Histopathology of Prostate Cancer

Mesenchymal stem cell-derived exosomes for management of prostate cancer: An updated view

Prostate cancer represents the second most prevalent form of cancer found in males, and stands as the fifth primary contributor to cancer-induced mortality on a global scale. Research has shown that transplanted mesenchymal stem cells (MSCs) can migrate by homing to tumor sites in the body. In prostate cancer, researchers have explored the fact that MSC-based therapies (including genetically modified delivery vehicles or vectors) and MSC-derived exosomes are emerging as attractive options to improve the efficacy and safety of traditional cancer therapies. In addition, researchers have reported new insights into the application of extracellular vesicle (EV)-MSC therapy as a novel treatment option that could provide a more effective and targeted approach to prostate cancer treatment. Moreover, the new generation of exosomes, which contain biologically functional molecules as signal transducers between cells, can simultaneously deliver different therapeutic agents and induce an anti-tumor phenotype in immune cells and their recruitment to the tumor site. The results of the current research on the use of MSCs in the treatment of prostate cancer may be helpful to researchers and clinicians working in this field. Nevertheless, it is crucial to emphasize that although dual-role MSCs show promise as a therapeutic modality for managing prostate cancer, further investigation is imperative to comprehensively grasp their safety and effectiveness. Ongoing clinical trials are being conducted to assess the viability of MSCs in the management of prostate cancer. The results of these trials will help determine the viability of this approach. Based on the current literature, engineered MSCs-EV offer great potential for application in targeted tumor therapy.

Bisphenol S enhances the cell proliferation ability of prostate cancer cells by regulating the expression of SDS

Recent times have witnessed an increase in both incidence and mortality rates of prostate cancer. While some individuals with localized or metastatic cancer may progress slowly with a lower mortality risk, those with intermediate or high-risk cancer often face a higher likelihood of death, despite treatment. Bisphenol A (BPA) has been linked to various cancers, including prostate and breast cancer, yet the relationship between bisphenol S (BPS) and human health remains underexplored. In our study, we employed ssGSEA analysis to evaluate the BPS-associated score in a prostate cancer cohort. Additionally, differential expression analysis identified BPS-related genes within the same group. Through COX and LASSO regression analyses, we developed and validated a BPS-related risk model using ROC curve and survival analyses. A nomogram, integrating clinical characteristics with this risk model, was established for improved predictive accuracy, further substantiated by calibration curve validation. Molecular docking analysis suggested potential binding between SDS and BPS. We also conducted cell proliferation assays on C4-2 and LNCaP prostate cancer cells, revealing increased cell growth at a BPS concentration of 10-7 M, as evidenced by CCK8 and EdU assays. In summary, our findings shed light on the BPS-prostate cancer linkage, identifying BPS-associated genes, establishing a validated risk model, exploring SDS-BPS binding potential, and assessing BPS's effect on prostate cancer cell growth. These insights underscore the need for further investigation into BPS and its impact on human diseases.

Characterization of prostatic cancer lesion and gleason grade using a continuous-time random-walk diffusion model at high b-values

Background

Distinguishing between prostatic cancer (PCa) and chronic prostatitis (CP) is sometimes challenging, and Gleason grading is strongly associated with prognosis in PCa. The continuous-time random-walk diffusion (CTRW) model has shown potential in distinguishing between PCa and CP as well as predicting Gleason grading.

Purpose

This study aimed to quantify the CTRW parameters (α, β & Dm) and apparent diffusion coefficient (ADC) of PCa and CP tissues; and then assess the diagnostic value of CTRW and ADC parameters in differentiating CP from PCa and low-grade PCa from high-grade PCa lesions.

Study type

Retrospective (retrospective analysis using prospective designed data).

Population

Thirty-one PCa patients undergoing prostatectomy (mean age 74 years, range 64-91 years), and thirty CP patients undergoing prostate needle biopsies (mean age 68 years, range 46-79 years).

Field strength/Sequence

MRI scans on a 3.0T scanner (uMR790, United Imaging Healthcare, Shanghai, China). DWI were acquired with 12 b-values (0, 50, 100, 150, 200, 500, 800, 1200, 1500, 2000, 2500, 3000 s/mm2).

Assessment

CTRW parameters and ADC were quantified in PCa and CP lesions.

Statistical tests

The Mann-Whitney U test was used to evaluate the differences in CTRW parameters and ADC between PCa and CP, high-grade PCa, and low-grade PCa. Spearman's correlation of the pathologic grading group (GG) with CTRW parameters and ADC was evaluated. The usefulness of CTRW parameters, ADC, and their combinations (Dm, α and β; Dm, α, β, and ADC) to differentiate PCa from CP and high-grade PCa from low-grade PCa was determined by logistic regression and receiver operating characteristic curve (ROC) analysis. Delong test was used to compare the differences among AUCs.

Results

Significant differences were found for the CTRW parameters (α, Dm) between CP and PCa (all P<0.001), high-grade PCa, and low-grade PCa (α:P=0.024, Dm:P=0.021). GG is correlated with certain CTRW parameters and ADC(α:P<0.001,r=-0.795; Dm:P<0.001,r=-0.762;ADC:P<0.001,r=-0.790). Moreover, CTRW parameters (α, β, Dm) combined with ADC showed the best diagnostic efficacy for distinguishing between PCa and CP as well as predicting Gleason grading. The differences among AUCs of ADC, CTRW parameters and their combinations were not statistically significant (P=0.051-0.526).

Conclusion

CTRW parameters α and Dm, as well as their combination were beneficial to distinguish between CA and PCa, low-grade PCa and high-grade PCa lesions, and CTRW parameters and ADC had comparable diagnostic performance.

Case report: Isolated oligometastatic disease of the prostate from a primary lung adenocarcinoma

Secondary prostate cancer typically occurs from direct seeding of a renal or bladder tumor. Metastasis via hematogenous spread is exceedingly rare and is typically identified incidentally at autopsy. This report describes a 72-year-old male with lung adenocarcinoma initially staged as Stage IA2 who developed oligometastatic disease of the prostate. He was initially treated with radiation therapy and was found to have a hypermetabolic focus in the prostate gland during surveillance PET/CT imaging 6 months following treatment. Subsequent biopsy revealed metastatic lung adenocarcinoma in 6/6 core samples, leading to diagnosis of oligometastatic disease of the prostate. To our knowledge, this is the first report of isolated oligometastatic disease to the prostate from a primary lung adenocarcinoma.

Prostate cancer biomarkers: from early diagnosis to precision treatment

Prostate cancer (PCa) is the second most prevalent cancer in men. In 2020, approximately 1,414,259 new cases were reported that accounted for 3,75,324 deaths (Sung et al. in CA 71:209-249, 2021). PCa is often asymptomatic at early stages; hence, routine screening and monitoring based on reliable biomarkers is crucial for early detection and assessment of cancer progression. Early diagnosis of disease is key step in reducing PCa-induced mortality. Biomarkers such as PSA have played vital role in reducing recent PCa deaths. Recent research has identified many other biomarkers and also refined PSA-based tests for non-invasive diagnosis of PCa in patients. Despite progress in screening methods, an important issue that influences treatment is heterogeneity of the cancer in different individuals, necessitating personalized treatment. Currently, focus is to identify biomarkers that can accurately diagnose PCa at early stage, indicate the stage of the disease, metastatic nature and chances of survival based on individual patient profile (Fig. 1). Fig. 1 Graphical abstract.

The neuroendocrine transition in prostate cancer is dynamic and dependent on ASCL1

Lineage plasticity is a recognized hallmark of cancer progression that can shape therapy outcomes. The underlying cellular and molecular mechanisms mediating lineage plasticity remain poorly understood. Here, we describe a versatile in vivo platform to identify and interrogate the molecular determinants of neuroendocrine lineage transformation at different stages of prostate cancer progression. Adenocarcinomas reliably develop following orthotopic transplantation of primary mouse prostate organoids acutely engineered with human-relevant driver alterations (e.g., Rb1-/-; Trp53-/-; cMyc+ or Pten-/-; Trp53-/-; cMyc+), but only those with Rb1 deletion progress to ASCL1+ neuroendocrine prostate cancer (NEPC), a highly aggressive, androgen receptor signaling inhibitor (ARSI)-resistant tumor. Importantly, we show this lineage transition requires a native in vivo microenvironment not replicated by conventional organoid culture. By integrating multiplexed immunofluorescence, spatial transcriptomics and PrismSpot to identify cell type-specific spatial gene modules, we reveal that ASCL1+ cells arise from KRT8+ luminal epithelial cells that progressively acquire transcriptional heterogeneity, producing large ASCL1+;KRT8- NEPC clusters. Ascl1 loss in established NEPC results in transient tumor regression followed by recurrence; however, Ascl1 deletion prior to transplantation completely abrogates lineage plasticity, yielding adenocarcinomas with elevated AR expression and marked sensitivity to castration. The dynamic feature of this model reveals the importance of timing of therapies focused on lineage plasticity and offers a platform for identification of additional lineage plasticity drivers.

