The Prostate

Objective: To develop and evaluate an Observational Medical Outcomes Partnership (OMOP) standardized prostate cancer database from the University of Texas Medical Branch (UTMB) Epic Electronic Health Record (EHR) and improve data quality using natural language processing (NLP) and prostate-specific antigen (PSA) based algorithms. Materials and Methods: We built a data pipeline to transform UTMB Epic EHR data from 2010 to 2021 into OMOP Common Data Model (CDM) v5.4. Data quality was assessed by comparing the OMOP-standardized data with Galveston Cancer Registry data using availability agreement, Cohen's kappa, and Intraclass Correlation Coefficient. NLP was used to extract PSA, Gleason score, and cancer stage from clinical text, and PSA-based algorithms were used to identify missing treatment and biochemical recurrence. Results: We extracted 815 analytic cases from UTMB EHR. Among them, 700, or 85.9%, were complete and concordant with the cancer registry. PSA showed excellent value agreement. Structured Gleason score and stage data were sparse, with fewer than 20 cases, but NLP greatly improved capture. Treatment agreement was good compared with the cancer registry and improved slightly for radical prostatectomy after applying a PSA-based algorithm. Using PSA trajectories, we identified 60 cases of biochemical recurrence. Discussion: The OMOP-standardized data from UTMB showed good agreement with the cancer registry. However, structured EHR fields incompletely captured diagnosis, pathology, and treatment details. NLP and PSA-based algorithms substantially improved data capture. Manual review also revealed errors in registry data, showing that OMOP-standardized EHR data can complement and help improve cancer registry quality. Conclusion: OMOP standardization combined with NLP and PSA-based algorithms improved prostate cancer data quality and research readiness.

The spatial arrangement of immune cells in the tumor microenvironment (TME) varies widely, from dispersed to clustered and tumor excluded to infiltrating. Multiplexed spatial profiling is an effective means of characterizing tumor-infiltrating lymphocytes (TILs) and immune complexes such as tertiary lymphoid structures (TLS) in the TME. However, few approaches have been described for objectively parametrizing patterns of immune organization and assessing their association with biological or clinical variables. This makes it difficult to evaluate whether a set of tumors is relatively immunologically cold or hot. Here we describe an intuitive set of statistical tools (available in the R package, tlsR) for characterizing lymphocyte patterns in the TME of solid cancers. We apply tlsR to primary prostate cancer (PCa), which is often described as immunologically cold. Using a cohort of 29 radical prostatectomy specimens stratified into low Gleason-grade (LGG; n=15) and high Gleason-grades (HGG; n =14) we show that HGG PCa is significantly more infiltrated than LGG PCa with lymphocytes organized into B cell or T cell enriched immune clusters (BICs and TICs). A subset of these ICs have the B and T cell zonation and follicular dendritic cells characteristic of a bona fide TLS. HGGs are also enriched with ICs containing precursor exhausted T cells (Tpex) and proliferating B cells and their tumor compartments harbor granzyme-B+ cytotoxic T cells in contact with cancer cells. Thus, far from being cold, a subset of HGG PCa has features associated with active immune surveillance, a finding with implications for emerging PCa immunotherapies.

Background: Changes in the extracellular matrix (ECM) are a recognised feature of aggressive prostate cancer, but they are not exploited in clinical decision-making. We aimed to develop automated quantitative ECM parameters to facilitate risk stratification for localised prostate cancer. Methods: 378 quantitative ECM parameters were derived from picrosirius red-stained diagnostic prostate biopsies in a cohort of 422 patients, matched 1:1 for recurrence, recruited to the CHHiP (Conventional or Hypofractionated High Dose Intensity Modulated Radiotherapy in Prostate Cancer) trial of radiotherapy fractionation for localised prostate cancer. These ECM parameters comprehensively described fibre architecture, gaps and ECM texture. Machine learning models at the level of both individual image tiles and patients defined how ECM parameters related to tumour versus normal prostate, Gleason grade group and recurrence. Shapley analysis was used to interpret ECM feature importance and develop signatures associated with recurrence. Results: Specific ECM patterns identified tumour versus normal prostate, Gleason pattern 4 versus 3 and recurrence. ECM patterns associated with recurrence were enriched in Gleason 4+3 patients, versus Gleason 3+4 patients. Shapley analysis revealed that biopsies from patients with recurrence had smaller more elongated gaps between fibres, with finer grained ECM texture and lower ECM homogeneity than less recurrent regions. Interpretation: Quantitative automated analysis of ECM architecture can inform probability of prostate cancer recurrence after radiotherapy; Features relating to ECM gap size and texture are of particular relevance.

