Non-Metastatic Clear Cell Renal Cell Carcinoma Immune Cell Infiltration Heterogeneity and Prognostic Ability in Patients Following Surgery.

Predicting which patients will progress to metastatic disease after surgery for non-metastatic clear cell renal cell carcinoma (ccRCC) is difficult; however, recent data suggest that tumor immune cell infiltration could be used as a biomarker. We evaluated the quantity and type of immune cells infiltrating ccRCC tumors for associations with metastatic progression following attempted curative surgery. We quantified immune cell densities in the tumor microenvironment and validated our findings in two independent patient cohorts with multi-region sampling to investigate the impact of heterogeneity on prognostic accuracy. For non-metastatic ccRCC, increased CD8+ T cell infiltration was associated with a reduced likelihood of progression to metastatic disease. Interestingly, patients who progressed to metastatic disease also had increased percentages of exhausted CD8+ T cells. Finally, we evaluated the spatial heterogeneity of the immune infiltration and demonstrated that patients without metastatic progression had CD8+ T cells in closer proximity to ccRCC cells. These data strengthen the evidence for CD8+ T cell infiltration as a prognostic biomarker in non-metastatic ccRCC and demonstrate that multi-region sampling may be necessary to fully characterize immune infiltration within heterogeneous tumors. Tumor CD8+ T cell infiltration should be investigated as a biomarker in adjuvant systemic therapy clinical trials for high-risk non-metastatic RCC.

Shorter Ureters Lead to Fewer Strictures Following Cystectomy and Urinary Diversion.

OBJECTIVE: To identify the impact of length of distal ureteral resection on the risk of benign uretero-enteric anastomotic stricture (UEAS) formation following cystectomy and urinary diversion. METHODS: A database of patients who underwent cystectomy and urinary diversion from 2015 to 2022 was analyzed. Distal ureteral resections were sent for final pathology. The length of resected ureter was collected from pathology reports. Benign UEAS were confirmed with renal scintigraphy, antegrade nephrostogram, or endoscopic evaluation. The relationship between stricture formation and clinical parameters were assessed using T-tests, chi-square tests, and multivariable analysis. RESULTS: A total of 366 patients underwent cystectomy and urinary diversion. Of the cohort, 35 (9.5%) patients developed UEAS. Median time to stricture formation was 12.5months (IQR 4-30). Of the 711 uretero-enteric anastomoses, 40 (5.6%) ultimately formed a UEAS. Median distal ureteral resection was significantly longer among ureteral anastomoses which did not form a UEAS (2.3 cm vs 1.65 cm, P = .028). Multivariable logistic regression adjusting for surgical approach, prior radiation, ureteral side, and urinary diversion type demonstrated that longer distal ureteral resections were inversely associated with odds of UEAS formation (OR 0.73, 95% CI 0.58-0.92). Multivariable Cox regression analysis similarly showed that length of distal ureteral resection was inversely associated with time to stricture formation (HR 0.78, 95% CI 0.62-0.98). CONCLUSION: The etiology of benign UIA strictures is multifactorial. Vascular compromise is a critical hypothesis. We found that longer distal ureteral resections (and thus shorter ureters) were associated with a significantly lower risk of stricture formation in cystectomy patients.

Impact of Agent Orange Exposure on Non-muscle Invasive Bladder Cancer Outcomes.

OBJECTIVE: To explore the effect of Agent Orange (AO) exposure on bladder cancer (BCa) outcomes in patients receiving Bacillus Calmette-Guérin (BCG) for non-muscle invasive BCa (NMIBC). METHODS: We retrospectively examined the association between AO exposure in patients with NMIBC in national veterans affairs databases who were being treated with BCG. Patients were diagnosed with NMIBC from 2000 to 2010 with follow-up through 2018. Clinical, pathological, and demographic variables were compared by AO exposure. Associations of AO exposure with recurrence, progression, and cancer-specific survival were performed using Cox proportional hazard models after inverse propensity score weighting and competing risks adjustments. We also assessed the association of AO exposure on grade and stage via multivariable logistic regression models. RESULTS: A total of 7651 patients were identified of which 753 (9.8%) were exposed to AO. The median follow-up time was 130 months. The AO-exposed patients were younger (age 61 vs 71 years, P <.001), but had similar Charlson comorbidity scores and stage/grade distribution as the non-AO exposed patients. AO exposure was not associated with higher grade or stage. In our Cox multivariable analyses, AO exposure was not associated with worse recurrence (hazard ratio (HR) 0.89, 95% confidence interval (CI) 0.72-1.10, P = .29), progression (HR 1.08, 95% CI 0.86-1.36, P = .51), or cancer-specific survival (HR 1.31, 95% CI 0.92-1.87, P = .13). CONCLUSION: AO exposure was not associated with worse oncologic outcomes in patients receiving BCG for NMIBC. While this is reassuring, additional research is needed in other patient populations and disease states to determine if the effect is consistent.

