Expression of prostatic acid phosphatase (PSAP) in transurethral resection specimens of the prostate is predictive of histopathologic tumor stage in subsequent radical prostatectomies.
ABSTRACT Clinical management of incidental prostate cancer (IPC) remains challenging since its clinical course cannot be predicted by conventional histopathology. Aiming to define predictive factors in IPC, we correlated the immunohistochemically detected expression of prostate-specific antigen (PSA), prostatic acid phosphatase (PSAP), alpha-methylacyl-CoA racemase (AMACR, p504s), and androgen receptor in transurethral resection specimens with Gleason scores and histologic staging on the corresponding radicals in a cohort of 54 patients (mean age, 65.9 years; range, 49-80 years). PSAP expression showed a significant correlation with tumor staging (rho = -0.37; p = 0.02) but not with Gleason scores (rho = -0.06; p = 0.69). K-statistics revealed a highly significant moderate interobserver agreement concerning the evaluation of PSAP staining (K = 0.47; p < 0.001). In contrast, the other markers assessed failed to correlate with conventional histopathology. Therefore, PSAP might be predictive of tumor stage in IPC and represent a valuable adjunct for clinical decisions in terms of individual therapeutic management.
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ABSTRACT: Prostate cancer (PCa) is the most common cancer in men and the second most common cause of cancer-related death in men. In recent years, novel therapeutic options for PCa have been developed and studied extensively in clinical trials. Sipuleucel-T is the first cell-based immunotherapeutic vaccine for treatment of cancer. This vaccine consists of autologous mononuclear cells stimulated and loaded with an immunostimulatory fusion protein containing the prostate tumor antigen prostate acid posphatase. The choice of antigen might be key for the efficiency of cell-based immunotherapy. Depending on the treatment strategy, target antigens should be immunogenic, abundantly expressed by tumor cells, and preferably functionally important for the tumor to prevent loss of antigen expression. Autoimmune responses have been reported against several antigens expressed in the prostate, indicating that PCa is a suitable target for immunotherapy. In this review, we will discuss PCa antigens that exhibit immunogenic features and/or have been targeted in immunotherapeutic settings with promising results, and we highlight the hurdles and opportunities for cancer immunotherapy.Frontiers in Immunology 01/2014; 5:191.
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ABSTRACT: Recent data showed that prostate stem cell antigen (PSCA) mRNA expression is predictive of the subsequent cancer in BPH patients treated with TURP. This study was to determine whether PSCA mRNA expression in preoperatively negative biopsies identified the presence of incidental prostate cancer (IPCa) on TURP tissues analysis. PSCA in situ hybridization was performed in preoperatively negative prostatic biopsies taken from 592 enrolled BPH patients. Predictive performance of PSCA mRNA for IPCa was evaluated by the Cox proportional hazards models. PSCA mRNA positivity in negative biopsy specimens was detected in 84 (14.2%) of 592 men. Of those 84 patients, 57 were histopathologically identified as having PCa on their TURP tissues. None of the rest 508 men with negative PSCA mRNA expression were diagnosed with IPCa. Spearman's rank correlation coefficient showed that PSCA mRNA expression levels were correlated significantly and positively with Gleason score (r = 0.80, P < 0.001) and clinical stage (r = 0.86, P < 0.001). A multivariate Cox model demonstrated that only PSCA mRNA positivity was predictive of the IPCa presence on TURP (HR = 4.04; 95% CI: 2.12-5.42; P < 0.001), with the concordance index of 0.878. PSCA mRNA positivity in negative biopsies is a promising marker for the presence of IPCa in BPH patients.Journal of Surgical Oncology 06/2011; 104(6):672-8. · 2.64 Impact Factor
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ABSTRACT: Prostate cancer has heterogeneous characteristics. For that reason, even if tumors appear histologically similar to each other, there are many cases in which they are actually different, based on their gene expression levels. A single tumor may have multiple expression levels with both high-risk cancer genes and low-risk cancer genes. We can produce more useful models for stratifying prostate cancers into high-risk cancer and low-risk cancer categories by considering the range in each class through inner-class clustering. In this paper, we attempt to classify cancers into high-risk (aggressive) prostate cancer and low-risk (non-aggressive) prostate cancer using ICP (Inner-class Clustering and Prediction). Our model classified more efficiently than the models of the algorithms used for comparison. After discovering a number of genes linked to prostate cancer from the gene pairs used in our classification, we discovered that the proposed method can be used to find new unknown genes and gene pairs which distinguish between high-risk cancer and low-risk cancer.Computers in biology and medicine 10/2013; 43(10):1363-73. · 1.27 Impact Factor