Unveiling spatial complexity in solid tumor immune microenvironments through multiplexed imaging

Deciphering cellular components and the spatial interaction network of the tumor immune microenvironment (TIME) of solid tumors is pivotal for understanding biologically relevant cross-talks and, ultimately, advancing therapies. Multiplexed tissue imaging provides a powerful tool to elucidate spatial complexity in a holistic manner. We established and cross-validated a comprehensive immunophenotyping panel comprising over 121 markers for multiplexed tissue imaging using MACSima™ imaging cyclic staining (MICS) alongside an end-to-end analysis workflow. Applying this panel and workflow to primary cancer tissues, we characterized tumor heterogeneity, investigated potential therapeutical targets, conducted in-depth profiling of cell types and states, sub-phenotyped T cells within the TIME, and scrutinized cellular neighborhoods of diverse T cell subsets. Our findings highlight the advantage of spatial profiling, revealing immunosuppressive molecular signatures of tumor-associated myeloid cells interacting with neighboring exhausted, PD1high T cells in the TIME of hepatocellular carcinoma (HCC). This study establishes a robust framework for spatial exploration of TIMEs in solid tumors and underscores the potency of multiplexed tissue imaging and ultra-deep cell phenotyping in unraveling clinically relevant tumor components.

Prostate cancer in Spain: A retrospective database analysis of hospital incidence and the direct medical costs

INTRODUCTION

The goal of this study is to determine the medical costs, comorbidity profile, and health care resources use of patients diagnosed with prostate cancer who have been treated in Spanish hospitals.

METHODS

The admission records of the patients diagnosed with prostate cancer used in the study were registered between January 2016 and December 2020. These records have been collected from a Spanish hospital discharge database and have been evaluated in a retrospective multicenter analysis.

RESULTS

8218 patients from the database met the criteria and were thus analyzed. The median aged of the diagnosed patients was 71.68 years. The median Charlson comorbidity index (CCI) score was 4, and the updated median CCI was 3. Hypertension was diagnosed in the 49.76% of the individuals, 37.03% had chronic obstructive pulmonary disease and 34.51% had hyperlipidaemia. The mortality rate was 9.30%. The most common medical procedure was prostate resection with percutaneous endoscopic approach (31.18%). The mean annual cost per admission was 5212.98€ €.

CONCLUSIONS

Technologies, such as the prostate-specific antigen (PSA) testing for screening has helped in the diagnosis in the past decades, enhancing a decrease in the mortality rate of the patients throughout the years.

A multivariate curve resolution analysis of multicenter proton spectroscopic imaging of the prostate for cancer localization and assessment of aggressiveness

In this study, we investigated the potential of the multivariate curve resolution alternating least squares (MCR-ALS) algorithm for analyzing three-dimensional (3D) 1 H-MRSI data of the prostate in prostate cancer (PCa) patients. MCR-ALS generates relative intensities of components representing spectral profiles derived from a large training set of patients, providing an interpretable model. Our objectives were to classify magnetic resonance (MR) spectra, differentiating tumor lesions from benign tissue, and to assess PCa aggressiveness. We included multicenter 3D 1 H-MRSI data from 106 PCa patients across eight centers. The patient cohort was divided into a training set (N = 63) and an independent test set (N = 43). Singular value decomposition determined that MR spectra were optimally represented by five components. The profiles of these components were extracted from the training set by MCR-ALS and assigned to specific tissue types. Using these components, MCR-ALS was applied to the test set for a quantitative analysis to discriminate tumor lesions from benign tissue and to assess tumor aggressiveness. Relative intensity maps of the components were reconstructed and compared with histopathology reports. The quantitative analysis demonstrated a significant separation between tumor and benign voxels (t-test, p < 0.001). This result was achieved including voxels with low-quality MR spectra. A receiver operating characteristic analysis of the relative intensity of the tumor component revealed that low- and high-risk tumor lesions could be distinguished with an area under the curve of 0.88. Maps of this component properly identified the extent of tumor lesions. Our study demonstrated that MCR-ALS analysis of 1 H-MRSI of the prostate can reliably identify tumor lesions and assess their aggressiveness. It handled multicenter data with minimal preprocessing and without using prior knowledge or quality control. These findings indicate that MCR-ALS can serve as an automated tool to assess the presence, extent, and aggressiveness of tumor lesions in the prostate, enhancing diagnostic capabilities and treatment planning of PCa patients.

Co-axial hydrogel spinning for facile biofabrication of prostate cancer-like 3D models

Glandular cancers are amongst the most prevalent types of cancer, which can develop in many different organs, presenting challenges in their detection as well as high treatment variability and failure rates. For that purpose, anticancer drugs are commonly tested in cancer cell lines grown in 2D tissue culture on plastic dishesin vitro, or in animal modelsin vivo. However, 2D culture models diverge significantly from the 3D characteristics of living tissues and animal models require extensive animal use and time. Glandular cancers, such as prostate cancer-the second leading cause of male cancer death-typically exist in co-centrical architectures where a cell layer surrounds an acellular lumen. Herein, this spatial cellular position and 3D architecture, containing dual compartments with different hydrogel materials, is engineered using a simple co-axial nozzle setup, in a single step utilizing prostate as a model of glandular cancer. The resulting hydrogel soft structures support viable prostate cancer cells of different cell lines and enable over-time maturation into cancer-mimicking aggregates surrounding the acellular core. The biofabricated cancer mimicking structures are then used as a model to predict the inhibitory efficacy of the poly ADP ribose polymerase inhibitor, Talazoparib, and the antiandrogen drug, Enzalutamide, in the growth of the cancer cell layer. Our results show that the obtained hydrogel constructs can be adapted to quickly obtain 3D cancer models which combine 3D physiological architectures with high-throughput screening to detect and optimize anti-cancer drugs in prostate and potentially other glandular cancer types.

Urinary volatile organic compounds in prostate cancer biopsy pathologic risk stratification using logistic regression and multivariate analysis models

Prostate cancer (PCa) is the second leading cause of cancer-related death in American men after lung cancer. The current PCa diagnostic method, the serum prostate-specific antigen (PSA) test, is not specific, thus, alternatives are needed to avoid unnecessary biopsies and over-diagnosis of clinically insignificant PCa. To explore the application of metabolomics in such effort, urine samples were collected from 386 male adults aged 44-93 years, including 247 patients with biopsy-proven PCa and 139 with biopsy-proven negative results. The PCa-positive group was further subdivided into two groups: low-grade (ISUP Grade Group = 1; n = 139) and intermediate/high-grade (ISUP Grade Group ≥ 2; n = 108). Volatile organic compounds (VOCs) in urine were extracted by stir bar sorptive extraction (SBSE) and analyzed using thermal desorption with gas chromatography and mass spectrometry (GC-MS). We used machine learning tools to develop and evaluate models for PCa diagnosis and prognosis. In total, 22,538 VOCs were identified in the urine samples. With regularized logistic regression, our model for PCa diagnosis yielded an area under the curve (AUC) of 0.99 and 0.88 for the training and testing sets respectively. Furthermore, the model for differentiating between low-grade and intermediate/high-grade PCa yielded an average AUC of 0.78 based on a repeated test-sample approach for cross-validation. These novel methods using urinary VOCs and logistic regression were developed to fill gaps in PCa screening and assessment of PCa grades prior to biopsy. Our study findings provide a promising alternative or adjunct to current PCa screening and diagnostic methods to better target patients for biopsy and mitigate the challenges associated with over-diagnosis and over-treatment of PCa.

Correlation Attention Registration Based on Deep Learning from Histopathology to MRI of Prostate

Deep learning offers a promising methodology for the registration of prostate cancer images from histopathology to MRI. We explored how to effectively leverage key information from images to achieve improved end-to-end registration. We developed an approach based on a correlation attention registration framework to register segmentation labels of histopathology onto MRI. The network was trained using paired prostate datasets of histopathology and MRI from the Cancer Imaging Archive. We introduced An L2-Pearson correlation layer to enhance feature matching. Furthermore, our model employed an enhanced attention regression network to distinguish between key and nonkey features. For data analysis, we used the Kolmogorov-Smirnov test and a one-sample t-test, with the statistical significance level for the one-sample t-test set at 0.001. Compared with two other models (ProsRegNet and CNNGeo), our model exhibited improved performance in Dice coefficient, with increases of 9.893% and 2.753%, respectively. The Hausdorff distance was reduced by approximately 50% and 50%, while the average label error (ALE) was reduced by 0.389% and 15.021%. The proposed improved multimodal prostate registration framework demonstrated high performance in statistical analysis. The results indicate that our enhanced strategy significantly improves registration performance and enables faster registration of histopathological images of patients undergoing radical prostatectomy to preoperative MRI. More accurate registration can prevent over-diagnosing low-risk cancers and frequent false positives due to observer differences.

