Integrated microRNA and mRNA Signature Associated with the Transition from the Locally Confined to the Metastasized Clear Cell Renal Cell Carcinoma Exemplified by miR-146-5p.

BACKGROUND: MicroRNAs (miRNAs) regulate gene expression by interfering translation or stability of target transcripts. This interplay between miRNA and their mRNA has been proposed as an important process in cancer development and progression. We have investigated molecular networks impacted by predicted mRNA targets of differentially expressed miRNAs in patients with clear cell renal cell carcinoma (ccRCC) diagnosed with or without metastasis. MATERIAL AND METHODS: miRNA and mRNA microarray expression profiles derived from primary ccRCC from patients with (16 samples) or without diagnosed metastasis (22 samples) were used to identify anti-correlated miRNA-mRNA interaction in ccRCC. For this purpose, Ingenuity pathway analysis microRNA Target Filter, which enables prioritization of experimentally validated and predicted mRNA targets was used. By applying an expression pairing tool, the analysis was focused on targets exhibiting altered expression in our analysis, finding miRNAs and their target genes with opposite or same expression. The resulting identified interactions were revalidated by RT-qPCR in another cohort of ccRCC patients. A selection of the predicted miRNA-mRNA interactions was tested by functional analyses using miRNA knockdown and overexpression experiments in renal cancer cell lines. RESULTS: Among the significantly differentially expressed miRNAs, we have identified three miRNAs (miR-146a-5p, miR-128a-3p, and miR-17-5p) that were upregulated in primary tumors from patients without metastasis and downregulated in primary tumors from patients with metastasis. We have further identified mRNA targets, which expression were inversely correlated to these 3 miRNAs, and have been previously experimentally demonstrated in cancer setting in humans. Specifically, we showed that CXCL8/IL8, UHRF1, MCM10, and CDKN3 were downregulated and targeted by miR-146a-5p. The interaction between miR-146a-5p and their targets CXCL8 and UHRF1 was validated in cell culture experiments. CONCLUSIONS: We identified novel target genes of dysregulated miRNAs, which are involved in the transition from primary RCC without metastases into tumors generating distant metastasis.

miRNA profiling identifies candidate mirnas for bladder cancer diagnosis and clinical outcome.

Bladder cancer is a common cancer in the Western world. The current prognosticators such as tumor grade, stage, size, and multifocality do not accurately reflect the clinical outcome. It is of clinical interest to identify biomarkers that could improve diagnostic and/or prognostic predictions. The objectives of this study were to identify deregulated miRNAs in bladder cancer samples and evaluate their potential as diagnostic and prognostic biomarkers. We screened 723 miRNAs by microarray and selected a subset of 15 distinctively deregulated miRNAs for further validation by real-time quantitative RT-(q)PCR. Seven miRNAs (miR-20a, miR-106b, miR-130b, miR-141, miR-200a, miR-200a*, and miR-205) were found to be up-regulated and eight miRNAs (miR-100, miR-125b, miR-130a, miR-139-5p, miR-145*, miR-199a-3p, miR-214, and miR-222) were found to be down-regulated in malignant bladder tissue samples compared to healthy tissue. Four miRNAs that have already been described in the literature (miR-141, miR-199a-3p, miR-205, and miR-214) were significantly differentially expressed between nonmuscle-invasive and muscle-invasive bladder cancer. Furthermore, real-time RT-qPCR of all miRNAs provided high overall correct classification (>75%) of bladder cancer diagnosis. Two miRNAs (miR-141 and miR-205) were associated with overall survival time. The verification of tumor-specific miRNA expression profile, together with the observed association of miR-141 and miR-205 expression with overall survival, underline the potential of miRNAs to function as diagnostic and/or prognostic markers of bladder cancer.

Identification of metastamirs as metastasis-associated microRNAs in clear cell renal cell carcinomas.

