Manzamine A reduces androgen receptor transcription and synthesis by blocking E2F8-DNA interactions and effectively inhibits prostate tumor growth in mice.

The androgen receptor (AR) is the main driver in the development of castration-resistant prostate cancer, where the emergence of AR splice variants leads to treatment-resistant disease. Through detailed molecular studies of the marine alkaloid manzamine A (MA), we identified transcription factor E2F8 as a previously unknown regulator of AR transcription that prevents AR synthesis in prostate cancer cells. MA significantly inhibited the growth of various prostate cancer cell lines and was highly effective in inhibiting xenograft tumor growth in mice without any pathophysiological perturbations in major organs. MA suppressed the full-length AR (AR-FL), its spliced variant AR-V7, and the AR-regulated prostate-specific antigen (PSA; also known as KLK3) and human kallikrein 2 (hK2; also known as KLK2) genes. RNA sequencing (RNA-seq) analysis and protein modeling studies revealed E2F8 interactions with DNA as a potential novel target of MA, suppressing AR transcription and its synthesis. This novel mechanism of blocking AR biogenesis via E2F8 may provide an opportunity to control therapy-resistant prostate cancer over the currently used AR antagonists designed to target different parts of the AR gene.

Morphologic features of prostate cancer-encased native vessels: An image analysis study.

BACKGROUND: Vasculature plays a crucial role in the progression of prostate cancer (PC). Changes to the prostatic native vessels have not been studied since 2000 when Garcia et al. demonstrated marked media hypercellularity and increased artery thickness in prostatic native arteries within PC. We aim to further evaluate and characterize prostatic native vessels with a more accurate method with the use of virtual slides and digital analysis. DESIGN: Pathologist-annotated whole-mount digital slides from 96 entirely submitted prostatectomies were annotated for PC (color-coded by Gleason) using Omero platform. A subset of 44 cases met criteria for further analysis of media thickness, cellularity, and wall thickness to lumen ratio. Cases were included based on containing ≥5 native arteries (≥100 µm diameter) encased on at least 3 sides by PC, with vessels (≥100 µm diameter) designated as controls if they were ≥ 1000 µm away from PC. Annotated vessels were segmented and processed using Matlab 2023b. Mean media thickness (corrected for oblique sections), media: lumen ratio (based on numbers of pixels), and media cellularity (nuclei count) were studied by analysis with SPSS by linear mixed model with nested random effects for subject and slide to account for repeated measures. RESULTS: Vessels encased by PC showed greater media thickness (p=0.02), cellularity (p=0.02) and wall thickness/lumen ratio (p= <0.001) compared to vessels away from PC. These values showed an increasing trend according to stage in cellularity (p=0.14), media thickness (p=0.12) and wall thickness/ lumen ratio (p= 0.33) with higher stage (pT3). A Gleason group comparison showed a borderline-significant gradewise trend when analyzing wall thickness/lumen ratio (p=0.06). Grade 5 emerged as significantly different (p=0.02) from grades 3 or 4 non-cribriform. CONCLUSIONS: Similar to the 2000 study, increased media thickness and hypercellularity of vessels encased by PC were evident compared to controls. Borderline grade-dependent increased vessel cellularity changes were seen, suggesting a possible role in PC progression; the predictive value of these changes for outcome is uncertain. Whether the etiology of changes reflects locally increased intravascular pressure of vessels within tumor should be investigated.

Addition of cribriform pattern 4 and intraductal prostatic carcinoma into the CAPRA-S tool improves post-radical prostatectomy patient stratification in a multi-institutional cohort.