Objectives. To determine whether medical machine olfaction via tracking the activation of mammalian G-Protein Coupled odorant Receptors (GPCR) stabilized by proprietary co-polymers on a photonic MZI chip can be used to diagnose prostate cancer (PCa) via urine scent. Specifically, scent character is compared against the current diagnostic PCa screening gold-standard in the US: the serum level of prostate specific antigen (PSA). The device is an artificial nose sensor built on a commercial photonic platform that reads interchangeable Mach-Zehnder interferometer (MZI) chips. These chips were functionalized with a stabilised panel of mammalian olfactory G-protein-coupled receptors (GPCRs). These samples had been characterized into POSITIVE or CONTROL for PCa six to eight years prior by standard hospital diagnostic procedures and by trained medical detection dogs, then stored at -80 Celcius. A subset of 80 patients urine samples was subsequently thawed and used for training and testing the medical machine olfaction system of RealNose as an initial validation of the novel technology and methodological approach. We posed two primary research questions: (a) whether the cancer-associated odor profile would remain detectable by machine-based systems following long-term storage and with what accuracy could it be used to cluster (YES and AUC 0.79 from scent character alone), and (b) what technical and procedural requirements would be necessary to translate such a signal into a clinically useful diagnostic assay (more training samples (500 predicted to yield 0.93) and increased breadth of receptors per chip and/or more chips per device in next iteration seen as helpful). Design, setting, participants. Retrospective diagnostic-accuracy feasibility study on 80 biobanked urine samples (40 PCa, 40 non-cancer; 368 sensor runs; a subset of unknown Gleason grade) from a single UK NHS urology service, the same collection used to train canine detectors. Main outcome measures: Patient-level Receiver Operating Characteristic (ROC) area under the curve (AUC) under patient-grouped cross-validation with a fold-honest pooled-control reference (reconstructed from training-partition controls only); sensitivity, specificity and predictive values at pre-specified operating points; 1000-fold whole-procedure label-permutation significance; patient bootstrap 95% CIs; and leave-one-day-out / leave-one-chip-out generalisation. Results. An L2-regularised linear classifier when allowed to see between three and six chips outcome on a patient sample extracted within-instrument AUC 0.79 (95% CI 0.69 to 0.88; 1000-permutation p = 0.001) from urine scent alone, exceeding this cohort own serum prostate-specific antigen (PSA) discrimination (AUC 0.645; itself within the population range for PSA 0.67) and obtained without a blood draw (at the Youden point, sensitivity 0.75, specificity 0.78, PPV 0.77, NPV 0.76). Upon allowing PSA the total AUC rose to 0.82. This was not a plateau: AUC rose from chance at 30 training samples, passed the serum-PSA range at 40, and reached 0.79 at 80 patients (0.82 if PSA was included), with an inverse-power fit projecting 0.93 by n = 500 and 0.96 by n = 1000. The discriminant was a genuine multivariate receptor pattern, independent of patient age (Spearman 0.09; the cohort is not age-matched). So at least for these data, neither age, nor collection day, ambient humidity/temperature, or overall signal amplitude (sometimes thought of as intensity of smell) were predictive of prostate cancer status, yet the scent character was. Transfer to a new sensor chip fell to AUC 0.57 without calibration, meaning the remaining obstacles are hardware portability rather than signal existence: much as a detection dog acclimatizes to a new setting, the system improves with on-site calibration prior to use. Conclusions: A genuine, confound-controlled olfactory PCa signature is recoverable from 80 samples, surpasses this cohort serum PSA (0.645) and exceeds the population PSA range, and improves monotonically with training-set size. We present this as a small-sample feasibility benchmark, not yet a validated diagnostic; the dominant remaining factor is training-set size, and the path to clinical-utility and improved AUC is clearly found to be a larger, multi-site, age-matched, and ideally prospective training cohort. A transferable small-sample lesson is also reported: adaptive feature searches (evolutionary and self-calibrating-protocol handle search) artificially inflate cross-validation and collapse under whole-procedure permutation, whereas non-adaptive averaging survives, giving a robust scent signal obtainable from the headspace of urine samples and recordable by the RealNose device that keeps improving with expanding sample training set.