MicroRNAs (miRNAs) play a pivotal role in cancerogenesis and cancer progression, but their specific role in the metastasis of clear cell renal cell carcinomas (ccRCC) is still limited. Based on microRNA microarray analyses from normal and cancerous samples of ccRCC specimens and from bone metastases of ccRCC patients, we identified a set of 57 differentially expressed microRNAs between these three sample groups of ccRCC. A selected panel of 33 miRNAs was subsequently validated by RT-qPCR on total 57 samples. Then, 30 of the 33 examined miRNAs were confirmed to be deregulated. A stepwise down-regulation of miRNA expression from normal, over primary tumor to metastatic tissue samples, was found to be typical. A total of 23 miRNAs (miR-10b/-19a/-19b/-20a/-29a/-29b/-29c/-100/-101/-126/-127/-130/-141/-143/-145/-148a/-192/-194/-200c/-210/-215/-370/-514) were down-regulated in metastatic tissue samples compared with normal tissue. This down-regulated expression in metastatic tissue in comparison with primary tumor tissue was also present in 21 miRNAs. In cell culture experiments with 5-aza-2'-deoxycytidine and trichostatin A, epigenetic modifications were shown as one reason of this down-regulation. The altered miRNA profiles, comprising newly identified metastasis-associated miRNAs, termed metastamir and the predicted miRNA-target interactions together with the significant correlations of miRNAs that were either lost or newly appeared in the studied sample groups, afford a solid basis for further functional analyses of individual miRNAs in RCC metastatic progression.

Value of prostate specific antigen density and percent free prostate specific antigen for prostate cancer prognosis.

PURPOSE: Limited data exist on the relationship of percent free prostate specific antigen and prostate specific antigen density with prostate cancer prognosis. Therefore, we compared percent free prostate specific antigen and prostate specific antigen density with prostate specific antigen, Gleason sum and stage to predict prostate cancer prognosis in a large cohort using a single prostate specific antigen and free prostate specific antigen assay. MATERIALS AND METHODS: Between 1999 and 2007 a total of 1,656 patients with prostate cancer underwent laparoscopic radical prostatectomy at the Charité Berlin. There were 322 patients excluded from analysis for a variety of reasons. The final 1,334 patients had prostate specific antigen, free prostate specific antigen, prostate volume and complete pathological analysis available. RESULTS: Median followup was 60.3 months (range 0.2 to 135). Median age (63 years, range 43 to 75) did not differ between the 1,092 patients without and the 242 with biochemical recurrence (p = 0.956), but prostate volume, prostate specific antigen and percent free prostate specific antigen differed significantly (p <0.0001). While prostate specific antigen and prostate specific antigen density increased significantly in patients with Gleason less than 7, 7 and greater than 7 tumors, percent free prostate specific antigen decreased significantly (p <0.0001). Prostate specific antigen, percent free prostate specific antigen and prostate specific antigen density differed significantly between pT2 and pT3 tumors, and between patients with vs without positive surgical margins. On univariate analysis Gleason sum, pathological stage, positive surgical margin, total prostate specific antigen, percent free prostate specific antigen and prostate specific antigen density were predictors of biochemical recurrence-free survival. Multivariate Cox regression analysis identified Gleason sum, pathological stage, positive surgical margin and prostate specific antigen density as independent predictors of biochemical recurrence-free survival, while percent free prostate specific antigen and total prostate specific antigen failed to be significant. CONCLUSIONS: Few models for prostate cancer prognosis include prostate specific antigen density. There is substantial value in prostate specific antigen density but not in percent free prostate specific antigen for improving prostate cancer prognosis and biochemical recurrence prediction.

Reference miRNAs for miRNAome analysis of urothelial carcinomas.

BACKGROUND/OBJECTIVE: Reverse transcription quantitative real-time PCR (RT-qPCR) is widely used in microRNA (miRNA) expression studies on cancer. To compensate for the analytical variability produced by the multiple steps of the method, relative quantification of the measured miRNAs is required, which is based on normalization to endogenous reference genes. No study has been performed so far on reference miRNAs for normalization of miRNA expression in urothelial carcinoma. The aim of this study was to identify suitable reference miRNAs for miRNA expression studies by RT-qPCR in urothelial carcinoma. METHODS: Candidate reference miRNAs were selected from 24 urothelial carcinoma and normal bladder tissue samples by miRNA microarrays. The usefulness of these candidate reference miRNAs together with the commonly for normalization purposes used small nuclear RNAs RNU6B, RNU48, and Z30 were thereafter validated by RT-qPCR in 58 tissue samples and analyzed by the algorithms geNorm, NormFinder, and BestKeeper. PRINCIPAL FINDINGS: Based on the miRNA microarray data, a total of 16 miRNAs were identified as putative reference genes. After validation by RT-qPCR, miR-101, miR-125a-5p, miR-148b, miR-151-5p, miR-181a, miR-181b, miR-29c, miR-324-3p, miR-424, miR-874, RNU6B, RNU48, and Z30 were used for geNorm, NormFinder, and BestKeeper analyses that gave different combinations of recommended reference genes for normalization. CONCLUSIONS: The present study provided the first systematic analysis for identifying suitable reference miRNAs for miRNA expression studies of urothelial carcinoma by RT-qPCR. Different combinations of reference genes resulted in reliable expression data for both strongly and less strongly altered miRNAs. Notably, RNU6B, which is the most frequently used reference gene for miRNA studies, gave inaccurate normalization. The combination of four (miR-101, miR-125a-5p, miR-148b, and miR-151-5p) or three (miR-148b, miR-181b, and miR-874,) reference miRNAs is recommended for normalization.