Development of a multiplex assay to assess activated p300/CBP in circulating prostate tumor cells.

Reduced SIRT2 deacetylation and increased p300 acetylation activity leads to a concerted mechanism of hyperacetylation at specific histone lysine sites (H3K9, H3K14, and H3K18) in castration-resistant prostate cancer (CRPC). We examined whether circulating tumor cells (CTCs) identify patients with altered p300/CBP acetylation. CTCs were isolated from 13 advanced PC patients using Exclusion-based Sample Preparation (ESP) technology. Bound cells underwent immunofluorescent staining for histone modifying enzymes (HMEs) of interest and image capture with NIS-Elements software. Using the cBioPortal PCF/SU2C dataset, the response of CRPC to androgen receptor signaling inhibitors (ARSI) was analyzed in 50 subjects. Staining optimization and specificity revealed clear expression of acetyl-p300, acetyl-H3K18, and SIRT2 on CTCs (CK positive, CD45 negative cells). Exposure to A-485, a selective p300/CBP catalytic inhibitor, reduced p300 and H3K18 acetylation. In CRPC patients, a-p300 strongly correlated with its target acetylated H3k18 (Pearson's R = 0.61), and SIRT2 expression showed robust negative correlation with a-H3k18 (R = -0.60). A subgroup of CRPC patients (6/11; 55%) demonstrated consistent upregulation of acetylation based on these markers. To examine the clinical impact of upregulation of the CBP/p300 axis, CRPC patients with reduced deacetylase SIRT2 expression demonstrate shorter response times to ARSI therapy (5.9 vs. 12 mo; p = 0.03). A subset of CRPC patients demonstrate increased p300/CBP activity based on a novel CTC biomarker assay. With further development, this biomarker suite may be used to identify candidates for CBP/p300 acetylation inhibitors in clinical development.

Elucidating the RNA-Protein Interactomes of Target RNAs in Tissue.

RNA-protein interactions are key to many aspects of cellular homeostasis and their identification is important to understanding cellular function. Multiple strategies have been developed for the RNA-centric characterization of RNA-protein complexes. However, these studies have all been done in immortalized cell lines that do not capture the complexity of heterogeneous tissue samples. Here, we develop hybridization purification of RNA-protein complexes followed by mass spectrometry (HyPR-MS) for use in tissue samples. We isolated both polyadenylated RNA and the specific long noncoding RNA MALAT1 and characterized their protein interactomes. These results demonstrate the feasibility of HyPR-MS in tissue for the multiplexed characterization of specific RNA-protein complexes.

Updates to Advanced Prostate Cancer: AUA/SUO Guideline (2023).

PURPOSE: In 2022 the American Urological Association (AUA) requested an Update Literature Review (ULR) to incorporate new evidence generated since the 2020 publication of this guideline. The resulting 2023 Guideline Amendment addresses updated recommendations for patients with advanced prostate cancer. MATERIALS AND METHODS: The ULR addressed 23 of the original 38 guideline statements and included an abstract-level review of eligible studies published since the 2020 systematic review. Sixteen studies were selected for full text review. The current summary presents the updates made to the Guideline as a result of that new literature. RESULTS: The Advanced Prostate Cancer Panel amended evidence- and consensus-based statements based on an updated review to aid clinicians in the management of patients with advanced prostate cancer. These statements are detailed herein. CONCLUSION: This Guideline Amendment provides a framework designed to improve a clinician's ability to treat patients diagnosed with advanced prostate cancer with the most current evidence-based information. Further research and publication of high-quality clinical trials will be essential to continue to improve the quality of care for these patients.

Integrated analysis of the tumor microenvironment using a reconfigurable microfluidic cell culture platform.