AIMS: Pre-surgical risk classification tools for prostate cancer have shown better patient stratification with the addition of cribriform pattern 4 (CC) and intraductal prostatic carcinoma (IDC) identified in biopsies. Here, we analyse the additional prognostic impact of CC/IDC observed in prostatectomies using Cancer of Prostate Risk Assessment post-surgical (CAPRA-S) stratification. METHODS: A retrospective cohort of treatment-naïve radical prostatectomy specimens from three North American academic institutions (2010-2018) was assessed for the presence of CC/IDC. Patients were classified, after calculating the CAPRA-S scores, into low-risk (0-2), intermediate-risk (3-5) and high-risk (6-12) groups. Kaplan-Meier curves were created to estimate biochemical recurrence (BCR)-free survival. Prognostic performance was examined using Harrell's concordance index, and the effects of CC/IDC within each risk group were evaluated using the Cox proportional hazards models. RESULTS: Our cohort included 825 prostatectomies (grade group (GG)1, n=94; GG2, n=475; GG3, n=185; GG4, n=13; GG5, n=58). CC/IDC was present in 341 (41%) prostatectomies. With a median follow-up of 4.2 years (range 2.9-6.4), 166 (20%) patients experienced BCR. The CAPRA-S low-risk, intermediate-risk and high-risk groups comprised 357 (43%), 328 (40%) and 140 (17%) patients, and discriminated for BCR-free survival (p<0.0001). For CAPRA-S scores 3-5, the addition of CC/IDC status improved stratification for BCR (HR 2.27, 95% CI 1.41 to 3.66, p<0.001) and improved the overall c-index (0.689 vs 0.667, analysis of variance p<0.001). CONCLUSION: The addition of CC/IDC into the CAPRA-S classification significantly improved post-radical prostatectomy patient stratification for BCR among the intermediate-risk group (CAPRA-S scores 3-5). The reporting of CC and IDC should be included in future prostate cancer stratification tools for improved outcome prediction.

Stat5 induces androgen receptor (AR) gene transcription in prostate cancer and offers a druggable pathway to target AR signaling.

Androgen receptor (AR) drives prostate cancer (PC) growth and progression, and targeting AR signaling is the mainstay of pharmacological therapies for PC. Resistance develops relatively fast as a result of refueled AR activity. A major gap in the field is the lack of understanding of targetable mechanisms that induce persistent AR expression in castrate-resistant PC (CRPC). This study uncovers an unexpected function of active Stat5 signaling, a known promoter of PC growth and clinical progression, as a potent inducer of AR gene transcription. Stat5 suppression inhibited AR gene transcription in preclinical PC models and reduced the levels of wild-type, mutated, and truncated AR proteins. Pharmacological Stat5 inhibition by a specific small-molecule Stat5 inhibitor down-regulated Stat5-inducible genes as well as AR and AR-regulated genes and suppressed PC growth. This work introduces the concept of Stat5 as an inducer of AR gene transcription in PC. Pharmacological Stat5 inhibitors may represent a new strategy for suppressing AR and CRPC growth.

Addition of Cribriform and Intraductal Carcinoma Presence to Prostate Biopsy Reporting Strengthens Pretreatment Risk Stratification Using CAPRA and NCCN Tools.

BACKGROUND: Pretreatment stratification tools can help in clinical decision making in prostate cancer. To date, none incorporates well-established routinely reported adverse prognostic pathologic features such as intraductal carcinoma of prostate (IDC) or cribriform pattern 4 (CC). OBJECTIVE: To assess the impact of addition of CC and/or IDC on the Cancer of Prostate Risk Assessment (CAPRA) and National Cancer Comprehensive Network (NCCN) tools for predicting biochemical recurrence free survival (BCR-FS) and event-free survival (EFS) across multiple patient cohorts. DESIGN, SETTING, AND PARTICIPANTS: Matched prostate biopsies and radical prostatectomies from institutions in Toronto, Wisconsin and Rotterdam. The presence/absence of CC/IDC was recorded on all biopsies. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Relationship to outcome was assessed using Cox proportional hazard models, ANOVA and Harrell's concordance index. RESULTS AND LIMITATIONS: We included 1326 patients (Toronto- 612, Wisconsin- 542, Rotterdam- 172) with median follow up of 4.2 years (IQR 2.9-6.4 years); 306 (23.1%) had CC/IDC on biopsy with 207 (20.9%) BCR and 154 (11.6%) events (metastases/death). Addition of CC/IDC improved stratification in CAPRA scores 3 to 5 for BCR-FS (c-index increase 0.633-0.658, P < .001) and scores 6-10 for EFS (c-index increase 0.653-0.697, P < .001). For NCCN, all risk groups apart from score 1 to 2 showed improvement in BCR-FS (c-index increase 0.599-0.636, P < 0.001) and EFS prediction (c-index increase 0.648-0.697, P < .001). Sub-analysis of grade group (GG) 2 biopsies showed similar findings. The retrospective nature and inclusion of cases only reported by genitourinary pathologists are study limitations. CONCLUSIONS: The clinical benefit of the addition of CC/IDC to both CAPRA and NCCN pretreatment tools was validated in 3 cohorts, including the subset of biopsy GG2 prostate cancer patients. PATIENT SUMMARY: Including additional pathologic features to existing pretreatment, clinical decision making tools improves the ability to predict prostate cancer recurrence, cancer spread and death of disease.