ADORA2A-driven proline synthesis triggers epigenetic reprogramming in neuroendocrine prostate and lung cancers

Cell lineage plasticity is one of the major causes for the failure of targeted therapies in various cancers. However, the driver and actionable drug targets in promoting cancer cell lineage plasticity are scarcely identified. Here, we found that a G protein-coupled receptor, ADORA2A, is specifically upregulated during neuroendocrine differentiation, a common form of lineage plasticity in prostate cancer and lung cancer following targeted therapies. Activation of the ADORA2A signaling rewires the proline metabolism via an ERK/MYC/PYCR cascade. Increased proline synthesis promotes deacetylases SIRT6/7-mediated deacetylation of histone H3 at lysine 27 (H3K27), and thereby biases a global transcriptional output toward a neuroendocrine lineage profile. Ablation of Adora2a in genetically engineered mouse models inhibits the development and progression of neuroendocrine prostate and lung cancers, and, intriguingly, prevents the adenocarcinoma-to-neuroendocrine phenotypic transition. Importantly, pharmacological blockade of ADORA2A profoundly represses neuroendocrine prostate and lung cancer growth in vivo. Therefore, we believe that ADORA2A can be used as a promising therapeutic target to govern the epigenetic reprogramming in neuroendocrine malignancies.

Diplopia and Ptosis: An Unusual Case of Prostate Cancer Metastasis to the Sphenoid Bone Treated With Palliative Radiotherapy

We report a case of a 72-year-old male who presented to the hospital with a chief complaint of diplopia in the setting of a recent onset of urinary incontinence and right-sided back pain. He was subsequently diagnosed with prostate cancer, notably metastasizing to the right sphenoid bone, causing impingement of the oculomotor nerve. Our case is unique in that the patient's initial presentation of prostate cancer was oculomotor nerve palsy with subsequent histologic analysis of the primary tumor showing both small cell neuroendocrine carcinoma along with adenocarcinoma. Also, the initial routine stroke protocol MRI and computed tomography angiography (CTA) missed the lesion, while gadolinium-enhanced targeted MRI revealed lesions in both the spine and the orbit. This case emphasizes the need for enhanced contrast as well as focused imaging in patients presenting with diplopia with a negative initial workup for stroke. Ptosis can be a sign of metastasis from other cancers and it is important to have a broad differential including metastatic disease in patients' presenting with similar symptoms and negative initial workup who may otherwise be at risk of cancer.

Inflammation in Prostate Cancer: Exploring the Promising Role of Phenolic Compounds as an Innovative Therapeutic Approach

Prostate cancer (PCa) remains a significant global health concern, being a major cause of cancer morbidity and mortality worldwide. Furthermore, profound understanding of the disease is needed. Prostate inflammation caused by external or genetic factors is a central player in prostate carcinogenesis. However, the mechanisms underlying inflammation-driven PCa remain poorly understood. This review dissects the diagnosis methods for PCa and the pathophysiological mechanisms underlying the disease, clarifying the dynamic interplay between inflammation and leukocytes in promoting tumour development and spread. It provides updates on recent advances in elucidating and treating prostate carcinogenesis, and opens new insights for the use of bioactive compounds in PCa. Polyphenols, with their noteworthy antioxidant and anti-inflammatory properties, along with their synergistic potential when combined with conventional treatments, offer promising prospects for innovative therapeutic strategies. Evidence from the use of polyphenols and polyphenol-based nanoparticles in PCa revealed their positive effects in controlling tumour growth, proliferation, and metastasis. By consolidating the diverse features of PCa research, this review aims to contribute to increased understanding of the disease and stimulate further research into the role of polyphenols and polyphenol-based nanoparticles in its management.

Analysis of genetic biomarkers, polymorphisms in ADME-related genes and their impact on pharmacotherapy for prostate cancer

Prostate cancer (PCa) is a non-cutaneous malignancy in males with wide variation in incidence rates across the globe. It is the second most reported cause of cancer death. Its etiology may have been linked to genetic polymorphisms, which are not only dominating cause of malignancy casualties but also exerts significant effects on pharmacotherapy outcomes. Although many therapeutic options are available, but suitable candidates identified by useful biomarkers can exhibit maximum therapeutic efficacy. The single-nucleotide polymorphisms (SNPs) reported in androgen receptor signaling genes influence the effectiveness of androgen receptor pathway inhibitors and androgen deprivation therapy. Furthermore, SNPs located in genes involved in transport, drug metabolism, and efflux pumps also influence the efficacy of pharmacotherapy. Hence, SNPs biomarkers provide the basis for individualized pharmacotherapy. The pharmacotherapeutic options for PCa include hormonal therapy, chemotherapy (Docetaxel, Mitoxantrone, Cabazitaxel, and Estramustine, etc.), and radiotherapy. Here, we overview the impact of SNPs reported in various genes on the pharmacotherapy for PCa and evaluate current genetic biomarkers with an emphasis on early diagnosis and individualized treatment strategy in PCa.

Direct Patlak Reconstruction of [68Ga]Ga-PSMA PET for the Evaluation of Primary Prostate Cancer Prior Total Prostatectomy: Results of a Pilot Study

To investigate the use of kinetic parameters derived from direct Patlak reconstructions of [68Ga]Ga-PSMA-11 positron emission tomography/computed tomography (PET/CT) to predict the histological grade of malignancy of the primary tumor of patients with prostate cancer (PCa). Thirteen patients (mean age 66 ± 10 years) with a primary, therapy-naïve PCa (median PSA 9.3 [range: 6.3-130 µg/L]) prior radical prostatectomy, were recruited in this exploratory prospective study. A dynamic whole-body [68Ga]Ga-PSMA-11 PET/CT scan was performed for all patients. Measured quantification parameters included Patlak slope (Ki: absolute rate of tracer consumption) and Patlak intercept (Vb: degree of tracer perfusion in the tumor). Additionally, the mean and maximum standardized uptake values (SUVmean and SUVmax) of the tumor were determined from a static PET 60 min post tracer injection. In every patient, initial PSA (iPSA) values that were also the PSA level at the time of the examination and final histology results with Gleason score (GS) grading were correlated with the quantitative readouts. Collectively, 20 individual malignant prostate lesions were ascertained and histologically graded for GS with ISUP classification. Six lesions were classified as ISUP 5, two as ISUP 4, eight as ISUP 3, and four as ISUP 2. In both static and dynamic PET/CT imaging, the prostate lesions could be visually distinguished from the background. The average values of the SUVmean, slope, and intercept of the background were 2.4 (±0.4), 0.015 1/min (±0.006), and 52% (±12), respectively. These were significantly lower than the corresponding parameters extracted from the prostate lesions (all p < 0.01). No significant differences were found between these values and the various GS and ISUP (all p > 0.05). Spearman correlation coefficient analysis demonstrated a strong correlation between static and dynamic PET/CT parameters (all r ≥ 0.70, p < 0.01). Both GS and ISUP grading revealed only weak correlations with the mean and maximum SUV and tumor-to-background ratio derived from static images and dynamic Patlak slope. The iPSA demonstrated no significant correlation with GS and ISUP grading or with dynamic and static PET parameter values. In this cohort of mainly high-risk PCa, no significant correlation between [68Ga]Ga-PSMA-11 perfusion and consumption and the aggressiveness of the primary tumor was observed. This suggests that the association between SUV values and GS may be more distinctive when distinguishing clinically relevant from clinically non-relevant PCa.

Real-world outcomes of abiraterone and enzalutamide in first-line treatment of metastatic castration-resistant prostate cancer: which patients benefit most?

OBJECTIVES

Abiraterone and enzalutamide are two oral novel androgen receptor axis-targeted agents approved for the treatment of castration-resistant prostate cancer (mCRPC). Despite the availability of multiple treatments, there is a need to improve the knowledge and management of these drugs in the real-world setting, especially in patient groups under-represented in clinical trials. Our aim was to review the outcome of patients with chemotherapy-naïve mCRPC treated with abiraterone or enzalutamide in routine clinical practice in order to identify factors that are predictive for response.

METHODS

This observational retrospective study was performed in a Spanish tertiary hospital and included men with chemotherapy-naïve mCPRC who started treatment with abiraterone or enzalutamide between September 2012 and November 2018. The study end date was 30 October 2020.