Effects of systemic versus local administration of corticosteroids on mucosal tolerance.

Respiratory exposure to allergen induces T cell tolerance and protection against the development of airway hyperactivity in animal models of asthma. Whereas systemic administration of dexamethasone during the delivery of respiratory Ag has been suggested to prevent the development of mucosal tolerance, the effects of local administration of corticosteroids, first-line treatment for patients with bronchial asthma, on mucosal tolerance remain unknown. To analyze the effects of systemic versus local administration of different types of corticosteroids on the development of mucosal tolerance, mice were exposed to respiratory allergen to induce mucosal tolerance with or without systemic or intranasal application of different doses of dexamethasone or prednisolone. After the induction of mucosal tolerance, proliferation of T cells was inhibited in tolerized mice, whereas systemic applications of corticosteroids restored T cell proliferation and secretion of Th2 cytokines. In contrast, inhaled corticosteroids showed no effect on both T cell proliferation and cytokine secretion. In addition, mice systemically treated with corticosteroids showed an increased airway hyperactivity with a significant lung inflammation, but also an increased T effector cells/regulatory T cells ratio in the second lymphoid organs when compared with mice that receive corticosteroids by inhalation. These results demonstrate that local administration of corticosteroids has no effect on the development of immune tolerance in contrast to systemically applied corticosteroids. Furthermore, although different concentrations of corticosteroids are administered to patients, our results demonstrated that the route of administration rather than the doses affects the effect of corticosteroids on respiratory tolerance induction. Considering the broad application of corticosteroids in patients with allergic disease and asthma, the route of administration of steroid substances seems crucial in terms of treatment and potential side effects. These findings may help elucidate the apparently contradicting results of corticosteroid treatment in allergic diseases.

Between-method differences in prostate-specific antigen assays affect prostate cancer risk prediction by nomograms.

BACKGROUND: To date, no published nomogram for prostate cancer (PCa) risk prediction has considered the between-method differences associated with estimating concentrations of prostate-specific antigen (PSA). METHODS: Total PSA (tPSA) and free PSA were measured in 780 biopsy-referred men with 5 different assays. These data, together with other clinical parameters, were applied to 5 published nomograms that are used for PCa detection. Discrimination and calibration criteria were used to characterize the accuracy of the nomogram models under these conditions. RESULTS: PCa was found in 455 men (58.3%), and 325 men had no evidence of malignancy. Median tPSA concentrations ranged from 5.5 µg/L to 7.04 µg/L, whereas the median percentage of free PSA ranged from 10.6% to 16.4%. Both the calibration and discrimination of the nomograms varied significantly across different types of PSA assays. Median PCa probabilities, which indicate PCa risk, ranged from 0.59 to 0.76 when different PSA assays were used within the same nomogram. On the other hand, various nomograms produced different PCa probabilities when the same PSA assay was used. Although the ROC curves had comparable areas under the ROC curve, considerable differences were observed among the 5 assays when the sensitivities and specificities at various PCa probability cutoffs were analyzed. CONCLUSIONS: The accuracy of the PCa probabilities predicted according to different nomograms is limited by the lack of agreement between the different PSA assays. This difference between methods may lead to unacceptable variation in PCa risk prediction. A more cautious application of nomograms is recommended.

DNA vaccination: using the patient's immune system to overcome cancer.