The tumor microenvironment (TME) is a complex network of non-malignant cells and stroma that perform a wide array of vital roles in tumor growth, immune evasion, metastasis, and therapeutic resistance. These highly diverse roles have been shown to be critically important to the progression of cancers and have already shown potential as therapeutic targets. Therefore, there has been a tremendous push to elucidate the pathways that underlie these roles and to develop new TME-directed therapies for cancer treatment. Unfortunately, TME-focused research has been limited by a lack of translational in vitro culture platforms that can model this highly complex niche and can support the integrated analysis of cell biology and function. In the current study, we investigate whether an independently developed reconfigurable microfluidic platform, known as Stacks, can address the critical need for translational multi-cellular tumor models and integrated analytics in TME research. We present data on multi-cellular culture of primary human cells in Stacks as well as the orthogonal analysis of cellular polarization, differentiation, migration, and cytotoxicity in this reconfigurable system. These expanded capabilities of Stacks are highly relevant to the cancer research community with the potential to enhance clinical translation of pre-clinical TME studies and to yield novel biological insight into TME crosstalk, metastasis, and responses to novel drug combinations or immune therapies.

Reversible epigenetic alterations regulate class I HLA loss in prostate cancer.

Downregulation of HLA class I (HLA-I) impairs immune recognition and surveillance in prostate cancer and may underlie the ineffectiveness of checkpoint blockade. However, the molecular mechanisms regulating HLA-I loss in prostate cancer have not been fully explored. Here, we conducted a comprehensive analysis of HLA-I genomic, epigenomic and gene expression alterations in primary and metastatic human prostate cancer. Loss of HLA-I gene expression was associated with repressive chromatin states including DNA methylation, histone H3 tri-methylation at lysine 27, and reduced chromatin accessibility. Pharmacological DNA methyltransferase (DNMT) and histone deacetylase (HDAC) inhibition decreased DNA methylation and increased H3 lysine 27 acetylation and resulted in re-expression of HLA-I on the surface of tumor cells. Re-expression of HLA-I on LNCaP cells by DNMT and HDAC inhibition increased activation of co-cultured prostate specific membrane antigen (PSMA)27-38-specific CD8+ T-cells. HLA-I expression is epigenetically regulated by functionally reversible DNA methylation and chromatin modifications in human prostate cancer. Methylated HLA-I was detected in HLA-Ilow circulating tumor cells (CTCs), which may serve as a minimally invasive biomarker for identifying patients who would benefit from epigenetic targeted therapies.

Prostate cancer cells demonstrate unique metabolism and substrate adaptability acutely after androgen deprivation therapy.

BACKGROUND: Androgen deprivation therapy (ADT) has been the standard of care for advanced hormone-sensitive prostate cancer (PC), yet tumors invariably develop resistance resulting in castrate-resistant PC. The acute response of cancer cells to ADT includes apoptosis and cell death, but a large fraction remains arrested but viable. In this study, we focused on intensively characterizing the early metabolic changes that result after ADT to define potential metabolic targets for treatment. METHODS: A combination of mass spectrometry, optical metabolic imaging which noninvasively measures drug responses in cells, oxygen consumption rate, and protein expression analysis was used to characterize and block metabolic pathways over several days in multiple PC cell lines with variable hormone response status including ADT sensitive lines LNCaP and VCaP, and resistant C4-2 and DU145. RESULTS: Mass spectrometry analysis of LNCaP pre- and postexposure to ADT revealed an abundance of glycolytic intermediates after ADT. In LNCaP and VCaP, a reduction in the optical redox ratio [NAD(P)H/FAD], extracellular acidification rate, and a downregulation of key regulatory enzymes for fatty acid and glutamine utilization was acutely observed after ADT. Screening several metabolic inhibitors revealed that blocking fatty acid oxidation and synthesis reversed this stress response in the optical redox ratio seen with ADT alone in LNCaP and VCaP. In contrast, both cell lines demonstrated increased sensitivity to the glycolytic inhibitor 2-Deoxy- d-glucose(2-DG) and maintained sensitivity to electron transport chain inhibitor Malonate after ADT exposure. ADT followed by 2-DG results in synergistic cell death, a result not seen with simultaneous administration. CONCLUSIONS: Hormone-sensitive PC cells displayed altered metabolic profiles early after ADT including an overall depression in energy metabolism, induction of a quiescent/senescent phenotype, and sensitivity to selected metabolic inhibitors. Glycolytic blocking agents (e.g., 2-DG) as a sequential treatment after ADT may be promising.