RESULTS

Ninety patients with mCRPC were included, 57 with abiraterone and 33 with enzalutamide. Median overall survival (OS) was 26.87 months (95% CI 19.68 to 34.05), with no difference found between the two treatment groups. Nine variables were related to increased OS in the univariate analysis: Eastern Cooperative Oncology Group (ECOG) performance status (0-1 vs 2), pain (need of opioids for cancer pain), visceral disease, ≥3 bone lesions, exclusively lymph node metastases, baseline prostate specific antigen (PSA) (<50 vs ≥50 ng/dL and <20 vs ≥20 ng/dL), haemoglobin (<12 vs ≥12 g/dL) and alkaline phosphatase (≤116 vs >116 IU/L). A PSA response >50% was observed in 65 patients (76.5%). In the multivariate analysis, ECOG performance status, pain, visceral disease and alkaline phosphatase provided independent prognostic information. Median OS by Kaplan-Meier analysis was significantly longer for patients with a PSA response (32.1 vs 17.9 months; HR 0.46, 95% CI 0.27 to 0.78; p=0.003).

CONCLUSIONS

This study assessed the efficacy of abiraterone and enzalutamide in a real-world setting, including patients under-represented in pivotal studies. Some clinical factors were correlated with improved OS in chemotherapy-naïve men with mCPRC treated with these drugs.

The Effect of Natural Substances Contained in Bee Products on Prostate Cancer in In Vitro Studies

Prostate cancer is a common cancer in men in older age groups. The WHO forecasts an increase in the incidence of prostate cancer in the coming years. Patients may not respond to treatment, and may not tolerate the side effects of chemotherapy. Compounds of natural origin have long been used in the prevention and treatment of cancer. Flavonoids obtained from natural products, e.g., propolis, are compounds with proven antibacterial and antiviral efficacy which modulate the immune response and may be useful as adjuvants in chemotherapy. The main aim of the present study was to evaluate the cytotoxic and pro-apoptotic properties of selected flavonoids on prostate cancer cells of the LNCaP line. The compounds used in this study were CAPE, curcumin (CUR), and quercetin (QUE). Mitochondrial and lysosome metabolism was assessed by the XTT-NR-SRB triple assay as well as by the fluorescent staining techniques. Staining for reactive oxygen species was performed as well. The experiment showed that each of the tested compounds has a cytotoxic effect on the LNCaP cell line. Different types of cell death were induced by the tested compounds. Apoptosis was induced by quercetin, while autophagy-specific changes were observed after using CAPE. Compounds obtained from other bee products have antiproliferative and cytotoxic activity against LNCaP prostate cancer cells.

Usefulness of BRCA and ctDNA as Prostate Cancer Biomarkers: A Meta-Analysis

Prostate cancer represents the most common male urologic neoplasia. Tissue biopsies are the gold standard in oncology for diagnosing prostate cancer. We conducted a study to find the most reliable and noninvasive diagnostic tool. We performed a systematic review and meta-analysis of two biomarkers which we believe are the most interesting: BRCA (BRCA1 and 2) and ctDNA. Our systematic research yielded 248 articles. Forty-five duplicates were first excluded and, upon further examination, a further 203 articles were excluded on the basis of the inclusion and exclusion criteria, leaving 25 articles. A statistical analysis of the obtained data has been performed. With a collective calculation, BRCA1 was expressed in 2.74% of all cases from 24,212 patients examined and BRCA2 in 1.96% of cases from 20,480 patients. In a total calculation using ctDNA, it was observed that 89% of cases from 1198 patients exhibited high expression of circulating tumor DNA. To date, no ideal PCa biomarker has been found. Although BRCA1 and BRCA2 work well for breast and ovarian cancers, they do not seem to be reliable for prostate cancer. ctDNA seems to be a much better biomarker; however, there are few studies in this area. Further studies need to be performed.

Prognostic value of a baseline prognostic nutritional index for patients with prostate cancer: a systematic review and meta-analysis

BACKGROUND

The prognostic nutritional index (PNI) integrates both nutritional and immune indicators and provides promising prognostic value for various malignancies. However, there is still no specific consensus relating to the precise relationship between the pretreatment PNI and the survival outcome of patients with prostate cancer (PCa). Here, we performed a meta-analysis to determine the prognostic significance of PNI for patients with PCa.

METHODS

We used the PubMed, EMBASE, Web of Science, Cochrane Library (CENTRAL), and CNKI databases to identify and retrieve eligible articles that were published in any language up to the 1st March 2023. Our analysis considered hazard ratios (HRs) and 95% confidence intervals (CIs) published in the included studies. Data synthesis and analysis were conducted using Stata 15.1 software.

RESULTS

A total of ten studies featuring 1631 cases were included in our quantitative analysis. Analysis showed that a low PNI at baseline was significantly associated with poor overall survival (OS) (HR: 2.16; 95% CI: 1.40-3.34; p = 0.01), progression-free survival (PFS) (HR: 2.17; 95% CI 1.63-2.89; p < 0.001). Owing to high levels of heterogeneity, we performed subgroup analysis based on disease staging, sample size, and cutoff value; we found that disease staging may have been the source of the heterogeneity. A low pretreatment PNI was associated with poor survival outcomes for both metastatic castration-resistant prostate cancer (mCRPC) patients and nonmetastatic castration-resistant prostate cancer (nmCRPC) patients.

CONCLUSIONS

A low pretreatment PNI was significantly correlated with a worse OS and PFS in patients with PCa. A low pretreatment PNI may act as a reliable and effective predictor for the prognosis of patients with PCa. Further well-designed studies should be performed to fully evaluate the prognostic performance of this novel indicator for PCa.

Application of Spectral Algorithm Applied to Spatially Registered Bi-Parametric MRI to Predict Prostate Tumor Aggressiveness: A Pilot Study

Background: Current prostate cancer evaluation can be inaccurate and burdensome. Quantitative evaluation of Magnetic Resonance Imaging (MRI) sequences non-invasively helps prostate tumor assessment. However, including Dynamic Contrast Enhancement (DCE) in the examined MRI sequence set can add complications, inducing possible side effects from the IV placement or injected contrast material and prolonging scanning time. More accurate quantitative MRI without DCE and artificial intelligence approaches are needed. Purpose: Predict the risk of developing Clinically Significant (Insignificant) prostate cancer CsPCa (CiPCa) and correlate with the International Society of Urologic Pathology (ISUP) grade using processed Signal to Clutter Ratio (SCR) derived from spatially registered bi-parametric MRI (SRBP-MRI) and thereby enhance non-invasive management of prostate cancer. Methods: This pilot study retrospectively analyzed 42 consecutive prostate cancer patients from the PI-CAI data collection. BP-MRI (Apparent Diffusion Coefficient, High B-value, T2) were resized, translated, cropped, and stitched to form spatially registered SRBP-MRI. Efficacy of noise reduction was tested by regularizing, eliminating principal components (PC), and minimizing elliptical volume from the covariance matrix to optimize the SCR. MRI guided biopsy (MRBx), Systematic Biopsy (SysBx), combination (MRBx + SysBx), or radical prostatectomy determined the ISUP grade for each patient. ISUP grade ≥ 2 (<2) was judged as CsPCa (CiPCa). Linear and logistic regression were fitted to ISUP grade and CsPCa/CiPCa SCR. Correlation Coefficients (R) and Area Under the Curves (AUC) for Receiver Operator Curves (ROC) evaluated the performance. Results: High correlation coefficients (R) (>0.55) and high AUC (=1.0) for linear and/or logistic fit from processed SCR and z-score for SRBP-MRI greatly exceed fits using prostate serum antigen, prostate volume, and patient age (R ~ 0.17). Patients assessed with combined MRBx + SysBx and from individual MRI scanners achieved higher R (DR = 0.207+/-0.118) than all patients used in the fits. Conclusions: In the first study, to date, spectral approaches for assessing tumor aggressiveness on SRBP-MRI have been applied and tested and achieved high values of R and exceptional AUC to fit the ISUP grade and CsPCA/CiPCA, respectively.

Three-dimensional convolutional neural network model to identify clinically significant prostate cancer in transrectal ultrasound videos: a prospective, multi-institutional, diagnostic study

Background

Identifying patients with clinically significant prostate cancer (csPCa) before biopsy helps reduce unnecessary biopsies and improve patient prognosis. The diagnostic performance of traditional transrectal ultrasound (TRUS) for csPCa is relatively limited. This study was aimed to develop a high-performance convolutional neural network (CNN) model (P-Net) based on a TRUS video of the entire prostate and investigate its efficacy in identifying csPCa.