Gleason score 3+3=6 prostatic adenocarcinoma is not benign and the current debate is unhelpful to clinicians and patients.

Prostate adenocarcinoma is a common malignancy associated with a significant morbidity and mortality. In both prostate biopsies and radical prostatectomy specimens Gleason scoring informs both treatment and outcome prediction. The current convention is that in needle biopsies, Gleason patterns 3, 4 and 5 are considered to be malignant. Despite this there is debate as to whether or not Gleason score (GS) 3+3=6 should be diagnosed as cancer due to potential over-treatment and the psychological impact on patients. It is apparent that GS 3+3=6 is indolent disease with a low risk of metastasis. However, it does have the histological features of malignancy and is capable of infiltrating the prostate gland, extraprostatic extension, and metastatic spread. Furthermore GS 3+3=6 carcinoma has immunohistochemical and molecular genetic features similar to those of higher grade prostatic carcinoma. If GS 3+3=6 tumour is considered benign, the question arises should a benign label be given to the Gleason pattern 3 component of tumour that includes Gleason patterns of higher grade? This would seem a logical step as GS 3+3=6 cancers and the pattern 3 component in cancers with multiple patterns are morphologically identical. If pattern 3 is considered to be benign, then Gleason scoring would be limited to 4+4=8, 4+5=9, 5+4=9 and 5+5=10 which is clearly inappropriate. The correct strategy to address potential over-treatment of patients with low-grade cancer is clinician and patient education, not the recalibration of Gleason grading to reclassify malignant tumours as benign.

International Society of Urological Pathology (ISUP) Consensus Conference on Current Issues in Bladder Cancer: Working Group 3: Subcategorization of T1 Bladder Cancer.

Emerging data on T1 bladder cancer subcategorization (aka substaging) suggests a correlation with oncological outcomes. The International Society of Urological Pathology (ISUP) organized the 2022 consensus conference in Basel, Switzerland to focus on current issues in bladder cancer and tasked working group 3 to make recommendations for T1 subcategorization in transurethral bladder resections. For this purpose, the ISUP developed and circulated a survey to their membership querying approaches to T1 bladder cancer subcategorization. In particular, clinical relevance, pathological reporting, and endorsement of T1 subcategorization in the daily practice of pathology were surveyed. Of the respondents of the premeeting survey, about 40% do not routinely report T1 subcategory. We reviewed literature on bladder T1 subcategorization, and screened selected articles for clinical performance and practicality of T1 subcategorization methods. Published literature offered evidence of the clinical rationale for T1 subcategorization and at the conference consensus (83% of conference attendants) was obtained to report routinely T1 subcategorization of transurethral resections. Semiquantitative T1 subcategorization was favored (37%) over histoanatomic methods (4%). This is in line with literature findings on practicality and prognostic impact, that is, a shift of publications from histoanatomic to semiquantitative methods or by reports incorporating both methodologies is apparent over the last decade. However, 59% of participants had no preference for either methodology. They would add a comment in the report briefly stating applied method, interpretation criteria (including cutoff), and potential limitations. When queried on the terminology of T1 subcategorization, 34% and 20% of participants were in favor of T1 (microinvasive) versus T1 (extensive) or T1 (focal) versus T1 (nonfocal), respectively.

Quantitative Histomorphometric Features of Prostate Cancer Predict Patients Who Biochemically Recur Following Prostatectomy.