Association between baseline body mass index and survival in men with metastatic hormone-sensitive prostate cancer: ECOG-ACRIN CHAARTED E3805.

BACKGROUND: E3805 (CHAARTED) is a phase 3 trial demonstrating improved survival for men with metastatic hormone-sensitive prostate cancer (mHSPC) randomized to treatment with docetaxel (D) and androgen-deprivation therapy (ADT) versus ADT alone. We assessed the association of baseline body mass index (BMI) and metformin exposure with quality of life (QOL) and prostate cancer outcomes including survival in patients enrolled in the CHAARTED study. METHODS: We performed a posthoc exploratory analysis of the CHAARTED trial of men with mHSPC randomized to treatment with ADT with or without D between 2006 and 2012. Cox proportional hazards models and Kruskal-Wallis test were used to evaluate the association between BMI with QOL and prostate cancer outcomes and between metformin exposure and survival. RESULTS: In 788 of 790 enrolled patients with prospectively recorded baseline BMI and metformin exposure status, lower BMI was not associated with survival, but was associated with high volume disease (p < 0.0001) and poorer baseline QOL on functional assessment of cancer therapy-prostate (p = 0.008). Only 68 patients had prevalent metformin exposure at baseline in the CHAARTED trial. Four groups were identified: ADT + D + metformin (n = 39); ADT + D (n = 357); ADT + metformin (n = 29); and ADT alone (n = 363). Baseline clinicopathologic characteristics were similar between groups. In this small exploratory multivariable analysis, metformin exposure was not associated with survival (hazard ratio: 1.15; 95% confidence interval: 0.81-1.63, p = 0.44). CONCLUSIONS: There was no link between baseline BMI and survival, but lower baseline BMI was associated with features of greater cancer burden and poorer QOL.

Fresh tissue procurement and preparation for multicompartment and multimodal analysis of the prostate tumor microenvironment.

BACKGROUND: Prostatic cancers include a diverse microenvironment of tumor cells, cancer-associated fibroblasts, and immune components. This tumor microenvironment (TME) is a known driving force of tumor survival after treatment, but the standard-of-care tissue freezing or fixation in pathology practice limit the use of available approaches/tools to study the TME's functionality in tumor resistance. Thus, there is a need for approaches that satisfy both clinical and laboratory endpoints for TME study. Here we present methods for clinical case identification, tissue processing, and analytical workflow that are compatible with standard histopathology while enabling molecular and functional interrogation of prostate TME components. METHODS: We first performed a small retrospective review to identify cases where submission of alternate prostate tissue slices and a parallel live tissue processing protocol complement traditional histopathology and enable viable multicompartment analysis of the TME. Then, we tested its compatibility with commonly employed methods to study the microenvironment including quantification of components both in situ and after tissue dissociation. We also evaluated tissue digestion conditions and cell isolation techniques to aid various molecular and functional endpoints. RESULTS: We identified Gleason Grade Group 3+ clinical cases where tumor volume was sufficient to allow slicing of unfixed tissue and distribution of alternating tissue slices to standard-of-care histopathology and viable multi-modal TME analyses. No single method was found that preserved cellular sub-types for all downstream readouts; instead, tissues were further divided so techniques could be catered to each endpoint. For instance, we show that incorporating the protease dispase into tissue dissociation improves viability for culture and functional analyses but hinders immune cell analysis by flow cytometry. We also found that flow activated cell sorting provides highly pure cell populations for quantitative reverse-transcription polymerase chain reaction and RNA-seq while isolation using antibody-labeled paramagnetic particles facilitated functional coculture experiments. CONCLUSIONS: The identification of candidate cases and use of these techniques enable translational research and the development of molecular and functional assays to facilitate prostate TME study without compromising standard-of-care histopathological diagnosis. This allows bridging clinical histopathology and further interrogation of the prostate TME and promises to advance our understanding of tumor biology and unveil new predictive and prognostic markers of prostate cancer progression.

MetaNetwork Enhances Biological Insights from Quantitative Proteomics Differences by Combining Clustering and Enrichment Analyses.