Methods

Between January 2021 and December 2022, this study prospectively evaluated 832 patients from four centres who underwent prostate biopsy and/or radical prostatectomy. All patients had a standardised TRUS video of the whole prostate. A two-dimensional CNN (2D P-Net) and three-dimensional CNN (3D P-Net) were constructed using the training cohort (559 patients) and tested on the internal validation cohort (140 patients) as well as on the external validation cohort (133 patients). The performance of 2D P-Net and 3D P-Net in predicting csPCa was assessed in terms of the area under the receiver operating characteristic curve (AUC), biopsy rate, and unnecessary biopsy rate, and compared with the TRUS 5-point Likert score system as well as multiparametric magnetic resonance imaging (mp-MRI) prostate imaging reporting and data system (PI-RADS) v2.1. Decision curve analyses (DCAs) were used to determine the net benefits associated with their use. The study is registered at https://www.chictr.org.cn with the unique identifier ChiCTR2200064545.

Findings

The diagnostic performance of 3D P-Net (AUC: 0.85-0.89) was superior to TRUS 5-point Likert score system (AUC: 0.71-0.78, P = 0.003-0.040), and similar to mp-MRI PI-RADS v2.1 score system interpreted by experienced radiologists (AUC: 0.83-0.86, P = 0.460-0.732) and 2D P-Net (AUC: 0.79-0.86, P = 0.066-0.678) in the internal and external validation cohorts. The biopsy rate decreased from 40.3% (TRUS 5-point Likert score system) and 47.6% (mp-MRI PI-RADS v2.1 score system) to 35.5% (2D P-Net) and 34.0% (3D P-Net). The unnecessary biopsy rate decreased from 38.1% (TRUS 5-point Likert score system) and 35.2% (mp-MRI PI-RADS v2.1 score system) to 32.0% (2D P-Net) and 25.8% (3D P-Net). 3D P-Net yielded the highest net benefit according to the DCAs.

Interpretation

3D P-Net based on a prostate grayscale TRUS video achieved satisfactory performance in identifying csPCa and potentially reducing unnecessary biopsies. More studies to determine how AI models better integrate into routine practice and randomized controlled trials to show the values of these models in real clinical applications are warranted.

Funding

The National Natural Science Foundation of China (Grants 82202174 and 82202153), the Science and Technology Commission of Shanghai Municipality (Grants 18441905500 and 19DZ2251100), Shanghai Municipal Health Commission (Grants 2019LJ21 and SHSLCZDZK03502), Shanghai Science and Technology Innovation Action Plan (21Y11911200), and Fundamental Research Funds for the Central Universities (ZD-11-202151), Scientific Research and Development Fund of Zhongshan Hospital of Fudan University (Grant 2022ZSQD07).

Molecular evaluation of human papillomavirus as an oncogenic biomarker in prostate cancer

BACKGROUND

Prostate cancer (PCa) is one of the most common tumors in men, regardless of ethnicity and demographics. In many risk factors causing PCa, genes and viral infections are strong candidates for the development of prostate tumors. Indeed, tissue infections of PCa have been reported by the presence of several types of viruses including Human Papillomaviruses (HPV).

OBJECTIVE

the present study was planned to determine whether HPV DNA could be detected in the blood of known men with prostate cancer and to assess the potential association between HPV infection and clinico-pathological characteristics of the patients.

MATERIALS AND METHODS

In order to achieve our objectives, 150 liquid blood samples were taken from Moroccan patients, 100 patients with PCa, and 50 control cases. The viral DNA was extracted, calibrated and the target genes were amplified by PCR using specific primers and the use of 2% agarose gel with visualization under UV.

RESULTS

Of the 100 samples tested, (10%) were infected with HPV), However, none of the control cases were infected with HPV. The analysis of the data made it possible to establish a correlation between the frequency of the viral infection of the human papilloma and the tumoral criteria.

CONCLUSION

Therefore, this study strengthens the potential role of HPV as a cofactor in prostate cancer development, and we propose that infection with this virus may be involved in the development of PCa metastases.

Gleason Score-related MT1L as biomarker for prognosis in prostate adenocarcinoma and contribute to tumor progression in vitro

BACKGROUND

The Gleason Score is well correlated with biological behavior and prognosis in prostate adenocarcinoma (PRAD). This study was derived to determine the clinical significance and function of Gleason-Score-related genes in PRAD.

METHODS

RNA-sequencing profiles and clinical data were extracted from the The Cancer Genome Atlas PRAD database. The Gleason-Score-related genes were screened out by the Jonckheere-Terpstra rank-based test. The "limma" R package was performed for differentially expressed genes. Next, a Kaplan-Meier survival analysis was performed. Correlation MT1L expression levels with tumor stage, non-tumor tissue stage, radiation therapy, and residual tumor were analyzed. Further, MT1L expression was detected in PRAD cell lines by reverse transcription-quantitative polymerase chain reaction assay. Overexpression of MT1L was constructed and used for cell count kit-8, flow cytometric assay, transwell assay, and wound-healing assay.

RESULTS

Survival analysis showed 15 Gleason-Score-related genes as prognostic biomarkers in PRAD. The high-frequency deletion of MT1L was verified in PRAD. Furthermore, MT1L expression was decreased in PRAD cell lines than RWPE-1 cells, and overexpression of MT1L repressed cell proliferation and migration, and induced apoptosis in PC-3 cells.

CONCLUSION

Gleason-Score-related MT1L may serve as a biomarker of poor prognostic biomarker in PRAD. In addition, MT1L plays a tumor suppressor in PRAD progression, which is beneficial for PRAD diagnosis and treatment research.

MicroRNA-372 acts as a double-edged sword in human cancers

MicroRNAs (miRNAs or miRs) are non-coding, single-stranded, endogenous RNAs that regulate various biological processes, most notably the pathophysiology of many human malignancies. It process is accomplished by binding to 3'-UTR mRNAs and controlling gene expression at the post-transcriptional level. As an oncogene, miRNAs can either accelerate cancer progression or slow it down as a tumor suppressor. MicroRNA-372 (miR-372) has been found to have an abnormal expression in numerous human malignancies, implying that the miRNA plays a role in carcinogenesis. It is both increased and downregulated in various cancers, and it serves as both a tumor suppressor and an oncogene. This study examines the functions of miR-372 as well as the LncRNA/CircRNA-miRNA-mRNA signaling pathways in various malignancies and analyses its potential prognostic, diagnostic, and therapeutic implications.

Removing non-nuclei information from histopathological images: A preprocessing step towards improving nuclei segmentation methods

Disease interpretation by computer-aided diagnosis systems in digital pathology depends on reliable detection and segmentation of nuclei in hematoxylin and eosin (HE) images. These 2 tasks are challenging since appearance of both cell nuclei and background structures are very variable. This paper presents a method to improve nuclei detection and segmentation in HE images by removing tiles that only contain background information. The method divides each image into smaller patches and uses their projection to the noiselet space to capture different spatial features from non-nuclei background and nuclei structures. The noiselet features are clustered by a K-means algorithm and the resultant partition, defined by the cluster centroids, is herein named the noiselet code-book. A part of an image, a tile, is divided into patches and represented by the histogram of occurrences of the projected patches in the noiselet code-book. Finally, with these histograms, a classifier learns to differentiate between nuclei and non-nuclei tiles. By applying a conventional watershed-marked method to detect and segment nuclei, evaluation consisted in comparing pure watershed method against denoising-plus-watershed in an open database with 8 different types of tissues. The averaged F-score of nuclei detection improved from 0.830 to 0.86 and the dice score after segmentation increased from 0.701 to 0.723.

Classifying Malignancy in Prostate Glandular Structures from Biopsy Scans with Deep Learning

Histopathological classification in prostate cancer remains a challenge with high dependence on the expert practitioner. We develop a deep learning (DL) model to identify the most prominent Gleason pattern in a highly curated data cohort and validate it on an independent dataset. The histology images are partitioned in tiles (14,509) and are curated by an expert to identify individual glandular structures with assigned primary Gleason pattern grades. We use transfer learning and fine-tuning approaches to compare several deep neural network architectures that are trained on a corpus of camera images (ImageNet) and tuned with histology examples to be context appropriate for histopathological discrimination with small samples. In our study, the best DL network is able to discriminate cancer grade (GS3/4) from benign with an accuracy of 91%, F₁-score of 0.91 and AUC 0.96 in a baseline test (52 patients), while the cancer grade discrimination of the GS3 from GS4 had an accuracy of 68% and AUC of 0.71 (40 patients).

Ki67 and the apparent diffusion coefficient in postoperative prostate cancer with endocrine therapy

Background

Prostate-specific antigen (PSA) is a critical part of prostate cancer (PCa) screening, diagnosis, staging, and prognosis. However, elevated PSA levels can also be caused by several external factors. To improve the specificity and sensitivity of PSA in clinical practice, we explored whether markers or parameters may be used as prognostic targets for PCa by long-term follow-up.