Metastatic prostate cancer (PCa) continues to be a major cause of death in males, despite advances in treatment. Most treatment focuses on targeting the Androgen Receptor (AR), the main oncogene responsible for driving most prostate tumors. Despite these therapies targeting AR, the majority of patients still succumb to AR-driven disease. Therefore, there is a critical need for understanding how AR functions to promote prostate cancer growth and identify alternative therapeutic targets in AR-driven PCa. One avenue garnering attention is targeting epigenetic regulators that promote AR-activity; however, the importance of epitranscriptomic regulators, like those that modify mRNAs, is not well understood. Here, we identify a new role for the key catalytic subunit of the RNA N6-methyladenosine (m6A) transferase complex, METTL3, as an AR-coregulator. METTL3 is overexpressed in prostate tumors compared to normal tissue, and METTL3 protein is elevated in AR-expressing cell lines. Depletion of METTL3 significantly reduces proliferation of cancer cells and has no effect on the growth of non-transformed prostate epithelial cells, despite decreasing global m6A levels on mRNA. The catalytic activity of METTL3 is dispensable for the growth of both non-transformed and PCa cell lines, as pharmacologic inhibition of METTL3 does not inhibit proliferation, despite the reduction of global m6A on mRNA. Overexpression of both wild-type and catalytically inactive METTL3 mutants enhances cell viability and rescues cells in which METTL3 is knocked down. Finally, we report on direct interaction between AR and METTL3, their co-localization on chromatin, and reduced AR-cistromic occupancy within cells with METTL3 knockdown. Together, these findings identify a non-enzymatic role for METTL3 in supporting AR-driven transcriptional programs and PCa proliferation.

The therapeutic efficacy of oncolytic viruses is often limited by the presence of tumor cells that resist virus-mediated killing. Here, we investigated the molecular mechanisms underlying resistance to Vesicular Stomatitis Virus (VSV) in PC3 cells, an aggressive metastatic prostate cancer (PrCa) cell line, using the VSV-sensitive LNCaP cell line as a comparator. RNA sequencing revealed that, relative to untreated cells, VSV-infected PC3 cells upregulated both pro-apoptotic genes, including BIM, PUMA, and NOXA, and anti-apoptotic and antiviral genes, including A20 and RIG-I. In addition, genes associated with antiviral and pro-survival pathways, including NF{kappa}B and PI3K-Akt signaling, were more highly expressed in PC3 cells than in LNCaP cells. At baseline, PC3 cells also exhibited elevated expression of multiple pro-survival genes, including BCL-xL, MCL1, and CK2, compared with LNCaP cells. Complementary proteomic analyses identified enhanced activation of NF{kappa}B, PI3K-Akt, and MSK1 signaling in VSV-infected PC3 cells relative to infected LNCaP cells. Furthermore, pharmacological inhibition of BCL-2 family proteins or NF{kappa}B signaling restored sensitivity to VSV-induced cell death in PC3 cells. Collectively, these findings identify NF{kappa}B-centered pro-survival signaling networks as key contributors to the resistant phenotype of PC3 cells and suggest that combining oncolytic virotherapy with targeted inhibitors may improve therapeutic efficacy in resistant prostate cancers.

Cellular interactions underlie fundamental biological processes but are not fully represented in conventional 2D histology images. While 3D pathology allows for more-accurate construction of cell-level graphs, machine-learning models are computationally unwieldy and prone to overfitting, especially when dealing with small cohorts. Here, we introduce SCALE3D, a SuperCell graph Analysis framework for LargE 3D pathology datasets. In SCALE3D, spatially adjacent and morphologically similar cells are grouped into functional "supercells." Supercell subtypes are defined via morphology-based clustering and 3D graphs connecting these supercells are used to model their interactions. Validation was performed with 76 radical prostatectomy specimens from patients with known 5-year biochemical recurrence (BCR) outcomes. SCALE3D-derived features achieve higher performance for BCR prediction than established 3D nuclear and glandular morphological features. Combining these complementary features further improves prediction performance. Compared to individual cell-level 3D graphs, SCALE3D maintains comparable prognostic performance with improved noise tolerance while reducing computational times by up to 1,000-fold.