Interpreting proteomics data remains challenging due to the large number of proteins that are quantified by modern mass spectrometry methods. Weighted gene correlation network analysis (WGCNA) can identify groups of biologically related proteins using only protein intensity values by constructing protein correlation networks. However, WGCNA is not widespread in proteomic analyses due to challenges in implementing workflows. To facilitate the adoption of WGCNA by the proteomics field, we created MetaNetwork, an open-source, R-based application to perform sophisticated WGCNA workflows with no coding skill requirements for the end user. We demonstrate MetaNetwork's utility by employing it to identify groups of proteins associated with prostate cancer from a proteomic analysis of tumor and adjacent normal tissue samples. We found a decrease in cytoskeleton-related protein expression, a known hallmark of prostate tumors. We further identified changes in module eigenproteins indicative of dysregulation in protein translation and trafficking pathways. These results demonstrate the value of using MetaNetwork to improve the biological interpretation of quantitative proteomics experiments with 15 or more samples.

Combined mpMRI/US fusion targeted and concurrent standard biopsies in the detection of prostate cancer: a retrospective study.

In this retrospective study we compared the PCa detection rates between combined (combined MRI/US fusion targeted biopsy with concurrent standard biopsy) and standard systemic, combined and targeted (component), and targeted (component) and concurrent standard (component) biopsies. DESIGN: Two cohorts, totaling 735 cases, were selected from the University of Wisconsin Pathology archive. 390 cases (cohort 1) were combined biopsies from 2017-2020 and 345 cases (cohort 2) were part of the standard US-guided systematic biopsies from the same period. PCa was stratified into three categories: low, intermediate, and high risks. RESULTS: We found that combined biopsy was significantly better than the standard biopsy in detection of PCa (65.4% vs. 51.6%, P<0.01) and intermediate-risk PCa (18.7% vs. 10.4%, P=0.05) but only slightly better at detecting high-risk PCa (26.7% vs. 23.5%, P=0.32). Further examining the biopsy results in cohort 1, we found that combined biopsy was superior to targeted biopsy (65.4% vs. 56.9%, P=0.02) or concurrent standard biopsy (65.4% vs. 52.1%, P=0.0002) in PCa detection. Combined biopsy detected significantly more high-risk PCa than concurrent standard biopsy (26.7% vs. 17.4, P=0.002), but the difference in detecting high-risk PCa between combined and targeted biopsies was not significant (26.7% vs. 22.1%, P=0.133). Similarly, the differences in detecting PCa and high-risk PCa between targeted and concurrent standard biopsies were not significant (56.9% vs. 52.1%, P=0.172 and 22.1% vs. 17.4, P=0.133, respectively). Both targeted and concurrent standard biopsies missed PCa of each risk level. CONCLUSION: Combined MRI/US fusion targeted plus standard prostate biopsy is a superior technique for the detection of PCa and clinically significant PCa.

Live cell molecular analysis of primary prostate cancer organoids identifies persistent androgen receptor signaling.

Prostate Cancer (PC) is a disease with remarkable tumor heterogeneity that often manifests in significant intra-patient variability with regards to clinical outcomes and treatment response. Commonly available PC cell lines do not accurately reflect the complexity of this disease and there is critical need for development of new models to recapitulate the intricate hierarchy of tumor pathogenesis. In current study, we established ex vivo primary patient-derived cancer organoid (PDCO) cultures from prostatectomy specimens of patients with locally advanced PC. We then performed a comprehensive multi-parameter characterization of the cellular composition utilizing a novel approach for live-cell staining and direct imaging in the integrated microfluidic Stacks device. Using orthogonal flow cytometry analysis, we demonstrate that primary PDCOs maintain distinct subsets of epithelial cells throughout culture and that these cells conserve expression of androgen receptor (AR)-related elements. Furthermore, to confirm the tumor-origin of the PDCOs we have analyzed the expression of PC-associated epigenetic biomarkers including promoter methylation of the GSTP1, RASSF1 and APC and RARb genes by employing a novel microfluidic rare-event screening protocol. These results demonstrate that this ex vivo PDCO model recapitulates the complexity of the epithelial tumor microenvironment of multifocal PC using orthogonal analyses. Furthermore, we propose to leverage the Stacks microfluidic device as a high-throughput, translational platform to interrogate phenotypic and molecular endpoints with the capacity to incorporate a complex tumor microenvironment.