Prostate cancer is the most commonly diagnosed cancer in men, accounting for 27% of the new male cancer diagnoses in 2022. If organ-confined, removal of the prostate through radical prostatectomy is considered curative; however, distant metastases may occur, resulting in a poor patient prognosis. This study sought to determine whether quantitative pathomic features of prostate cancer differ in patients who biochemically experience biological recurrence after surgery. Whole-mount prostate histology from 78 patients was analyzed for this study. In total, 614 slides were hematoxylin and eosin stained and digitized to produce whole slide images (WSI). Regions of differing Gleason patterns were digitally annotated by a genitourinary fellowship-trained pathologist, and high-resolution tiles were extracted from each annotated region of interest for further analysis. Individual glands within the prostate were identified using automated image processing algorithms, and histomorphometric features were calculated on a per-tile basis and across WSI and averaged by patients. Tiles were organized into cancer and benign tissues. Logistic regression models were fit to assess the predictive value of the calculated pathomic features across tile groups and WSI; additionally, models using clinical information were used for comparisons. Logistic regression classified each pathomic feature model at accuracies >80% with areas under the curve of 0.82, 0.76, 0.75, and 0.72 for all tiles, cancer only, noncancer only, and across WSI. This was comparable with standard clinical information, Gleason Grade Groups, and CAPRA score, which achieved similar accuracies but areas under the curve of 0.80, 0.77, and 0.70, respectively. This study demonstrates that the use of quantitative pathomic features calculated from digital histology of prostate cancer may provide clinicians with additional information beyond the traditional qualitative pathologist assessment. Further research is warranted to determine possible inclusion in treatment guidance.

Racial differences in serum chemokines in prostate cancer patients.

BACKGROUND: This study aimed to understand the differential levels of inflammatory chemokines in association with higher prostate cancer incidence and mortality in African American (AA) men than in Caucasians (CA). METHODS: The authors used a chemokine assay to simultaneously measure 40 chemokines and cytokines levels in the serum of preoperative prostate cancer patients and healthy controls of AA and CA races. Selected chemokines (CXCL2, CXCL5, and CCL23) serum level was validated in 211 serum samples from prostate cancer patients and healthy controls. Differential expression of CXCL5 and CCL23 was analyzed using immunohistochemistry in a representative cohort of prostate tumor tissues of AA and CA races. RESULTS: Race-specific comparisons from 211 serum samples showed significantly higher levels of CXCL2 (control: 3104.0 pg/mL vs. cancer: 2451.0 pg/mL) and CXCL5 (control: 5189.0 pg/mL vs. cancer: 5459.0 pg/mL) in AA men than in CAs (CXCL2; control: 1155.0 pg/mL vs. cancer: 889.3 pg/mL, and CXCL5; control: 1183.0 pg/mL vs. cancer: 977.5 pg/mL). CCL23 differed significantly within and between the races with a lower level in AA cancer cases (454.5 vs. 966.6 pg/mL) than healthy controls (740.5 vs. 1263.0 pg/mL). Patient age, prostate-specific antigen, or Gleason scores were not significantly associated with these chemokines. Immunostaining for CXCL5 and CCL23 in a representative cohort of archival prostate tissues displayed significantly higher CXCL5 in prostate tumors than in adjacent benign tissues, whereas CCL23 was nondetectable in most of the analyzed tumor tissues. CONCLUSION: Lower levels of CCL23 in AA prostate cancer patient sera and tumor tissues and high CXCL2 and CXCL5 may contribute to aggressive prostate cancer, as often seen in AA men. The disproportionate levels of serum chemokines associated with race warrant further exploration to improve equitability in precision oncology to benefit prostate cancer patients.

T2-Weighted MRI Radiomic Features Predict Prostate Cancer Presence and Eventual Biochemical Recurrence.

Prostate cancer (PCa) is the most diagnosed non-cutaneous cancer in men. Despite therapies such as radical prostatectomy, which is considered curative, distant metastases may form, resulting in biochemical recurrence (BCR). This study used radiomic features calculated from multi-parametric magnetic resonance imaging (MP-MRI) to evaluate their ability to predict BCR and PCa presence. Data from a total of 279 patients, of which 46 experienced BCR, undergoing MP-MRI prior to surgery were assessed for this study. After surgery, the prostate was sectioned using patient-specific 3D-printed slicing jigs modeled using the T2-weighted imaging (T2WI). Sectioned tissue was stained, digitized, and annotated by a GU-fellowship trained pathologist for cancer presence. Digitized slides and annotations were co-registered to the T2WI and radiomic features were calculated across the whole prostate and cancerous lesions. A tree regression model was fitted to assess the ability of radiomic features to predict BCR, and a tree classification model was fitted with the same radiomic features to classify regions of cancer. We found that 10 radiomic features predicted eventual BCR with an AUC of 0.97 and classified cancer at an accuracy of 89.9%. This study showcases the application of a radiomic feature-based tool to screen for the presence of prostate cancer and assess patient prognosis, as determined by biochemical recurrence.