Cancer is one of the most challenging diseases of today. Optimization of standard treatment protocols consisting of the main columns of chemo- and radiotherapy followed or preceded by surgical intervention is often limited by toxic side effects and induction of concomitant malignancies and/or development of resistant mechanisms. This requires the development of therapeutic strategies which are as effective as standard therapies but permit the patients a life without severe negative side effects. Along this line, the development of immunotherapy in general and the innovative concept of DNA vaccination in particular may provide a venue to achieve this goal. Using the patient's own immune system by activation of humoral and cellular immune responses to target the cancer cells has shown first promising results in clinical trials and may allow reduced toxicity standard therapy regimen in the future. The main challenge of this concept is to transfer the plethora of convincing preclinical and early clinical results to an effective treatment of patients.

Reduced serum selenoprotein P concentrations in German prostate cancer patients.

Selenium (Se) is essentially needed for the biosynthesis of selenoproteins. Low Se intake causes reduced selenoprotein biosynthesis and constitutes a risk factor for tumorigenesis. Accordingly, some Se supplementation trials have proven effective to reduce prostate cancer risk, especially in poorly supplied individuals. Because Se metabolism is controlled by selenoprotein P (SEPP), we have tested whether circulating SEPP concentrations correlate to prostate cancer stage and grade. A total of 190 men with prostate cancer (n = 90) and "no evidence of malignancy" (NEM; n = 100) histologically confirmed by prostate biopsy were retrospectively analyzed for established tumor markers and for their Se and SEPP status. Prostate specific antigen (PSA), free PSA, total Se, and SEPP concentrations were determined from serum samples and compared with clinicopathologic parameters. The diagnostic performance was analyzed with receiver operating characteristic curves. Median Se and SEPP concentrations differed significantly (P < 0.001) between the groups. Median serum Se concentrations in the 25th to 75th percentile were 95.9 microg/L (82-117.9) in NEM patients and 81.4 microg/L (67.9-98.4) in prostate cancer patients. Corresponding serum SEPP concentrations were 3.4 mg/L (1.9-5.6) in NEM and 2.9 mg/L (1.1-5.5) in prostate cancer patients. The area under the curve (AUC) of a marker combination with age, PSA, and percent free PSA (%fPSA) in combination with the SEPP concentration, yielded the highest diagnostic value (AUC 0.80) compared with the marker combination without SEPP (AUC 0.77) or %fPSA (AUC 0.76). We conclude that decreased SEPP concentration in serum might represent an additional valuable marker for prostate cancer diagnostics.

The FUSE binding proteins FBP1 and FBP3 are potential c-myc regulators in renal, but not in prostate and bladder cancer.

BACKGROUND: The three far-upstream element (FUSE) binding proteins (FBP1, FBP2, and FBP3) belong to an ancient family of single-stranded DNA binding proteins which are required for proper regulation of the c-myc proto-oncogene. Whereas it is known that c-myc alterations play a completely different role in various carcinomas of the urogenital tract, the relevance of FBPs is unclear. METHODS: FBP1, FBP3 and c-myc expression was studied in 105 renal cell, 95 prostate and 112 urinary bladder carcinomas by immunohistochemistry using tissue microarrays. RESULTS: High rates of FBP1 and FBP3 expression were observed in all cancer types. There was a concomitant up-regulation of FBP1 and FBP3 in renal cell and prostate carcinomas (p < 0.001 both). C-myc expression was detectable in 21% of prostate, 30% of renal and 34% of urothelial carcinomas. Interestingly, strong FBP1 and FBP3 expression was associated with c-myc up-regulation in clear cell renal cell carcinomas (p < 0.001 and 0.09 resp.), but not in bladder or prostate cancer. CONCLUSION: The correlation between FBP1/FBP3, c-myc and high proliferation rate in renal cell carcinoma provides strong in vivo support for the suggested role of FBP1 and FBP3 as activators of c-myc. The frequent up-regulation of FBP1 and FBP3 in urothelial and prostate carcinoma suggests that FBPs also have an important function in gene regulation of these tumors.

Artificial neural network (ANN) velocity better identifies benign prostatic hyperplasia but not prostate cancer compared with PSA velocity.