A reconfigurable microscale assay enables insights into cancer-associated fibroblast modulation of immune cell recruitment.

Innate immune cell infiltration into neoplastic tissue is the first line of defense against cancer and can play a deterministic role in tumor progression. Here, we describe a series of assays, using a reconfigurable microscale assay platform (i.e. Stacks), which allows the study of immune cell infiltration in vitro with spatiotemporal manipulations. We assembled Stacks assays to investigate tumor-monocyte interactions, re-education of activated macrophages, and neutrophil infiltration. For the first time in vitro, the Stacks infiltration assays reveal that primary tumor-associated fibroblasts from specific patients differ from that associated with the benign region of the prostate in their ability to limit neutrophil infiltration as well as facilitate monocyte adhesion and anti-inflammatory monocyte polarization. These results show that fibroblasts play a regulatory role in immune cell infiltration and that Stacks has the potential to predict individual patients' cancer-immune response.

Beta-Adrenergic Antagonists and Cancer Specific Survival in Patients With Advanced Prostate Cancer: A Veterans Administration Cohort Study.

OBJECTIVE: To interrogate the National Veterans Health Administration (VA) database to determine if beta-blocker use at time of initiation of androgen therapy deprivation (ADT) would result in improved oncological outcomes in advanced prostate cancer (PCa). METHODS: All men diagnosed with high risk PCa (PSA >20) from 2000-2008 who were on ADT ≥ 6 months were identified. Patients receiving ADT concurrently with primary radiation therapy were excluded. Pharmacy data was interrogated for all beta-blockers, but then focused on the selective beta-1 blocker metoprolol. Cox proportional hazards ratios were calculated for overall survival (OS), PCa specific survival (CSS) and skeletal related events (SREs). RESULTS: In 39,198 patients with high risk PCa on ADT, use of any beta-blocker was not associated with improvement in OS, CSS, or SREs. Further analyses focusing on metoprolol found that 10,224 (31.9%) had used metoprolol while 21,834 had no beta-blocker use. Multivariable analysis with Inverse Propensity Score Weighting, adjusted for factors including PSA, Gleason score, and duration ADT, found that utilization of metoprolol was not associated with improvement in OS (hazard ratio [HR] 0.97, P = .19), CSS (HR 0.94, P = .23) or SREs (HR 0.98, P = .79). CONCLUSION: In this large cohort, metoprolol use in conjunction with ADT in high risk PCa was not associated with improvement in OS, CSS, or risk of SRE. In contrast to a recent smaller clinical study, our data strongly suggests no cancer specific benefit to beta-blocker use in advanced PCa.

Epigenetic field alterations in non-tumor prostate tissues detect prostate cancer in urine.

Prostate cancer (PC) development involves epigenetic DNA methylation changes that occur in the tumor. However, distinct DNA methylation changes have been previously found to encompass a widespread cancer field defect involving normal prostate tissue. In the current study, we analyzed a series of DNA methylation field markers to determine if they predict the presence of PC in urine. Urine samples were collected from patients undergoing prostate biopsy with biopsy-proven PC (90), and without PC (77). From the urine pellet, methylated DNA was quantified across several previously identified CpG island regions near the caveolin 1 (CAV1), even-skipped homeobox 1 (EVX1), fibroblast growth factor 1 (FGF1), natural cytotoxicity triggering receptor 2 (NCR2) and phospholipase A and acyltransferase 3 (PLA2G16) genes using bisulfite pyrosequencing. Univariate and multivariate analyses were performed. Urine cell pellets show significant increases in methylation in four of the markers from patients with PC compared to those without PC including EVX1 12.2 vs. 7.7%, CAV1 15.7 vs. 10.36%, FGF1 12.0 vs. 7.1%, and PLA2G16 12.2 vs. 8.3% [all P<0.01]. Area under the ROC Curve (AUCs) were generated for EXV1 (0.74, Odds ratios (OR) 1.09; 95% confidence intervals (CI) 0.94-1.25, CAV1 (0.72, OR 1.18; 95% CI 1.09-1.28) and PLA2G16 (0.76, OR 1.35; 95% CI 1.199-1.51). In combination, a two-marker assay performs better than prostate specific antigen (PSA), AUC 0.77 vs. PSA AUC of 0.6 (P = 0.01) with the lowest error. In addition, FGF1 distinguished between grade group 1 (GG1) and higher grade cancers (P<0.03). In conclusion, applying methylation of field defect loci to urine samples provides a novel approach to distinguish patients with and without cancer.