Whole slide imaging (WSI) scanner differences influence optical and computed properties of digitized prostate cancer histology.

Purpose: Digital pathology is becoming an increasingly popular area of advancement in both research and clinically. Pathologists are now able to manage and interpret slides digitally, as well as collaborate with external pathologists with digital copies of slides. Differences in slide scanners include variation in resolution, image contrast, and optical properties, which may influence downstream image processing. This study tested the hypothesis that varying slide scanners would result in differences in computed pathomic features on prostate cancer whole mount slides. Design: This study collected 192 unique tissue slides from 30 patients following prostatectomy. Tissue samples were paraffin-embedded, stained for hematoxylin and eosin (H&E), and digitized using 3 different scanning microscopes at the highest available magnification rate, for a total of 3 digitized slides per tissue slide. These scanners included a (S1) Nikon microscope equipped with an automated sliding stage, an (S2) Olympus VS120 slide scanner, and a (S3) Huron TissueScope LE scanner. A color deconvolution algorithm was then used to optimize contrast by projecting the RGB image into color channels representing optical stain density. The resulting intensity standardized images were then computationally processed to segment tissue and calculate pathomic features including lumen, stroma, epithelium, and epithelial cell density, as well as second-order features including lumen area and roundness; epithelial area, roundness, and wall thickness; and cell fraction. For each tested feature, mean values of that feature per digitized slide were collected and compared across slide scanners using mixed effect models, fit to compare differences in the tested feature associated with all slide scanners for each slide, including a random effect of subject with a nested random effect of slide to account for repeated measures. Similar models were also computed for tissue densities to examine how differences in scanner impact downstream processing. Results: Each mean color channel intensity (i.e., Red, Green, Blue) differed between slide scanners (all P<.001). Of the color deconvolved images, only the hematoxylin channel was similar in all 3 scanners (all P>.05). Lumen and stroma densities between S3 and S1 slides, and epithelial cell density between S3 and S2 (P>.05) were comparable but all other comparisons were significantly different (P<.05). The second-order features were found to be comparable for all scanner comparisons, except for lumen area and epithelium area. Conclusion: This study demonstrates that both optical and computed properties of digitized histological samples are impacted by slide scanner differences. Future research is warranted to better understand which scanner properties influence the tissue segmentation process and to develop harmonization techniques for comparing data across multiple slide scanners.

The DACH1 gene is frequently deleted in prostate cancer, restrains prostatic intraepithelial neoplasia, decreases DNA damage repair, and predicts therapy responses.

Prostate cancer (PCa), the second leading cause of death in American men, includes distinct genetic subtypes with distinct therapeutic vulnerabilities. The DACH1 gene encodes a winged helix/Forkhead DNA-binding protein that competes for binding to FOXM1 sites. Herein, DACH1 gene deletion within the 13q21.31-q21.33 region occurs in up to 18% of human PCa and was associated with increased AR activity and poor prognosis. In prostate OncoMice, prostate-specific deletion of the Dach1 gene enhanced prostatic intraepithelial neoplasia (PIN), and was associated with increased TGFß activity and DNA damage. Reduced Dach1 increased DNA damage in response to genotoxic stresses. DACH1 was recruited to sites of DNA damage, augmenting recruitment of Ku70/Ku80. Reduced Dach1 expression was associated with increased homology directed repair and resistance to PARP inhibitors and TGFß kinase inhibitors. Reduced Dach1 expression may define a subclass of PCa that warrants specific therapies.

Comparison of a machine and deep learning model for automated tumor annotation on digitized whole slide prostate cancer histology.