BACKGROUND: To validate an artificial neural network (ANN) based on the combination of PSA velocity (PSAV) with a %free PSA-based ANN to enhance the discrimination between prostate cancer (PCa) and benign prostate hyperplasia (BPH). METHODS: The study comprised 199 patients with PCa (n = 49) or BPH (n = 150) with at least three PSA estimations and a minimum of three months intervals between the measurements. Patients were classified into three categories according to PSAV and ANN velocity (ANNV) calculated with the %free based ANN "ProstataClass". Group 1 includes the increasing PSA and ANN values, Group 2 the stable values, and Group 3 the decreasing values. RESULTS: 71% of PCa patients typically have an increasing PSAV. In comparison, the ANNV only shows this in 45% of all PCa patients. However, BPH patients benefit from ANNV since the stable values are significantly more (83% vs. 65%) and increasing values are less frequently (11% vs. 21%) if the ANNV is used instead of the PSAV. CONCLUSION: PSAV has only limited usefulness for the detection of PCa with only 71% increasing PSA values, while 29% of all PCa do not have the typical PSAV. The ANNV cannot improve the PCa detection rate but may save 11-17% of unnecessary prostate biopsies in known BPH patients.

An artificial neural network for five different assay systems of prostate-specific antigen in prostate cancer diagnostics.

OBJECTIVE: To compare separate prostate-specific antigen (PSA) assay-specific artificial neural networks (ANN) for discrimination between patients with prostate cancer (PCa) and no evidence of malignancy (NEM). PATIENTS AND METHODS: In 780 patients (455 with PCa, 325 with NEM) we measured total PSA (tPSA) and free PSA (fPSA) with five different assays: from Abbott (AxSYM), Beckman Coulter (Access), DPC (Immulite 2000), and Roche (Elecsys 2010) and with tPSA and complexed PSA (cPSA) assays from Bayer (ADVIA Centaur). ANN models were developed with five input factors: tPSA, percentage free/total PSA (%fPSA), age, prostate volume and digital rectal examination status for each assay separately to examine two tPSA ranges of 0-10 and 10-27 ng/mL. RESULTS: Compared with the median tPSA concentrations (range from 4.9 [Bayer] to 6.11 ng/mL [DPC]) and especially the median %fPSA values (range from 11.2 [DPC] to 17.4%[Abbott], for tPSA 0-10 ng/mL), the areas under the receiver operating characteristic curves (AUC) for all calculated ANN models did not significantly differ from each other. The AUC were: 0.894 (Abbott), 0.89 (Bayer), 0.895 (Beckman), 0.882 (DPC) and 0.892 (Roche). At 95% sensitivity the specificities were without significant differences, whereas the individual absolute ANN outputs differed markedly. CONCLUSIONS: Despite only slight differences, PSA assay-specific ANN models should be used to optimize the ANN outcome to reduce the number of unnecessary prostate biopsies. We further developed the ANN named 'ProstataClass' to provide clinicians with an easy to use tool in making their decision about follow-up testing.

Comparison of two different artificial neural networks for prostate biopsy indication in two different patient populations.

OBJECTIVES: Different artificial neural networks (ANNs) using total prostate-specific antigen (PSA) and percentage of free PSA (%fPSA) have been introduced to enhance the specificity of prostate cancer detection. The applicability of independently trained ANN and logistic regression (LR) models to different populations regarding the composition (screening versus referred) and different PSA assays has not yet been tested. METHODS: Two ANN and LR models using PSA (range 4 to 10 ng/mL), %fPSA, prostate volume, digital rectal examination findings, and patient age were tested. A multilayer perceptron network (MLP) was trained on 656 screening participants (Prostatus PSA assay) and another ANN (Immulite-based ANN [iANN]) was constructed on 606 multicentric urologically referred men. These and other assay-adapted ANN models, including one new iANN-based ANN, were used. RESULTS: The areas under the curve for the iANN (0.736) and MLP (0.745) were equal but showed no differences to %fPSA (0.725) in the Finnish group. Only the new iANN-based ANN reached a significant larger area under the curve (0.77). At 95% sensitivity, the specificities of MLP (33%) and the new iANN-based ANN (34%) were significantly better than the iANN (23%) and %fPSA (19%). Reverse methodology using the MLP model on the referred patients revealed, in contrast, a significant improvement in the areas under the curve for iANN and MLP (each 0.83) compared with %fPSA (0.70). At 90% and 95% sensitivity, the specificities of all LR and ANN models were significantly greater than those for %fPSA. CONCLUSIONS: The ANNs based on different PSA assays and populations were mostly comparable, but the clearly different patient composition also allowed with assay adaptation no unbiased ANN application to the other cohort. Thus, the use of ANNs in other populations than originally built is possible, but has limitations.