Methods

A total of 121 PCa patients who underwent laparoscopic radical prostatectomy (LRP) were included in our study, all of whom underwent imaging and preoperative pathological diagnosis. Endocrine therapy has long been applied to treat postoperative patients. The prognosis of enrolled patients was followed, and statistics were collected. Spearman's correlation analysis was applied to examine the relationship and clinical parameters. Kaplan–Meier analysis was used to process the clinical variables of PCa patients. Cox proportional hazards regression analysis was applied to examine univariate and multivariate variables.

Results

The Gleason score (GS), PSA, clinical stage, nerve infiltration, organ confinement, Ki67 and apparent diffusion coefficient (ADC) were significantly associated with prognosis (all P &lt; 0.05). The GS, PSA, clinical stage, organ confined, Ki67, nerve infiltration and ADC were included in the multivariate analysis (all P &lt; 0.05). Ultimately, Ki67 and the ADC were found to provide meaningful predictive information (both P &lt; 0.05).

Conclusions

Ki67 and the ADC may be clinically and analytically valid prognostic biomarkers and imaging parameters in PCa. They may be useful for predicting the prognosis and risk of PCa patients undergoing postoperative routine endocrine therapy.

Prostate Volume Influence on Postoperative Outcomes for Patients Undergoing RARP: A Monocentric Serial Analysis of 500 Cases

Elevated prostate volume is considered to negatively influence postoperative outcomes after robot-assisted radical prostatectomy (RARP). We aim to investigate the influence of prostate volume on readmissions and complications after RARP. Methods: A total of 500 consecutive patients who underwent RARP between April 2019 and August 2022 were included. Patients were dichotomized into two groups using a prostate volume cut-off of 50 mL (small and normal prostate (SNP) n = 314, 62.8%; large prostate n = 186, 37.2%). Demographic, baseline, and perioperative data were analyzed. The postoperative complications and readmission rates within 90 days after RARP were compared between groups. A univariate linear analysis was performed to investigate the association between prostate volume and other relevant outcomes. Results: Patients with larger prostates had a higher IPSS score, and therefore, more relevant LUTS at the baseline. They had higher ASA scores (p = 0.015). They also had more catheter days (mean 6.6 days for SNP vs. 7.5 days for LP) (p = 0.041). All oncological outcomes were similar between the groups. Although statistical analysis showed no significant difference between the groups (p = 0.062), a trend for minor complications in patients with larger prostates, n = 37/186 (19.8%) for the LP group vs. n = 37/314 (11.7%) in the SNP group, was observed. Namely, acute urinary retention and secondary anastomosis insufficiency. Major complications with an SNP (4.4%) and LP (3.7%) (p = 0.708) and readmissions with an SNP (6.25%) and LP (4.2%) (p = 0.814) were infrequent and distributed equally between the groups. In univariate analysis, prostate volume could solely predict a longer console time (p = 0.005). Conclusions: A higher prostate volume appears to have minimal influence on the perioperative course after RARP. It can prolong catheter days and increase the incidence of minor complications such as acute urinary retention. However, it might predict minor changes in operating time. Yet, prostate volume has less influence on major complications, readmissions, or oncological results.

Prostate Cancer: Advances in Genetic Testing and Clinical Implications

The demand for genetic testing (GT) for prostate cancer (PCa) is expanding, but there is limited knowledge about the genetic counseling (GC) needs of men. A strong-to-moderate inherited genetic predisposition causes approximately 5–20% of prostate cancer (PCa). In men with prostate cancer, germline testing may benefit the patient by informing treatment options, and if a mutation is noticed, it may also guide screening for other cancers and have family implications for cascade genetic testing (testing of close relatives for the same germline mutation). Relatives with the same germline mutations may be eligible for early cancer detection strategies and preventive measures. Cascade family testing can be favorable for family members, but it is currently unutilized, and strategies to overcome obstacles like knowledge deficiency, family communication, lack of access to genetic services, and testing expenses are needed. In this review, we will look at the genetic factors that have been linked to prostate cancer, as well as the role of genetic counseling and testing in the early detection of advanced prostate cancer.

Two conflicting guidelines on prostate specific antigen screening in Japan

Japanese urologists need to listen seriously to the opinions of public health physicians and it is necessary to properly inform people of prostate specific antigen screening.

Prognostic value of the pretreatment systemic immune-inflammation index in patients with prostate cancer: a systematic review and meta-analysis

BACKGROUND

The systemic immune-inflammation index (SII) is a novel biomarker to predict the prognosis of some malignant tumors based on neutrophil, platelet, and lymphocyte counts. Evidence is scarce about the prognostic value of SII for prostate cancer patients. This systematic review and meta-analysis was conducted to explore the prognostic value of the SII in prostate cancer.

METHODS

The PubMed, Embase, Web of Science, and Cochrane Library (CENTRAL) databases were searched to determine eligible studies from inception to August 15, 2022. Hazard ratios (HRs) with 95% confidence intervals (CIs) were extracted to pool the results. Statistical analyses were conducted by using Stata 17.0 software.

RESULTS

A total of 12 studies with 8083 patients were included. The quantitative synthesis showed that a high SII was related to poor overall survival (OS) (HR = 1.44, 95% CI 1.23-1.69, p < 0.001). Furthermore, a subgroup analysis showed that a high SII was associated with poor OS in the groups of any ethnicity, tumor type, and cutoff value. An increased SII was also associated with inferior progression-free survival (PFS) (HR = 1.80, 95% CI 1.27-2.56, p = 0.001). In the subgroup analysis, a high SII value was related to poor PFS in Asian patients (HR = 4.03, 95% CI 1.07-15.17, p = 0.04) and a cutoff value > 580 (HR = 1.19, 95% CI 1.04-1.36, p = 0.01).

CONCLUSION

Based on the current evidence, a high pretreatment SII may be associated with poor OS and PFS. The SII may serve as an important prognostic indicator in patients with prostate cancer. More rigorously designed studies are needed to explore the SII and the prognosis of prostate cancer.

Aquaporins as Prognostic Biomarker in Prostate Cancer

Prostate cancer is a complex heterogeneous disease that affects millions of males worldwide. Despite rapid advances in molecular biology and innovation in technology, few biomarkers have been forthcoming in prostate cancer. The currently available biomarkers for the prognosis of prostate cancer are inadequate and face challenges, thus having limited clinical utility. To date, there are a number of prognostic and predictive biomarkers identified for prostate cancer but lack specificity and sensitivity to guide clinical decision making. There is still tremendous scope for specific biomarkers to understand the natural history and complex biology of this heterogeneous disease, and to identify early treatment responses. Accumulative studies indicate that aquaporins (AQPs) a family of membrane water channels may serve as a prognostic biomarker for prostate cancer in monitoring disease advancement. In the present review, we discuss the existing prostate cancer biomarkers, their limitations, and aquaporins as a prospective biomarker of prognostic significance in prostate cancer.

Genomic Characterization of Prostatic Basal Cell Carcinoma

Basal cell carcinoma (BCC) of the prostate is a rare tumor. Compared with the more common acinar adenocarcinoma (AAC) of the prostate, BCCs show features of basal cell differentiation and are thought to be biologically distinct from AAC. The spectrum of molecular alterations of BCC has not been comprehensively described, and genomic studies are lacking. Herein, whole genome sequencing was performed on archival formalin-fixed, paraffin-embedded specimens of two cases with BCC. Prostatic BCCs were characterized by an overall low copy number and mutational burden. Recurrent copy number loss of chromosome 16 was observed. In addition, putative driver gene alterations in KIT, DENND3, PTPRU, MGA, and CYLD were identified. Mechanistically, depletion of the CYLD protein resulted in increased proliferation of prostatic basal cells in vitro. Collectively, these studies show that prostatic BCC displays distinct genomic alterations from AAC and highlight a potential role for loss of chromosome 16 in the pathogenesis of this rare tumor type.

An update on computational pathology tools for genitourinary pathology practice: A review paper from the Genitourinary Pathology Society (GUPS)

Machine learning has been leveraged for image analysis applications throughout a multitude of subspecialties. This position paper provides a perspective on the evolutionary trajectory of practical deep learning tools for genitourinary pathology through evaluating the most recent iterations of such algorithmic devices. Deep learning tools for genitourinary pathology demonstrate potential to enhance prognostic and predictive capacity for tumor assessment including grading, staging, and subtype identification, yet limitations in data availability, regulation, and standardization have stymied their implementation.