Bipolar androgen therapy (BAT) exploits the paradoxical vulnerability of castration-resistant prostate cancer (CRPC) cells to rapid cycling between castrate and supraphysiologic androgen concentrations, but clinical BAT uses testosterone, which can also activate wild-type androgen receptor (AR) in androgen-responsive tissues, causing systemic side effects. 5{beta}-dihydrotestosterone (5{beta}-DHT) is a naturally occurring testosterone metabolite generally considered androgenically inactive because it binds wild-type AR weakly, yet its activity against clinically relevant AR mutants has not been systematically evaluated. Here, we tested whether 5{beta}-DHT and related 5{beta}-reduced testosterone metabolites activate AR signaling and growth programs in prostate cancer models that carry AR mutations. In C4-2 cells, 5{beta}-DHT and 3{beta}-etiocholanediol (3{beta}-ecdiol) increased canonical AR target genes, including KLK3 and TMPRSS2, with weaker activity than testosterone, whereas other 5{beta} metabolites showed limited activity. In androgen-responsive LNCaP and C4-2 models, 5{beta}-DHT and 3{beta}-ecdiol promoted cell growth under androgen-depleted conditions, and this effect was suppressed by enzalutamide, supporting AR dependence. RNA-seq confirmed that 5{beta}-DHT and 3{beta}-ecdiol induced androgen-response gene sets substantially overlapping with testosterone, albeit at lower transcriptional magnitude. Further, we found that 5{beta}-DHT, but not 3{beta}-ecdiol, suppresses cell proliferation of LNCaP, C4-2, and PC-3 cells stably expressing the clinically relevant AR gain-of-function mutants W742C and H875Y through activating AR-induced senescence-like features after high-dose exposure, consistent with the therapeutic logic of BAT. These findings identify 5{beta}-DHT as an overlooked mutant-AR agonist capable of BAT-like tumor suppression and propose it as a testosterone surrogate in BAT with potentially reduced systemic androgenic side effects. HighlightsO_LI5{beta}-DHT and 3{beta}-ecdiol promote AR-dependent prostate cancer cell growth C_LIO_LIBoth are weaker AR agonists than testosterone by RNA-seq and qPCR C_LIO_LISupraphysiologic 5{beta}-DHT suppresses growth via AR-mediated senescence C_LIO_LIGrowth suppression extends to AR mutants W742C and H875Y C_LIO_LI5{beta}-DHT may be a lower-androgenicity testosterone surrogate for BAT C_LI

PurposeTo develop and evaluate a multi-model consensus deep learning approach for automated gold fiducial marker (FM) segmentation in T1-weighted prostate MRI. Materials and MethodsIn this retrospective study, T1-weighted MRI and CT-derived reference standard segmentations were collected from 127 prostate cancer patients (all male; mean age, 70 years {+/-} 7 [standard deviation]; age range, 50-88 years; collected between October 2020 and January 2026) who each had three implanted gold FMs. A 3D U-Net was trained on 93 subjects using four random seeds to produce an ensemble. At inference, marker-class probability maps were averaged across models and the top three connected components selected. Performance was evaluated on 34 temporally held-out subjects (9 tuning, 25 test) using marker-level sensitivity and precision with exact (Clopper-Pearson) 95% confidence intervals (CIs). A model count ablation study was performed. The pipeline was deployed for on-scanner processing on Siemens MRI systems via the OpenRecon framework and as a browser-based application using WebAssembly, executing entirely client-side. ResultsThe four-model consensus achieved 96% (70 of 73) sensitivity and 95% (70 of 74) precision on 25 test subjects, with 29 of 34 (85%) subjects achieving perfect marker detection. Single models had a mean sensitivity of 84% (SD, 9%), improving to 96% with four-model consensus (SD, <1%). ConclusionMulti-model consensus deep learning substantially improved FM segmentation reliability over individual models, achieving high sensitivity and precision using only routinely acquired T1-weighted MRI.