One in eight men will be affected by prostate cancer (PCa) in their lives. While the current clinical standard prognostic marker for PCa is the Gleason score, it is subject to inter-reviewer variability. This study compares two machine learning methods for discriminating between cancerous regions on digitized histology from 47 PCa patients. Whole-slide images were annotated by a GU fellowship-trained pathologist for each Gleason pattern. High-resolution tiles were extracted from annotated and unlabeled tissue. Patients were separated into a training set of 31 patients (Cohort A, n = 9345 tiles) and a testing cohort of 16 patients (Cohort B, n = 4375 tiles). Tiles from Cohort A were used to train a ResNet model, and glands from these tiles were segmented to calculate pathomic features to train a bagged ensemble model to discriminate tumors as (1) cancer and noncancer, (2) high- and low-grade cancer from noncancer, and (3) all Gleason patterns. The outputs of these models were compared to ground-truth pathologist annotations. The ensemble and ResNet models had overall accuracies of 89% and 88%, respectively, at predicting cancer from noncancer. The ResNet model was additionally able to differentiate Gleason patterns on data from Cohort B while the ensemble model was not. Our results suggest that quantitative pathomic features calculated from PCa histology can distinguish regions of cancer; however, texture features captured by deep learning frameworks better differentiate unique Gleason patterns.

Zinc finger protein­like 1 is a novel neuroendocrine biomarker for prostate cancer.

Prostate­derived calcitonin (CT) and its receptor induce tumorigenicity and increase metastatic potential of prostate cancer (PC). CT­inducible genes in human prostate were identified by subtraction hybridization. Among these genes, zinc finger protein like 1 (ZFPL1) protein was interesting since it was abundantly expressed in malignant prostates but was almost absent in benign prostates. ZFPL1 expression was upregulated by CT and androgens, and ZFPL1 protein was secreted by prostate tumor cells through exosomal secretion. Serum levels of ZFPL1 in cancer patients were at least 4­fold higher than those in the sera of cancer­free individuals. Cell biology of ZFPL1 suggests its localization in Golgi bodies and exosomes, and its colocalization with chromogranin A and CD44. These results suggested that ZFPL1 is secreted by tumor cells of neuroendocrine (NE)/stem cell phenotype. The knockdown of endogenous ZFPL1 in (PC) cells led to a remarkable decrease in cell proliferation, and invasion while increasing their apoptosis. As expected, the overexpression of ZFPL1 in prostate cells had an opposite effect on these functions. The knockdown of ZFPL1 in PC cells also decreased Akt phosphorylation, suggesting the actions of ZFPL1 may be mediated through the PI3K­Akt pathway. Moreover, the present results revealed that ZFPL1 is released by tumors cells of NE or androgen­independent phenotype and its serum levels are significantly higher in cancer patients, suggesting that it may serve as a blood­based non­invasive biomarker of aggressive PC.

Computational pathology in 2030: a Delphi study forecasting the role of AI in pathology within the next decade.

BACKGROUND: Artificial intelligence (AI) is rapidly fuelling a fundamental transformation in the practice of pathology. However, clinical integration remains challenging, with no AI algorithms to date in routine adoption within typical anatomic pathology (AP) laboratories. This survey gathered current expert perspectives and expectations regarding the role of AI in AP from those with first-hand computational pathology and AI experience. METHODS: Perspectives were solicited using the Delphi method from 24 subject matter experts between December 2020 and February 2021 regarding the anticipated role of AI in pathology by the year 2030. The study consisted of three consecutive rounds: 1) an open-ended, free response questionnaire generating a list of survey items; 2) a Likert-scale survey scored by experts and analysed for consensus; and 3) a repeat survey of items not reaching consensus to obtain further expert consensus. FINDINGS: Consensus opinions were reached on 141 of 180 survey items (78.3%). Experts agreed that AI would be routinely and impactfully used within AP laboratory and pathologist clinical workflows by 2030. High consensus was reached on 100 items across nine categories encompassing the impact of AI on (1) pathology key performance indicators (KPIs) and (2) the pathology workforce and specific tasks performed by (3) pathologists and (4) AP lab technicians, as well as (5) specific AI applications and their likelihood of routine use by 2030, (6) AI's role in integrated diagnostics, (7) pathology tasks likely to be fully automated using AI, and (8) regulatory/legal and (9) ethical aspects of AI integration in pathology. INTERPRETATION: This systematic consensus study details the expected short-to-mid-term impact of AI on pathology practice. These findings provide timely and relevant information regarding future care delivery in pathology and raise key practical, ethical, and legal challenges that must be addressed prior to AI's successful clinical implementation. FUNDING: No specific funding was provided for this study.

