BACKGROUND We compared urinary prostate cancer antigen 3 (PCA3), transmembrane protease, serine 2 (TMPRSS2):v-ets erythroblastosis virus E26 oncogene homolog (avian) (ERG) gene fusion (T2:ERG), and the serum [−2]proprostate-specific antigen ([−2]proPSA)-based prostate health index (Phi) for predicting biopsy outcome. METHODS Serum samples and first-catch urine samples were collected after digital rectal examination (DRE) from consented outpatients with PSA 0.5–20 μg/L who were scheduled for prostate biopsy. The PCA3 score (PROGENSA PCA3, Hologic Gen-Probe) and T2:ERG score (Hologic Gen-Probe) were determined. Measurements of serum PSA, free PSA, and [−2]proPSA (Beckman Coulter) were performed, and the percentages of free PSA (%fPSA) and Phi ([−2]proPSA/fPSA × √PSA) were determined. RESULTS Of 246 enrolled men, prostate cancer (PCa) was diagnosed in 110 (45%) and there was no evidence of malignancy (NEM) in 136 (55%). A first set of biopsies was performed in 136 (55%) of all men, and 110 (45%) had ≥1 repeat biopsies. PCA3, Phi, and T2:ERG differed significantly between men with PCa and NEM, and these markers showed the largest areas under the ROC curve (AUCs) (0.74, 0.68, and 0.63, respectively). PCA3 had the largest AUC of all parameters, albeit not statistically different from Phi. Phi showed somewhat lower specificities than PCA3 at 90% sensitivity. Combination of both markers enhanced diagnostic power with modest AUC gains of 0.01–0.04. Although PCA3 had the highest AUC in the repeat-biopsy cohort, the highest AUC for Phi was observed in DRE-negative patients with PSA in the 2–10 μg/L range. CONCLUSIONS PCA3 and Phi were superior to the other evaluated parameters but their combination gave only moderate enhancements in diagnostic accuracy for PCa at first or repeat prostate biopsy.

Artificial neural networks (ANNs) are mathematical models that are based on biological neural networks and are composed of interconnected groups of artificial neurons. ANNs are used to map and predict outcomes in complex relationships between given 'inputs' and sought-after 'outputs' and can also be used find patterns in datasets. In medicine, ANN applications have been used in cancer diagnosis, staging and recurrence prediction since the mid-1990s, when an enormous effort was initiated, especially in prostate cancer detection. Modern ANNs can incorporate new biomarkers and imaging data to improve their predictive power and can offer a number of advantages as clinical decision making tools, such as easy handling of distribution-free input parameters. Most importantly, ANNs consider nonlinear relationships among input data that cannot always be recognized by conventional analyses. In the future, complex medical diagnostic and treatment decisions will be increasingly based on ANNs and other multivariate models.

Our results show that high plasma OPN levels are associated with distant metastases and poor survival in RCC patients. The use of OPN as potential marker to monitor new treatment strategies in patients with advanced RCC should be evaluated in prospective studies.

In eucaryotic cells signal sequences of secretory and membrane proteins are cleaved by the signal peptidase complex during their transport into the lumen of the endoplasmic reticulum. The signal peptidase complex in yeast consists of four subunits. To date, three of these subunits have been functionally characterized. One of them, the Sec11p, is essential for viability of yeast cells. It shows significant homology to the mammalian SPC18 and SPC21 as well as to bacterial leader peptidases. Two other subunits, Spc1p and Spc2p, have been shown to be homologous to mammalian SPC12 and SPC25, respectively, and are not essential for protein translocation or signal peptide cleavage.We have purified and analyzed the fourth subunit of yeast signal peptidase, Spc3p. The protein is essential for viability of yeast cells. Depletion of SPC3 leads to accumulation of precursors of secretory proteins in vivo and to the loss of the signal peptidase activity in vitro. Therefore, in contrast to the bacterial leader peptidases, yeast signal peptidase requires a second subunit for its function.

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