Prostate Cancer Treatment-Related Toxicity: Comparison between 3D-Conformal Radiation Therapy (3D-CRT) and Volumetric Modulated Arc Therapy (VMAT) Techniques

Objective: This paper illustrates the results of a mono-institutional registry trial, aimed to test whether gastrointestinal (GI) and genitourinary (GU) toxicity rates were lower in localized prostate cancer patients treated with image-guided volumetric modulated arc therapy (IG-VMAT) compared to those treated with IG-3D conformal radiation therapy (IG-3DCRT). Materials and Methods: Histologically proven prostate cancer patients with organ-confined disease, treated between October 2008 and September 2014 with moderately hypofractionated radiotherapy, were reviewed. Fiducial markers were placed in the prostate gland by transrectal ultrasound guide. The prescribed total dose was 70 Gy in 28 fractions. The mean and median dose volume constraints for bladder and rectum as well as total volume of treatment were analyzed as potentially prognostic factors influencing toxicity. The Kaplan−Meier method was applied to calculate survival. Results: Overall, 83 consecutive patients were included. Forty-two (50.6%) patients were treated with 3D-CRT and 41 (49.4%) with the VMAT technique. The median follow-up for toxicity was 77.26 months for the whole cohort. The VMAT allowed for a dose reduction to the rectum and bladder for the large majority of the considered parameters; nonetheless, the only parameter correlated with a clinical outcome was a rectal dose limit V66 > 8.5% for late GI toxicity G ≥ 2 (p = 0.045). Rates of G ≥ 2 toxicities were low among the whole cohort of these patients treated with IGRT. The analysis for rectum dose volume histograms (DVHs) showed that a severe (grade ≥ 2) late GI toxicity was related with the rectal dose limit V66 > 8.5% (p = 0.045). Conclusions: This study shows that moderate hypofractionation is feasible and safe in patients with intermediate and high-risk prostate cancer. Daily IGRT may decrease acute and late toxicity to organs at risk and improve clinical benefit and disease control rate, cutting down the risk of PTV geographical missing. The adoption of VMAT allows for promising results in terms of OAR sparing and a reduction in toxicity that, also given the small sample, did not reach statistical significance.

Impact of cribriform pattern 4 and intraductal prostatic carcinoma on National Comprehensive Cancer Network (NCCN) and Cancer of Prostate Risk Assessment (CAPRA) patient stratification

Pretreatment classification tools are used in prostate cancer to inform patient management. The effect of cribriform pattern 4 (CC) and intraductal carcinoma (IDC) on such nomograms is still underexplored. We analyzed the Cancer of Prostate Risk Assessment (CAPRA) and National Comprehensive Cancer Network (NCCN) risk scores in cases with and without CC/IDC to assess impact on biochemical recurrence (BCR) and metastases/death of prostate cancer (event free survival-EFS) after prostatectomy. A matched biopsy- prostatectomy cohort (2010-2017) was reviewed for CC/IDC. CAPRA and NCCN scores were calculated. CAPRA score 0-2 were deemed "low", 3-5 "intermediate" and 6-10 "high". NCCN scores 1-2 "very low/low", 3 "favorable intermediate", 4 "unfavorable intermediate", 5-6 "high/very high". Cases were stratified by presence of CC/IDC. BCR and EFS probabilities were estimated using the Kaplan-Meier method. Prognostic performance was evaluated using log-rank tests and Harrell's concordance index. 612 patients with mean age 63.1 years were included with mean follow up of 5.3 (range 0-10.8) years. CC/IDC was noted in 159/612 (26%) biopsies. There were 101 (17%) BCR and 36 (6%) events. CAPRA discriminated three distinct risk categories for BCR (p < 0.001) while only high risk separated significantly for EFS (p < 0.001). NCCN distinguished two prognostic groups for BCR (p < 0.0001) and three for EFS (p < 0.0001). Addition of CC/IDC to CAPRA impacted scores 3-5 for BCR and scores 3-5 and 6-10 for EFS and improved the overall concordance index (BCR: 0.66 vs. 0.71; EFS: 0.74 vs. 0.80). Addition of CC/IDC to NCCN impacted scores 4 and 5-6 and also improved the concordance index for BCR (0.62 vs. 0.68). Regarding EFS, NCCN scores 4 and 5-6 demonstrated markedly different outcomes with the addition of CC/IDC. The CAPRA nomogram allows better outcome stratification than NCCN. Addition of CC/IDC status particularly improves patient stratification for CAPRA scores 3-5, 6-10, and for NCCN scores 4 and 5-6.

Design, Synthesis and Biological Evaluation of Novel and Potent Protein Arginine Methyltransferases 5 Inhibitors for Cancer Therapy

Protein arginine methyltransferases 5 (PRMT5) is a clinically promising epigenetic target that is upregulated in a variety of tumors. Currently, there are several PRMT5 inhibitors under preclinical or clinical development, however the established clinical inhibitors show favorable toxicity. Thus, it remains an unmet need to discover novel and structurally diverse PRMT5 inhibitors with characterized therapeutic utility. Herein, a series of tetrahydroisoquinoline (THIQ) derivatives were designed and synthesized as PRMT5 inhibitors using GSK-3326595 as the lead compound. Among them, compound 20 (IC₅₀: 4.2 nM) exhibits more potent PRMT5 inhibitory activity than GSK-3326595 (IC₅₀: 9.2 nM). In addition, compound 20 shows high anti-proliferative effects on MV-4-11 and MDA-MB-468 tumor cells and low cytotoxicity on AML-12 hepatocytes. Furthermore, compound 20 possesses acceptable pharmacokinetic profiles and displays considerable in vivo antitumor efficacy in a MV-4-11 xenograft model. Taken together, compound 20 is an antitumor compound worthy of further study.

Fusing hand-crafted and deep-learning features in a convolutional neural network model to identify prostate cancer in pathology images

Prostate cancer can be diagnosed by prostate biopsy using transectal ultrasound guidance. The high number of pathology images from biopsy tissues is a burden on pathologists, and analysis is subjective and susceptible to inter-rater variability. The use of machine learning techniques could make prostate histopathology diagnostics more precise, consistent, and efficient overall. This paper presents a new classification fusion network model that was created by fusing eight advanced image features: seven hand-crafted features and one deep-learning feature. These features are the scale-invariant feature transform (SIFT), speeded up robust feature (SURF), oriented features from accelerated segment test (FAST) and rotated binary robust independent elementary features (BRIEF) (ORB) of local features, shape and texture features of the cell nuclei, the histogram of oriented gradients (HOG) feature of the cavities, a color feature, and a convolution deep-learning feature. Matching, integrated, and fusion networks are the three essential components of the proposed deep-learning network. The integrated network consists of both a backbone and an additional network. When classifying 1100 prostate pathology images using this fusion network with different backbones (ResNet-18/50, VGG-11/16, and DenseNet-121/201), we discovered that the proposed model with the ResNet-18 backbone achieved the best performance in terms of the accuracy (95.54%), specificity (93.64%), and sensitivity (97.27%) as well as the area under the receiver operating characteristic curve (98.34%). However, each of the assessment criteria for these separate features had a value lower than 90%, which demonstrates that the suggested model combines differently derived characteristics in an effective manner. Moreover, a Grad-CAM++ heatmap was used to observe the differences between the proposed model and ResNet-18 in terms of the regions of interest. This map showed that the proposed model was better at focusing on cancerous cells than ResNet-18. Hence, the proposed classification fusion network, which combines hand-crafted features and a deep-learning feature, is useful for computer-aided diagnoses based on pathology images of prostate cancer. Because of the similarities in the feature engineering and deep learning for different types of pathology images, the proposed method could be used for other pathology images, such as those of breast, thyroid cancer.

Increased Density of Growth Differentiation Factor-15+ Immunoreactive M1/M2 Macrophages in Prostate Cancer of Different Gleason Scores Compared with Benign Prostate Hyperplasia

Simple Summary

Prostate cancer (PCa) is the second most diagnosed cancer and cause of death in men worldwide. The main challenge is to discover biomarkers for malignancy to guide the physician towards optimized diagnosis and therapy. There is recent evidence that growth differentiation factor-15 (GDF-15) is elevated in cancer patients. Therefore, we aimed to decipher GDF-15+ cell types and their density in biopsies of human PCa patients with Gleason score (GS)6–9 and benign prostate hyperplasia (BPH). Here we show that the density of GDF-15+ cells, mainly identified as interstitial macrophages (MΦ), was higher in GS6–9 than in BPH, and, thus, GDF-15 is intended to differentiate patients with high GS vs. BPH, as well as GS6 vs. GS7 (or even with higher malignancy). Some GDF-15+ MΦ showed a transepithelial migration into the glandular lumen and, thus, might be used for measurement in urine/semen. Taken together, GDF-15 is proposed as a novel tool to diagnose PCa vs. BPH or malignancy (GS6 vs. higher GS) and as a potential target for anti-tumor therapy. GDF-15 in seminal plasma and/or urine could be utilized as a non-invasive biomarker of PCa as compared to BPH.