Serum (-5, -7) proPSA for distinguishing stage and grade of prostate cancer.

BACKGROUND: ProPSA has been suggested for the detection of preferentially aggressive prostate cancer (PCa). We report on the use of proPSA and free PSA to enhance preoperative staging and grading. PATIENTS AND METHODS: Serum samples from 376 PCa patients within the PSA range 1-25 microg/l who underwent radical prostatectomy were analysed for PSA, free PSA (fPSA) and (-5, -7) proPSA. RESULTS: ProPSA was only significantly different between pT2 and pT3 PCa (p = 0.02) in the subgroup of patients with % fPSA < 10%. The ratio proPSA/% fPSA differed between G2 and G3 (p = 0.004), Gleason < 7 and Gleason > or =7 (p = 0.001), and pT2 and pT3 tumors (p < 0.0001) at PSA 1-25 microg/l. However, % fPSA improved differentiation only between Gleason < 7 and Gleason > or = 7 tumors, not between pT2 and pT3 or G2 and G3 tumors. CONCLUSION: ProPSA as a single parameter did not improve the detection of non-organ confined or aggressive PCa whereas proPSA/% fPSA further improved staging and grading within all analysed PSA ranges.

Assay-specific artificial neural networks for five different PSA assays and populations with PSA 2-10 ng/ml in 4,480 men.

Use of percent free PSA (%fPSA) and artificial neural networks (ANNs) can eliminate unnecessary prostate biopsies. In a total of 4,480 patients from five centers with PSA concentrations in the range of 2-10 ng/ml an IMMULITE PSA-based ANN (iANN) was compared with other PSA assay-adapted ANNs (nANNs) to investigate the impact of different PSA assays. ANN data were generated with PSA, fPSA (assays from Abbott, Beckman, DPC, Roche or Wallac), age, prostate volume, and DRE status. In 15 different ROC analyses, the area under the curve (AUC) in the PSA ranges 2-4, 2-10, and 4-10 ng/ml for the nANN was always significantly larger than the AUC for %fPSA or PSA. The nANN and logistic regression models mostly also performed better than the iANN. Therefore, for each patient population, PSA assay-specific ANNs should be used to optimize the ANN outcome in order to reduce the number of unnecessary biopsies.

Different prostate-specific antigen assays give different results on the same blood sample: an obstacle to recommending uniform limits for prostate biopsies.

OBJECTIVE: To show the effect of different results for total prostate specific antigen (tPSA) and percentage free/total PSA (%fPSA) obtained with different assays for differentiating between benign and malignant prostate diseases. PATIENTS AND METHODS: Data were used for tPSA and fPSA levels from 596 patients with prostate cancer (314) or no evidence of cancer (282) within the PSA range 0.5-10 ng/mL, analysed with assays from Abbott (AxSYM), Beckman Coulter (Access), DPC (Immulite 2000), and Roche (Elecsys 2010), and with tPSA and complexed PSA (cPSA) assays from Bayer (ADVIA Centaur), as already reported. Receiver operating characteristics (ROC), specificities at assay-dependent and fixed thresholds, and the percentages of correct classification rates of patients were calculated. RESULTS: Whereas the areas under the ROC curves were no different among all tPSA assays, the assay-specific thresholds at 90% sensitivity were 2.5-3.1 ng/mL. When using fixed 2.5 or 4 ng/mL tPSA thresholds there was a wide sensitivity range, with significant differences among almost all assays, resulting in significantly different classification rates of patients. These differences were even larger when using fixed %fPSA thresholds. CONCLUSIONS: The current situation of differences among PSA values measured with different assays do not allow the recommendation of uniform PSA limits as biopsy criteria. For that purpose, better harmonization of PSA values between the different PSA test systems must be realized.

Improved prostate cancer detection with a human kallikrein 11 and percentage free PSA-based artificial neural network.

