Is the Post-Radical Prostatectomy Gleason Score a Valid Predictor of Mortality after Neoadjuvant Hormonal Treatment?

Purpose: To evaluate the validity of the Gleason score after neoadjuvant hormonal treatment as predictor of diseasespecific mortality after radical prostatectomy. Patients and Methods: A total of 2,880 patients with a complete data set and a mean follow-up of 10.3 years were studied; 425 of them (15%) had a history of hormonal treatment prior to surgery. The cumulative incidence of deaths from prostate cancer was determined by univariate and multivariate competing risk analysis. Cox proportional hazard models for competing risks were used to study combined effects of the variables on prostate cancer-specific mortality. Results: A higher portion of specimens with a history of neoadjuvant hormonal treatment were assigned Gleason scores of 8–10 (28 vs. 17%, p < 0.0001). The mortality curves in the Gleason score strata <8 vs. 8–10 were at large congruent in patients with and without neoadjuvant hormonal treatment. In patients with neoadjuvant hormonal treatment, a Gleason score of 8–10 was an independent predictor of prostate cancer-specific mortality; the hazard ratio was, however, somewhat lower than in patients without neoadjuvant hormonal treatment. Conclusion: This study suggests that the prognostic value of the post-radical prostatectomy Gleason score is not meaningfully jeopardized by heterogeneous neoadjuvant hormonal treatment in a routine clinical setting

Evaluation of Transperineal Magnetic Resonance Imaging/Ultrasound-Fusion Biopsy Compared to Transrectal Systematic Biopsy in the Prediction of Tumour Aggressiveness in Patients with Previously Negative Biopsy

Objectives: We compared the transperineal MRI/ultrasoundfusion biopsy (fusPbx) to transrectal systematic biopsy (sys-Pbx) in patients with previously negative biopsy and investigated the prediction of tumour aggressiveness with regard to radical prostatectomy (RP) specimen. Material and Methods: A total of 710 patients underwent multiparametric magnetic resonance imaging (mpMRI), which was evaluated in accordance with Prostate Imaging Reporting and Data System (PI-RADS). The maximum PI-RADS (maxPI-RADS) was defined as the highest PI-RADS of all lesions detected in mpMRI. In case of proven prostate cancer (PCa) and performed RP, tumour grading of the biopsy specimen was compared to that of the RP. Significant PCa (csPCa) was defined according to Epstein criteria. Results: Overall, scPCa was detected in 40% of patients. The detection rate of scPCa was 33% for fusPbx and 25% for sysPbx alone (p < 0.005). Patients with a maxPI-RADS ≥3 and a prostate specific antigen (PSA)-density ≥0.2 ng/mL2 harboured more csPCa than those with a PSA-density < 0.2 ng/mL2 (41% [33/81] vs. 20% [48/248]; p < 0.001). Compared to the RP specimen (n = 140), the concordance of tumour grading was 48% (γ = 0.57), 36% (γ = 0.31) and 54% (γ = 0.6) in fusPbx, sysPbx and comPbx, respectively. Conclusions: The combination of fusPbx and sysPbx outperforms both biopsy modalities in patients with re-biopsy. Additionally, the PSA-density may represent a predictor for csPCa in patients with maxPI-RADS ≥3

Neuropilin-2 regulates androgen-receptor transcriptional activity in advanced prostate cancer

Aberrant transcriptional activity of androgen receptor (AR) is one of the dominant mechanisms for developing of castration-resistant prostate cancer (CRPC). Analyzing AR-transcriptional complex related to CRPC is therefore important towards understanding the mechanism of therapy-resistance. While studying its mechanism, we observed that a transmembrane protein called neuropilin-2 (NRP2) plays a contributory role in forming a novel AR-transcriptional complex containing nuclear pore proteins. Using immunogold electron microscopy, high-resolution confocal microscopy, chromatin immunoprecipitation, proteomics, and other biochemical techniques, we delineated the molecular mechanism of how a specific splice variant of NRP2 becomes sumoylated upon ligand stimulation and translocates to the inner nuclear membrane. This splice variant of NRP2 then stabilizes the complex between AR and nuclear pore proteins to promote CRPC specific gene expression. Both full-length and splice variants of AR have been identified in this specific transcriptional complex. In vitro cell line-based assays indicated that depletion of NRP2 not only destabilizes the AR-nuclear pore protein interaction but also inhibits the transcriptional activities of AR. Using an in vivo bone metastasis model, we showed that the inhibition of NRP2 led to the sensitization of CRPC cells toward established anti-AR therapies such as enzalutamide. Overall, our finding emphasize the importance of combinatorial inhibition of NRP2 and AR as an effective therapeutic strategy against treatment refractory prostate cancer

An epigenetic reprogramming strategy to re-sensitize radioresistant prostate cancer cells