Abstract

Although growth differentiation factor-15 (GDF-15) is highly expressed in PCa, its role in the development and progression of PCa is unclear. The present study aims to determine the density of GDF-15+ cells and immune cells (M1-/M2 macrophages [MΦ], lymphocytes) in PCa of different Gleason scores (GS) compared to BPH. Immunohistochemistry and double immunofluorescence were performed on paraffin-embedded human PCa and BPH biopsies with antibodies directed against GDF-15, CD68 (M1 MΦ), CD163 (M2 MΦ), CD4, CD8, CD19 (T /B lymphocytes), or PD-L1. PGP9.5 served as a marker for innervation and neuroendocrine cells. GDF-15+ cell density was higher in all GS than in BPH. CD68+ MΦ density in GS9 and CD163+ MΦ exceeded that in BPH. GDF-15+ cell density correlated significantly positively with CD68+ or CD163+ MΦ density in extratumoral areas. Double immunoreactive GDF-15+/CD68+ cells were found as transepithelial migrating MΦ. Stromal CD68+ MΦ lacked GDF-15+. The area of PGP9.5+ innervation was higher in GS9 than in BPH. PGP9.5+ cells, occasionally copositive for GDF-15+, also occurred in the glandular epithelium. In GS6, but not in BPH, GDF-15+, PD-L1+, and CD68+ cells were found in epithelium within luminal excrescences. The degree of extra-/intra-tumoral GDF-15 increases in M1/M2Φ is proposed to be useful to stratify progredient malignancy of PCa. GDF-15 is a potential target for anti-tumor therapy.

Deep UV Microscopy Identifies Prostatic Basal Cells: An Important Biomarker for Prostate Cancer Diagnostics

Objective and Impact Statement. Identifying benign mimics of prostatic adenocarcinoma remains a significant diagnostic challenge. In this work, we developed an approach based on label-free, high-resolution molecular imaging with multispectral deep ultraviolet (UV) microscopy which identifies important prostate tissue components, including basal cells. This work has significant implications towards improving the pathologic assessment and diagnosis of prostate cancer. Introduction. One of the most important indicators of prostate cancer is the absence of basal cells in glands and ducts. However, identifying basal cells using hematoxylin and eosin (H&E) stains, which is the standard of care, can be difficult in a subset of cases. In such situations, pathologists often resort to immunohistochemical (IHC) stains for a definitive diagnosis. However, IHC is expensive and time-consuming and requires more tissue sections which may not be available. In addition, IHC is subject to false-negative or false-positive stains which can potentially lead to an incorrect diagnosis. Methods. We leverage the rich molecular information of label-free multispectral deep UV microscopy to uniquely identify basal cells, luminal cells, and inflammatory cells. The method applies an unsupervised geometrical representation of principal component analysis to separate the various components of prostate tissue leading to multiple image representations of the molecular information. Results. Our results show that this method accurately and efficiently identifies benign and malignant glands with high fidelity, free of any staining procedures, based on the presence or absence of basal cells. We further use the molecular information to directly generate a high-resolution virtual IHC stain that clearly identifies basal cells, even in cases where IHC stains fail. Conclusion. Our simple, low-cost, and label-free deep UV method has the potential to improve and facilitate prostate cancer diagnosis by enabling robust identification of basal cells and other important prostate tissue components.

Developments in proton MR spectroscopic imaging of prostate cancer

In this paper, we review the developments of 1H-MR spectroscopic imaging (MRSI) methods designed to investigate prostate cancer, covering key aspects such as specific hardware, dedicated pulse sequences for data acquisition and data processing and quantification techniques. Emphasis is given to recent advancements in MRSI methodologies, as well as future developments, which can lead to overcome difficulties associated with commonly employed MRSI approaches applied in clinical routine. This includes the replacement of standard PRESS sequences for volume selection, which we identified as inadequate for clinical applications, by sLASER sequences and implementation of 1H MRSI without water signal suppression. These may enable a new evaluation of the complementary role and significance of MRSI in prostate cancer management.

The Role of Androgen Receptor Expression in Prostate Adenocarcinoma

Prostate cancer is one of the most common cancer worldwide, where South Sulawesi is included in four provinces with the highest prevalence of prostate cancer in Indonesia. Laboratorium Sentra Patologia Makassar (SDPM) stated that prostate cancer cases continue to rise each year. Androgen receptor (AR) plays a role in the growth and differentiation of male urogenital structures, both under normal and neoplastic conditions, the neoplastic condition is caused by the mechanism of the AR pathway which undergoes changes that continue in the development and progression of prostate lesions, both benign and malignant. Androgen receptors are generally found evenly distributed in the nuclei of glandular and stromal cells in prostate hyperplasia and vary widely in prostate cancer. These inventions show that AR inhibitors are used to treat prostate adenocarcinoma by inhibiting androgen synthesis. Assessment of AR expression can be used in determining therapy and predicting the success of hormonal therapy so that the prognosis of the disease is better. This study is conducted to learn more about AR expression in adenocarcinoma prostate grading. The type of this research is an observational analytical study with cross-sectional methods. Samples are taken based on consecutive sampling of as many as 77 respondents. There is a significant difference between AR expression score and histopathological feature of prostate adenocarcinoma WHO Grup Grade (p<0,001). In conclusion, there is a significant correlation between AR and WHO Grup Grade and could be used as important marker in grading adenocarcinoma prostate progression Keywords : Androgen receptor (AR); prostate adenocarcinoma; WHO Grup Grade

Cribriform Patterned Lesions in the Prostate Gland with Emphasis on Differential Diagnosis and Clinical Significance

Simple Summary

A cribriform structure is defined as a continuous proliferation of cells with intermingled lumina. Various entities may have a cribriform morphology within the prostate gland, ranging from normal, to benign, to borderline and even to malignant lesions. This review summarizes the morphologic features of entities that have a cribriform morphology within the prostate gland, with an emphasis on their differential diagnosis, molecular profile and clinical significance. The basic aim is to assist the pathologist with challenging and controversial cases and inform the clinician on the clinical implications of cribriform morphology.

Abstract

Cribriform glandular formations are characterized by a continuous proliferation of cells with intermingled lumina and can constitute a major or minor part of physiologic (normal central zone glands), benign (clear cell cribriform hyperplasia and basal cell hyperplasia), premalignant (high-grade prostatic intraepithelial neoplasia), borderline (atypical intraductal cribriform proliferation) or clearly malignant (intraductal, acinar, ductal and basal cell carcinoma) lesions. Each displays a different clinical course and variability in clinical management and prognosis. The aim of this review is to summarize the current knowledge regarding the morphological features, differential diagnosis, molecular profile and clinical significance of the cribriform-patterned entities of the prostate gland. Areas of controversy regarding their management, i.e., the grading of Intaductal Carcinoma, will also be discussed. Understanding the distinct nature of each cribriform lesion leads to the correct diagnosis and ensures accuracy in clinical decision-making, prognosis prediction and personalized risk stratification of patients.

Molecular mechanisms of ferroptosis and its role in prostate cancer therapy

Prostate cancer (PCa) is a highly prevalent disease that affects men's health worldwide and is the second most common malignancy in males. Ferroptosis is a novel form of programmed cell death characterized by iron overload and the accumulation of lipid peroxidation, which differs from the regulated cell death modes of necrosis, apoptosis, and autophagy. Substantial progress has been achieved in researching the occurrence and regulatory mechanisms of ferroptosis, which is closely associated with cancer initiation, progression, and suppression and is expected to become a new breakthrough point in the PCa treatment. This review will summarize the mechanisms involved in PCa, and we detail the molecular mechanisms of ferroptosis and its role in PCa treatment.

Clinical Utility of Next-generation Sequencing in Real-world Cases: A Single-institution Study of Nine Cases

BACKGROUND/AIM

Targeted next-generation sequencing (NGS) is a well-established technique to detect pathogenic alterations in tumors. Indeed, it is the cornerstone of targeted therapy in precision medicine. We investigated the clinical utility of next-generation sequencing in real-world cases.

PATIENTS AND METHODS

We retrospectively selected six representative cancer cases, wherein targeted NGS played a pivotal role in the diagnosis and treatment of patients. Additionally, we analyzed three cases with rare, unusual pathogenic alterations.

RESULTS

Our NGS analysis revealed that four patients had TPR-ROS1, EGFR-RAD51, and NCOA4-RET fusions and MET exon 14 skipping mutation, respectively, which can be treated with targeted therapy. Furthermore, we used NGS as a diagnostic tool to confirm the origin of unknown primary malignant tumors in two cases. Interestingly, NGS also helped us identify the following cases: patients exhibiting BRCA1 and TP53 mutations that exhibited histological and immunohistochemical characteristics consistent with endometrioid carcinoma, patients with high-grade serous carcinoma not possessing a TP53 mutation, and patients with small cell lung cancer with a ERBB2 mutation and displaying no loss of RB1.

CONCLUSION

We recommend targeted NGS for the diagnoses and targeted therapy of cancer patients.