Human kallikrein 11 (hK11) was evaluated in a percentage free PSA-based artificial neural network (ANN) to reduce unnecessary prostate biopsies. Serum samples from 357 patients with (n=132) and without (n=225) prostate cancer (PCa) were analyzed and ANN models were constructed and compared to all parameters. The discriminatory power of hK11 was lower than that of PSA, but receiver operator characteristic (ROC) analyses demonstrated significantly larger areas under the curves for the ANN compared to all other parameters. ANNs with hK11 may lead to a further reduction in unnecessary prostate biopsies, especially when analyzing patients with less than 15% free PSA.

A (-5, -7) proPSA based artificial neural network to detect prostate cancer.

OBJECTIVE: The pro-forms of prostate specific antigen (-2,-5,-7 proPSA) and also %free PSA based artificial neural networks (ANN) have been suggested to enhance the discrimination between prostate cancer (PCa) and no evidence of malignancy (NEM). This study reports on the combined use of proPSA within a %free PSA based ANN to enhance specificity of PCa. METHODS: Serum samples from 898 patients with PCa (n=384) or NEM (n=514) within the PSA range 1-10 microg/l were analyzed for PSA, free PSA and (-5,-7) proPSA (Roche assays). Patient data from two centers - taken first from the Swiss site of the ERSPC (Aarau) and from a referral population (Berlin) have been analyzed. Leave-one-out ANN models with the variables PSA, %fPSA, proPSA, prostate volume and status of digital rectal examination (DRE) were constructed and compared by receiver-operating characteristic (ROC) curve analysis. RESULTS: (-5,-7) proPSA was only significantly different between NEM and PCa in the PSA range 4-10 microg/l. Within the PSA range 4-10 microg/l (Berlin group) the ANN including only the two variables %fPSA and proPSA could reach the same performance like the conventional ANN with PSA, %fPSA, age, prostate volume and DRE (both AUCs: 0.84) However, at 95% sensitivity all ANN could not improve specificity compared to %fPSA. CONCLUSIONS: ProPSA as single parameter did not improve specificity over %fPSA whereas proPSA and %fPSA within an ANN in the PSA range 4-10 microg/l substituted prostate volume and DRE. At 95% sensitivity only ANN with prostate volume and DRE perform significantly better than %fPSA.

The ubiquitin-specific protease USP10 modulates androgen receptor function.

The role of the ubiquitin/proteasome system in degrading nuclear hormone receptors and regulating their transcriptional function has emerged in the last few years. We identified the ubiquitin-specific protease USP10 as part of DNA-bound androgen receptor (AR) complexes purified from nuclear extracts of PC-3 cells stably expressing the AR. The interaction between USP10 and the AR was confirmed by GST pull-down assays. Fluorescence microscopy documented that USP10 was localised in the nucleus and the cytoplasm. Cell-based transactivation assays in PC-3/AR cells revealed that overexpression of wild-type USP10, but not of an enzymatically inactive form, stimulated AR activity mediated by reporter constructs harbouring selective androgen response elements (AREs), non-selective steroid response elements (SREs) or the mouse mammary tumour virus (MMTV) promoter. Conversely, USP10 expression knock-down by siRNAs impaired the MMTV response to androgen. In summary, the data indicate that USP10 is a new cofactor that binds to the AR and stimulates the androgen response of target promoters. This finding underlines the role of the ubiquitin/proteasome system in modulating the AR function.

The role of DNA response elements as allosteric modulators of steroid receptor function.

Steroid receptors are ligand-activated transcription factors which control the expression of their target genes by binding to specific DNA elements. Consensus response elements have been delineated for the glucocorticoid, androgen, progesterone and mineralocorticoid receptors on one hand (steroid response element, SRE) and for the estrogen receptor on the other hand (estrogen response element, ERE). Small variations in these sequences not only affect the binding but may also have a dramatic impact on the transcriptional activity of steroid receptors. It has now become obvious that DNA response elements do not merely tether regulatory proteins to control regions of target genes but may additionally impart conformational changes onto the DNA-binding domain as well as to neighbouring domains of steroid receptors. This in turn will create unique platforms for selective recruitment of cofactors and possibly for induction of modifications in local chromatin architecture. An additional level of complexity is added by the frequent presence of multiple response elements in gene promoter regions. The allosteric effects of DNA response elements on steroid receptors may be essential for differential gene expression and this offers interesting perspectives for the identification of selective modulators.