Androgen signalling is essential for prostate secretory functions and epithelial cell maintenance, yet how this signal is translated into a transcription output remains poorly understood. Androgens functions are primarily mediated by the androgen receptor (AR) that binds hormone response elements similar to those of other steroid receptors, including the glucocorticoid receptor (GR). Here we show that AR and GR are co-expressed in the prostate epithelium, and located within nuclear foci. Moreover, GR promotes the formation and dynamics of AR nuclear condensates, and heterodimerizes with AR in a ligand binding domain-dependent manner. In addition, subtle variations within the hormone response element sequence direct the co-recruitment of AR and GR within activator or repressor complexes to activate or repress gene expression. Finally, prostate-specific deletion of GR in mice disrupts AR nuclear distribution, impairs AR-dependent gene networks involved in epithelial maintenance, and promotes the expression of genes involved metabolism and cell cycle, resulting in altered tissue homeostasis. Thus, these findings identify GR as an integral component of the AR transcriptional machinery in epithelial cells of the healthy prostate, and reveal how shared cis-regulatory elements are interpreted to generate distinct transcriptional outcomes.

Objectives: Natural language processing (NLP) can enable scalable extraction of clinically relevant information from unstructured radiology reports retrieved from electronic healthcare data warehouses, but reliance on externally hosted models may pose cost, privacy, and deployment challenges. We compared self-hosted discriminative and generative NLP pipelines for automated extraction of Prostate Imaging and Reporting Data System (PIRADS) scores from multiparametric magnetic resonance imaging (mpMRI) reports used in prostate cancer risk assessment. Materials and Methods: We identified 44,511 mpMRI reports across 68 Veterans Affairs (VA) healthcare systems. A stratified random sample of 1,973 reports was used to train, test, and evaluate multiple pipeline configurations combining Named Entity Recognition (NER) models and large language models (LLMs). Performance was assessed by accuracy of maximum PI-RADS extraction and processing speed using self-hosted implementations of spaCy NER, Transformers NER, and generative LLMs Llama 3, Qwen3, and Gemma3. Results: Across the top 10 pipeline configurations, accuracy for maximum PI-RADS extraction ranged from 89.3% to 95.5%, with processing times spanning 150 milliseconds to 70 seconds per report. Generative LLM pipelines achieved the highest accuracy (up to 95.5%) but were substantially slower (2 to 70 seconds), whereas NER based pipelines demonstrated lower accuracy (88.5%) with faster performance (50 to 150 milliseconds). Discussion: Discriminative NER pipelines achieved high accuracy while offering advantages in speed and potential scalability. Accuracy gains from LLMs were accompanied by significantly higher computational cost, potentially limiting feasibility in high-volume clinical environments. Conclusion: Discriminative methods were more efficient than generative models in annotating PIRADS from mpMRI report text, providing insights into configurations for optimal clinical deployment when volume is a limiting factor. However, generative AI offered improved accuracy with less upfront development.

Cryopreservation of ram semen induces structural and functional alterations that compromise sperm fertility. Since seminal plasma contributes to the regulation and preservation of sperm function, increasing attention has been directed toward seminal plasma extracellular vesicles (EVs) that are involved in sperm physiology. EVs act as carriers of proteins that are involved in sperm membrane organization and capacitation, suggesting that they may contribute to the maintenance of sperm stability during cryopreservation.. Thus, the aim of this study was to evaluate the effect of seminal plasma-derived EVs on post-thaw functional parameters of ram sperm. Semen was cryopreserved in the presence or absence of EVs isolated by ultracentrifugation that have been characterized by nanoparticle tracking analysis (NTA) and Western blotting (WB). Post-thaw sperm quality was assessed by evaluating viability, membrane lipid disorder, reactive oxygen species production, protein phosphorylation, acrosome status, intracellular calcium levels, and sperm motility. Sperm cryopreserved with an extender containing EVs showed a significant reduction in membrane lipid disorder and lower intracellular calcium levels compared to control samples (p < 0.05). CASA analysis revealed that EV supplementation did not affect total or progressive motility but modified sperm kinematic patterns, with increased linearity and straightness, indicating improved trajectory efficiency without induction of hyperactivated motility. No differences were detected in viability, ROS content, phosphorylation of proteins in residuous tyrosine (pY) or PKA or acrosome status. These results provide the first evidence that seminal plasma derived extracellular vesicles exert a protective effect during ram semen cryopreservation, preserving membrane organization and calcium homeostasis and improving sperm functional quality after thawing. Highlights- Seminal EVs protect ram sperm during cryopreservation. - EVs reduce membrane lipid disorder and intracellular Ca2+ levels. - EVs modify kinematics, increasing linearity and straightness. - No effects on viability, ROS, phosphorylation or acrosome status. - EVs improve post-thaw sperm functional quality and stability. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=92 SRC="FIGDIR/small/732841v1_ufig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@d1f8a9org.highwire.dtl.DTLVardef@11c3d6aorg.highwire.dtl.DTLVardef@104124forg.highwire.dtl.DTLVardef@4e355f_HPS_FORMAT_FIGEXP M_FIG C_FIG