The DACH1 gene is frequently deleted in prostate cancer, restrains prostatic intraepithelial neoplasia, decreases DNA damage repair, and predicts therapy responses.

Prostate cancer (PCa), the second leading cause of death in American men, includes distinct genetic subtypes with distinct therapeutic vulnerabilities. The DACH1 gene encodes a winged helix/Forkhead DNA-binding protein that competes for binding to FOXM1 sites. Herein, DACH1 gene deletion within the 13q21.31-q21.33 region occurs in up to 18% of human PCa and was associated with increased AR activity and poor prognosis. In prostate OncoMice, prostate-specific deletion of the Dach1 gene enhanced prostatic intraepithelial neoplasia (PIN), and was associated with increased TGFb activity and DNA damage. Reduced Dach1 increased DNA damage in response to genotoxic stresses. DACH1 was recruited to sites of DNA damage, augmenting recruitment of Ku70/Ku80. Reduced Dach1 expression was associated with increased homology directed repair and resistance to PARP inhibitors and TGFb kinase inhibitors. Reduced Dach1 expression may define a subclass of PCa that warrants specific therapies.

Interobserver reproducibility of cribriform cancer in prostate needle biopsies and validation of International Society of Urological Pathology criteria.

AIMS: There is strong evidence that cribriform morphology indicates a worse prognosis of prostatic adenocarcinoma. Our aim was to investigate its interobserver reproducibility in prostate needle biopsies. METHODS AND RESULTS: A panel of nine prostate pathology experts from five continents independently reviewed 304 digitised biopsies for cribriform cancer according to recent International Society of Urological Pathology criteria. The biopsies were collected from a series of 702 biopsies that were reviewed by one of the panellists for enrichment of high-grade cancer and potentially cribriform structures. A 2/3 consensus diagnosis of cribriform and noncribriform cancer was reached in 90% (272/304) of the biopsies with a mean kappa value of 0.56 (95% confidence interval 0.52-0.61). The prevalence of consensus cribriform cancers was estimated to 4%, 12%, 21%, and 20% of Gleason scores 7 (3 + 4), 7 (4 + 3), 8, and 9-10, respectively. More than two cribriform structures per level or a largest cribriform mass with ≥9 lumina or a diameter of ≥0.5 mm predicted a consensus diagnosis of cribriform cancer in 88% (70/80), 84% (87/103), and 90% (56/62), respectively, and noncribriform cancer in 3% (2/80), 5% (5/103), and 2% (1/62), respectively (all P < 0.01). CONCLUSION: Cribriform prostate cancer was seen in a minority of needle biopsies with high-grade cancer. Stringent diagnostic criteria enabled the identification of cribriform patterns and the generation of a large set of consensus cases for standardisation.

Germ cell neoplasms of the testis: Update for 2022.

Germ cell neoplasia in situ (GCNIS) is the precursor of both seminomatous and non-seminomatous germ cell tumors. It consists of distended tubules that may have either intratubular seminoma or intratubular embryonal carcinoma cells. Many invasive non-seminomatous tumors contain a mixture of tumor types, which are reviewed here. Morphology, aided by a panel of immunostains, can determine the presence and percent of embryonal carcinoma, yolk sac tumor, choriocarcinoma, or teratoma in such tumors. Use of immunostains, required for diagnosis in perhaps 25% of testicular neoplasms, is reviewed. Changes of classification in the AJCC (8th edition) in 2016 are discussed, including the partitioning of two tumor types: the central role of chromosome 12p amplification allows both teratoma and yolk sac tumor to be divided into prepubertal types (lacking amplification) and post-pubertal types. Occasionally, sex cord-stromal tumors, hematolymphoid tumors, or epididymal adenomatoid tumors enter the differential diagnosis of germ cell neoplasms.

Malignant Mesothelioma of Tunica Vaginalis Testis: Update for 2022.

Malignant mesothelioma of the testicular tunics is rare. About one third of cases are metastatic and carry a poor prognosis. This paper reviews the epidemiology, clinicopathologic features, treatment, and outcome of this entity.