Radiotherapy is a mainstay of curative prostate cancer treatment, but risks of recurrence after treatment remain significant in locally advanced disease. Given that tumor relapse can be attributed to a population of cancer stem cells (CSC) that survives radiotherapy, analysis of this cell population might illuminate tactics to personalize treatment. However, this direction remains challenging given the plastic nature of prostate cancers following treatment. We show here that irradiating prostate cancer cells stimulates a durable upregulation of stem cell markers that epigenetically reprogram these cells. In both tumorigenic and radioresistant cell populations, a phenotypic switch occurred during a course of radiotherapy that was associated with stable genetic and epigenetic changes. Specifically, we found that irradiation triggered histone H3 methylation at the promoter of the CSC marker aldehyde dehydrogenase 1A1 (ALDH1A1), stimulating its gene transcription. Inhibiting this methylation event triggered apoptosis, promoted radiosensitization, and hindered tumorigenicity of radioresistant prostate cancer cells. Overall, our results suggest that epigenetic therapies may restore the cytotoxic effects of irradiation in radioresistant CSC populations

The Role of lncRNAs TAPIR-1 and -2 as Diagnostic Markers and Potential Therapeutic Targets in Prostate Cancer

In search of new biomarkers suitable for the diagnosis and treatment of prostate cancer, genome-wide transcriptome sequencing was carried out with tissue specimens from 40 prostate cancer (PCa) and 8 benign prostate hyperplasia patients. We identified two intergenic long non-coding transcripts, located in close genomic proximity, which are highly expressed in PCa. Microarray studies on a larger cohort comprising 155 patients showed a profound diagnostic potential of these transcripts (AUC~0.94), which we designated as tumor associated prostate cancer increased lncRNA (TAPIR-1 and -2). To test their therapeutic potential, knockdown experiments with siRNA were carried out. The knockdown caused an increase in the p53/TP53 tumor suppressor protein level followed by downregulation of a large number of cell cycle- and DNA-damage repair key regulators. Furthermore, in radiation therapy resistant tumor cells, the knockdown leads to a renewed sensitization of these cells to radiation treatment. Accordingly, in a preclinical PCa xenograft model in mice, the systemic application of nanoparticles loaded with siRNA targeting TAPIR-1 significantly reduced tumor growth. These findings point to a crucial role of TAPIR-1 and -2 in PCa

High-accuracy prostate cancer pathology using deep learning

Deep learning methods can be a powerful part of digital pathology workflows, provided well-annotated training datasets are available. Tolkach and colleagues develop a deep learning model to recognize and grade prostate cancer, based on a convolution neural network and a dataset with high-quality labels at gland-level precision. Deep learning (DL) is a powerful methodology for the recognition and classification of tissue structures in digital pathology. Its performance in prostate cancer pathology is still under intensive investigation. Here we develop DL-based models for the detection of prostate cancer tissue in whole-slide images based on a large high-quality annotated training dataset and a modern state-of-the-art convolutional network architecture (NASNetLarge). The overall accuracy of our model for tumour detection in two validation cohorts is comparable to that of pathologists and reaches 97.3% in a native version and more than 98% using the suggested DL-based augmentation strategies. As a second step, we suggest a new biologically meaningful DL-based algorithm for Gleason grading of prostatic adenocarcinomas with high, human-level performance in prognostic stratification of patients when tested in several well-characterized validation cohorts. Furthermore, we determine the optimal minimal tumour size (real size of approximately 560 x 560 mu m) for robust Gleason grading representative of the whole tumour focus. Our approach is realized in the unified digital pathology pipeline, which delivers all the relevant tumour metrics for a pathology report

PSMA-PET/CT-Positive Paget Disease in a Patient with Newly Diagnosed Prostate Cancer: Imaging and Bone Biopsy Findings

A 67-year-old man diagnosed with Gleason score 4+5=9 clinically localized prostate cancer with 68Ga-labeled prostate-specific membrane antigen-targeted ligand positron emission tomography/computed tomography (PSMA-PET/CT) positive Paget bone disease is described. Immunohistochemical staining revealed weak PSMA positivity of the bone lesion supporting the hypothesis that neovasculature might explain positive PSMA-PET/CT findings in Paget disease

CircEHD2, CircNETO2 and CircEGLN3 as Diagnostic and Prognostic Biomarkers for Patients with Renal Cell Carcinoma

Background: Circular RNA (circRNA) plays an important role in the carcinogenesis of various tumors. It is assumed that circRNAs have a high tissue and tumor specificity, thus they are discussed as cancer biomarkers. The knowledge about circRNAs in clear cell renal carcinoma (ccRCC) is limited so far, and thus we studied the expression profile of seven circRNAs (circCOL5A1, circEHD2, circEDEM2, circEGNL3, circNETO2, circSCARB1, circSOD2) in a cohort of ccRCC patients. Methods: Fresh-frozen normal and cancerous tissues were prospectively collected from patients with ccRCC undergoing partial/radical nephrectomy. Total RNA was isolated from 121 ccRCC and 91 normal renal tissues, and the circRNA expression profile was determined using quantitative real-time PCR. Results: circEHD2, circENGLN3, and circNETO2 were upregulated in ccRCC compared with non-malignant renal tissue. circENGLN3 expression was highly discriminative between normal and cancerous tissue. None of the circRNAs was correlated with clinicopathological parameters. High circEHD2 and low circNETO2 levels were an independent predictor of a shortened progression-free survival, cancer-specific survival, and overall survival in patients with ccRCC undergoing nephrectomy. Conclusions: The analysis of circRNAs may provide diagnostic and prognostic information. Thus, circRNAs could help to optimize the individual treatment and ultimately improve ccRCC patients’ survival