177Lu-PSMA-617 (PluvictoTM, Lu-177 RLT) is an FDA-approved targeted radioligand therapy (RLT) for metastatic castration-resistant prostate cancer (mCRPC), but its durability of response to this singular approach poses a challenge to the field. Chimeric antigen receptor (CAR) T cell therapy has revolutionized clinical practice for hematological malignancies, but its clinical development for solid tumors, including mCRPC, has been encumbered by antigen heterogeneity and the immunosuppressive tumor microenvironment (TME). Here, we evaluate the therapeutic combination of Lu-177 RLT and PSCA-CAR T cells to overcome these barriers. In human xenograft and mouse syngeneic prostate cancer models with homogeneous or heterogeneous antigen expression, the sequential administration of Lu-177 RLT, cyclophosphamide (Cy), and PSCA-CAR T cells improves tumor control and prolongs survival compared to monotherapies. Mechanistically, Lu-177 RLT alone or with Cy remodels the TME by promoting pro-inflammatory myeloid responses and activating endogenous T cells, while enhancing CAR T cell activation and effector function. We additionally evaluated 225Ac-PSMA-617 RLT as an emerging approach in combination with CAR T cells and observed anti-tumor responses, supporting its potential as an alternative RLT partner. These findings support RLT as an immune priming strategy to enhance CAR T cell therapy and provide a rationale for clinical translation of this combination in mCRPC. One Sentence SummaryCombining 177Lu-PSMA-617 radioligand therapy with PSCA-CAR T cells improves tumor control and survival in prostate cancer models by overcoming the antigen heterogeneity and reshaping the immunosuppressive tumor microenvironment.

Automated Gleason grading now matches expert pathologists on the cohorts where systems are developed and tuned, but deployment-relevant gaps remain: whether an automated grade, applied without site-specific tuning or pathologist oversight, stratifies outcome comparably to expert grading on slides from unseen institutions and in cross-specimen applications. We tested this for disease-free interval (DFI), a curated recurrence endpoint. A production gland-level prostate diagnostic (PathTools Prostate v11.0) was applied frozen and uncalibrated to 298 diagnostic whole-slide images from 274 TCGA-PRAD radical-prostatectomy patients, a cohort outside its development distribution and needle-core-biopsy training data, contributed by 25 source sites under heterogeneous digitization; tissue was detected automatically with no expert region annotation. From the output we derived an ISUP grade group and continuous high-grade content, and evaluated each grade as a standalone predictor of DFI (24 events) by Harrell's c-index with 95% bootstrap confidence intervals, a paired between-method bootstrap, and Kaplan-Meier curves with the log-rank test. The automated grade reproduced the clinical grade group at quadratic-weighted kappa = 0.62 (95% CI 0.53-0.70; 48% exact, 86% within one group), within the expert inter-observer range. As the sole predictor it stratified recurrence (log-rank p = 0.022; c-index 0.69, 95% CI 0.58-0.79), and the continuous high-grade fraction was robustly prognostic (hazard ratio 1.37 per SD, p = 0.029; c-index 0.71, 0.61-0.81). Standalone discrimination was not statistically separable from the clinical grade (c-index 0.78, 0.69-0.86; paired {triangleup} c-index spanning zero), and in a joint model the automated grade added nothing beyond it, consistent with both measuring a shared morphological axis. From a single out-of-distribution slide with no pathologist oversight, the automated grade provides standalone recurrence stratification not statistically separable from whole-gland expert grading, demonstrating robust generalizability beyond training data; reported as a continuous high-grade fraction, it offers reproducible, expert-free, grade-equivalent risk stratification for harmonizing large archival or genomically-profiled cohorts.

