transcript abundance levels in benign human prostate tissues associated with high grade (7-10) or low grade (β€6) adenocarcinomas for each gene determined to be altered in mouse strain comparisons where a corresponding ortholog was identified. Genes depected in (a) and (b) are in identical order. Black box (b) and text (a) represent genes with significant differential expression in the human datasets altered in the expected orientation. Gray box (b) and text (a) represent genes with significant differential expression in the human datasets altered in the opposite orientation. Transcript alterations for selected genes in benign tissue samples associating with high (Gleason 7-10) and low (Gleason β€6) prostate cancers. Plots represent the 95% confidence intervals of logexpression ratios of tissues samples relative to a cell line reference.<p><b>Copyright information:</b></p><p>Taken from "Genetic background influences murine prostate gene expression: implications for cancer phenotypes"</p><p>http://genomebiology.com/2007/8/6/R117</p><p>Genome Biology 2007;8(6):R117-R117.</p><p>Published online 18 Jun 2007</p><p>PMCID:PMC2394769.</p><p></p
Analysis of strain-dependent differences in prostate gene expression by qRT-PCR
RNAs from preparations used in the microarray analysis or microdissected epithelium were reverse transcribed and amplified using qRT-PCR with primers specific for (), (), () and (). Ribosomal protein S16 expression levels were used to normalize qRT-PCR data. Normalized results are expressed relative to the lowest expressing value. Error bars indicate the standard deviation of four biological independent replicates. qRT-PCR for microdissected epithelium is represented by one sample per strain for each gene. White bars denote measurements from the microarray analysis. Black bars denote measurements generated by qRT-PCR from whole prostate. Diagonal lines denote measurements generated by qRT-PCR from microdissected prostate epithelium.<p><b>Copyright information:</b></p><p>Taken from "Genetic background influences murine prostate gene expression: implications for cancer phenotypes"</p><p>http://genomebiology.com/2007/8/6/R117</p><p>Genome Biology 2007;8(6):R117-R117.</p><p>Published online 18 Jun 2007</p><p>PMCID:PMC2394769.</p><p></p
Mouse prostate strain-associated gene expression and analysis in human prostate tissues: BALB/c and C57BL/6
Genes differentially expressed in prostates of BALB/c (BALB) and C57BL/6 (C57) strains. Heat map colors reflect fold ratio values between sample and reference pool. Columns 1-4 represent biological replicates for each strain. Rows represent individual genes. Values shown in red are relatively larger than the overall mean; values shown in green are relatively smaller than the overall mean. Transcript abundance levels in benign human prostate tissues associated with high grade (7-10) or low grade (β€6) adenocarcinomas for each gene determined to be altered in mouse strain comparisons where a corresponding ortholog was identified. Genes depicted in (a) and (b) are in identical order. Black box (b) and text (a) represent genes with significant differential expression in the human datasets altered in the expected orientation. Gray box (b) and text (a) represent genes with significant differential expression in the human datasets altered in the opposite orientation. Transcript alterations for selected genes in benign tissue samples associating with high (Gleason 7-10) and low (Gleason β€6) prostate cancers. Plots represent the 95% confidence intervals of logexpression ratios of tissues samples relative to a cell line reference.<p><b>Copyright information:</b></p><p>Taken from "Genetic background influences murine prostate gene expression: implications for cancer phenotypes"</p><p>http://genomebiology.com/2007/8/6/R117</p><p>Genome Biology 2007;8(6):R117-R117.</p><p>Published online 18 Jun 2007</p><p>PMCID:PMC2394769.</p><p></p
The Landscape of Somatic Chromosomal Copy Number Aberrations in GEM Models of Prostate Carcinoma
Expression of Hairy Target Genes Is Disrupted in <i>hairy</i> Mutant Embryos
<p>Whole mount in situ hybridization on wild-type (A, C, E, G, I, K, and M) or <i>hairy<sup>7H</sup></i> mutant (B, D, F, H, J, L, and N) embryos with probes recognizing <i>prd</i> (A and B), <i>stg</i> (C and D), <i>ImpL2</i> (E and F), <i>mae</i> (G and H), <i>egh</i> (I and J), <i>kayak</i> (K and L), or <i>Idgf2</i> (M and N). Anterior is to the left. Dorsal is up, except in (M) and (N), which are dorsal views.</p
Hairy Target Gene Expression Is Disrupted in the Mutant Background of the Cofactors Associated with a Particular Target
<div><p>Whole mount in situ hybridization on wild-type (A, E, and I), <i>groucho</i> germline clone</p>
<p>(B, F, and J), <i>dCtBP</i> germline clone (C, G, and K), and <i>dSir2</i> mutant (D, H, and L) embryos with probes recognizing <i>stg</i> (AβD), <i>kayak</i> (EβH), or <i>prd</i> (IβL). Anterior is to the left. Dorsal is up.</p></div