Advanced Prostate Cancer: AUA/ASTRO/SUO Guideline PART II.

PURPOSE: The summary presented herein represents Part II of the two-part series dedicated to Advanced Prostate Cancer: AUA/ASTRO/SUO Guideline discussing prognostic and treatment recommendations for patients with castration-resistant disease. Please refer to Part I for discussion of the management of patients with biochemical recurrence without metastatic disease after exhaustion of local treatment options as well as those with metastatic hormone-sensitive prostate cancer. RESULTS: The Advanced Prostate Cancer Panel created evidence- and consensus-based guideline statements to aid clinicians in the management of patients with advanced prostate cancer. Such statements are summarized in figure 1[Figure: see text] and detailed herein. MATERIALS AND METHODS: The systematic review utilized to inform this guideline was conducted by an independent methodological consultant. A research librarian conducted searches in Ovid MEDLINE (1998 to January Week 5 2019), Cochrane Central Register of Controlled Trials (through December 2018), and Cochrane Database of Systematic Reviews (2005 through February 6, 2019). An updated search was conducted prior to publication through January 20, 2020. The methodology team supplemented searches of electronic databases with the studies included in the prior AUA review and by reviewing reference lists of relevant articles. CONCLUSIONS: This guideline attempts to improve a clinician's ability to treat patients diagnosed with advanced prostate cancer. Continued research and publication of high-quality evidence from future trials will be essential to improve the level of care for these patients.

Advanced Prostate Cancer: AUA/ASTRO/SUO Guideline PART I.

PURPOSE: The summary presented herein represents Part I of the two-part series dedicated to Advanced Prostate Cancer: AUA/ASTRO/SUO Guideline discussing prognostic and treatment recommendations for patients with biochemical recurrence without metastatic disease after exhaustion of local treatment options as well as those with metastatic hormone-sensitive prostate cancer. Please refer to Part II for discussion of the management of castration-resistant disease. MATERIALS AND METHODS: The systematic review utilized to inform this guideline was conducted by an independent methodological consultant. A research librarian conducted searches in Ovid MEDLINE (1998 to January Week 5 2019), Cochrane Central Register of Controlled Trials (through December 2018), and Cochrane Database of Systematic Reviews (2005 through February 6, 2019). An updated search was conducted prior to publication through January 20, 2020. The methodology team supplemented searches of electronic databases with the studies included in the prior AUA review and by reviewing reference lists of relevant articles. RESULTS: The Advanced Prostate Cancer Panel created evidence- and consensus-based guideline statements to aid clinicians in the management of patients with advanced prostate cancer. Such statements are summarized in figure 1[Figure: see text] and detailed herein. CONCLUSIONS: This guideline attempts to improve a clinician's ability to treat patients diagnosed with advanced prostate cancer. Continued research and publication of high-quality evidence from future trials will be essential to improve the level of care for these patients.

Accurate segmentation of prostate cancer histomorphometric features using a weakly supervised convolutional neural network.

Purpose: Prostate cancer primarily arises from the glandular epithelium. Histomophometric techniques have been used to assess the glandular epithelium in automated detection and classification pipelines; however, they are often rigid in their implementation, and their performance suffers on large datasets where variation in staining, imaging, and preparation is difficult to control. The purpose of this study is to quantify performance of a pixelwise segmentation algorithm that was trained using different combinations of weak and strong stroma, epithelium, and lumen labels in a prostate histology dataset. Approach: We have combined weakly labeled datasets generated using simple morphometric techniques and high-quality labeled datasets from human observers in prostate biopsy cores to train a convolutional neural network for use in whole mount prostate labeling pipelines. With trained networks, we characterize pixelwise segmentation of stromal, epithelium, and lumen (SEL) regions on both biopsy core and whole-mount H&E-stained tissue. Results: We provide evidence that by simply training a deep learning algorithm on weakly labeled data generated from rigid morphometric methods, we can improve the robustness of classification over the morphometric methods used to train the classifier. Conclusions: We show that not only does our approach of combining weak and strong labels for training the CNN improve qualitative SEL labeling within tissue but also the deep learning generated labels are superior for cancer classification in a higher-order algorithm over the morphometrically derived labels it was trained on.