Polo-like kinase 1 (PLK1), a key regulatory protein controlling entry into and passage through mitosis, has been targeted through its kinase domain (KD) with mixed clinical success. Inhibition through the Polo-box domain (PBD) is a viable alternative through targeting the sub-cellular localization and kinase activity of PLK1. Novel non-peptidic compounds, termed abbapolins, were discovered through the REPLACE strategy and have been lead optimized through structure-based strategies and screening analogs in the NCI-60 tumor cell panel. Proteomic analysis revealed a correlation between abbapolin activity and PLK1 protein levels in the cell lines part of the NCI-60. Prostate cell lines were identified as among the most sensitive and led to further detailed studies of their activity in prostate cancer models. Compounds were evaluated for their pharmacokinetic properties, and in vivo efficacy, and results showed significant antitumor xenograft activity with no observable gross toxicity. Treated tumors were analyzed for loss of PLK1, which was previously shown to be induced by abbapolin binding. Results obtained showed a significant degradation of PLK1 in abbapolin-treated vs untreated tumors, thereby confirming on-target action in vivo and revealing PLK1 levels as a potential pharmacodynamic marker. Lead compounds were shown to sensitize PC tumors resistant to androgen deprivation therapy paving the way for future combination studies in vivo. These data provide an alternative pathway for effective PLK1 therapeutics that avoid the reported problems of molecules targeting the KD, in vivo proof-of-concept for the REPLACE strategy and validation for targeting the PBD as an anti-tumor drug development strategy.

Chimeric antigen receptor (CAR) T cell therapy has limited efficacy against solid tumors such as prostate cancer due to the immunosuppressive tumor microenvironment (TME). Combining CAR T cells with existing therapies that remodel the TME and promote endogenous immune responses, such as radiation therapy and chemotherapies, may strengthen antitumor responses. Here, we assessed the potency of combining focal radiotherapy (RT), cyclophosphamide (Cy) preconditioning, and prostate stem cell antigen (PSCA)-CAR T cells against syngeneic prostate cancer models. Focal RT alone increased T cell and dendritic cell infiltration and activation in the irradiated tumor. Furthermore, the combination of all three therapies was critical for enhanced antitumor responses and survival across multiple subcutaneous, bone-metastatic, and multifocal disease models. This combination, in the irradiated TME and tumor-draining lymph nodes (tdLN), led to greater antigen presentation by myeloid cells and endogenous T cell activation and cytotoxicity. Our study demonstrates the potency of combining focal RT with PSCA-CAR T cells, significantly improving therapeutic responses in the irradiated tumor and contributing to a more robust systemic immune response against metastatic burden in prostate cancer.

Background and Objective: Due to the heterogeneity of bladder cancer, minimally invasive molecular profiling may improve tumor characterization at the time of diagnosis. We evaluated whether integrated genomic and fragmentomic profiling of plasma and urinary circulating tumor DNA (ctDNA) detects BC-derived signals for diagnosis and disease stratification across all tumor stages. Methods: In this real-world cohort, 202 plasma and urine samples were obtained from 33 patients with non-muscle-invasive BC (NMIBC), mostly Ta tumors, and 15 patients with muscle-invasive BC (MIBC), as well as from 58 cancer-free controls. Low-coverage whole-genome sequencing was performed to assess ctDNA fragmentation, chromosomal instability and copy number variations. Matched tumor tissue was analyzed to evaluate concordance between liquid biopsy and tissue-derived molecular alterations. Key Findings and Limitations: Complementary genomic and fragmentomic profiling of cfDNA achieved detection rates of 75.8% in NMIBC patients and 91.7% in MIBC patients with paired plasma and urine. Distinct differences were observed between MIBC, NMIBC and cancer-free controls, consistent with increasing ctDNA signals during disease progression. Tumor tissue analysis confirmed BC-associated molecular alterations. Limitations include the single-center design and limited sample size. Conclusions and Clinical Implications: Multimodal profiling of plasma and urinary cfDNA enabled the detection of tumor-derived molecular signals for all bladder cancer stages, including early-stage disease. By integrating genomic and fragmentomic features, this minimally invasive approach provides molecular tumor characterization at the time of diagnosis and may support future risk-adapted diagnostic, therapeutic and surveillance strategies.

Study questionHow does cryptorchidism affect germ cell development and UTF-1-mediated pluripotency potential at the time of orchiopexy? Summary answerCryptorchidism was associated with the following germ cell abnormalities: germ cell clustering with many cords/tubules lacking germ cells and reduced UTF-1 expression, suggesting limited germ cell differentiation into spermatogonia What is known alreadyCryptorchidism, affecting 1.6-9% of male newborns, is known to increase the risk of infertility and testicular cancer due to abnormal germ cell development. Germ cells and pluripotent stem cell gene, UTF-1, play critical roles in spermatogonia differentiation, self-renewal, and spermatogenesis. No prior study has evaluated the testicular development by immunohistochemically mapping of these cell populations, Study design, size, durationA cross-sectional study of 31 postnatal cryptorchid testis and 5 age-matched scrotal testicular biopsies obtained from UCSFs pathology department performed between 1993-2023. Participants/materials, setting, methodsSpecimens were grouped by age at surgery (6-18 months, 19 months-7 years, 8-12 years, and [&ge;]13 years) and testis location (palpable vs. non-palpable). Scrotal prepubertal testis biopsies were sourced through the Pedi-LIFE program, a fertility preservation research biobank, with at least one control per age group. Immunohistochemistry was performed to stain specimens for germ cell (DDX4, OCT4, TSPY), pluripotent cell marker (UTF-1), as well as other key testis cell markers (A-actin, AR, P450, Sox-9), with staining graded based on control expression levels. The number of germ cells per seminiferous tubule was quantified and compared across anatomical locations using appropriate statistical analyses. Main results and the role of chanceThis study included 36 specimens, comprising 31 cryptorchid testes (86%) and 5 scrotal control testes (16%). The cryptorchid group exhibited testicular dysgenesis and reduced germ cell expression, correlated with increased age and testis location. Qualitative assessment revealed reduced germ cell expression across all ages in cryptorchid testes. The number of germ cells per tubule was markedly reduced in cryptorchid compared with scrotal testes after 19 months of age for DDX4, TSPY, and UTF-1. Germ cell clusters were identified in 15 out of 31 cryptorchid specimens (48%) stained for DDX4 and TSPY. UTF-1 expression was lower in cryptorchid testes across all age groups. No significant differences were noted in other testicular cell markers. Large scale dataNA Limitations, reasons for cautionFirst, the power and generalizability of the study are limited by the availability of specimens within each age group, particularly for scrotal testes, as biopsies of these tissues are not routinely performed. Second, a cross-sectional study design limits a longitudinal comparison to evaluate changes in marker expression, delayed maturation, or irreversible germ cell loss. Third, immunohistochemistry data is semi-quantitative, and protein detection is affected by antibody sensitivity and tissue preservation and influenced by antibody sensitivity. Lastly, scrotal testis used as controls were obtained from cryopreserved tissue from patients with other unrelated pathology, which may influence histological profiles. Wider implications of the findingsCollectively, our findings support a model in which cryptorchidism involves both germ cell depletion and disrupted SSC lineage formation, with UTF-1 downregulation and germ cell clustering as early signatures of testicular dysgenesis. These features may help identify high-risk patients for worsening gonadal dysgenesis and infertility and can provide a rationale for earlier orchiopexy or SSC-preserving strategies. Study funding/competing interest(s)The authors declare no conflicts of interest and received no funding for this study. Data Availability StatementThe data underlying this article cannot be shared publicly due to ethical and legal restrictions related to the use of human tissue specimens, which may compromise donor privacy and confidentiality. Data are available from the corresponding author upon reasonable request and subject to institutional and ethical approvals.

BackgroundPremature ovarian insufficiency (POI) affects approximately 1% of women under 40 and is characterized by elevated levels of gonadotropins, reduced estradiol, impaired folliculogenesis, and infertility. Bone marrow-derived mesenchymal stem cell (BM-MSC)-based therapy has emerged as a promising regenerative strategy in preclinical POI models. This systematic review and meta-analysis evaluated BM-MSC-based interventions, including cell transplantation and secretome/extracellular vesicle administration, in animal models of POI. MethodsA systematic review and meta-analysis was conducted following PRISMA guidelines. PubMed, Web of Science, Scopus, ScienceDirect, and the Cochrane Library were searched from inception to February 19, 2025. Preclinical studies assessing BM-MSC-based interventions in animal models of POI were included. ResultsThirty-four studies comprising 1,357 animals were included. Compared with controls, BM-MSC-based therapy increased serum estradiol (standardized mean difference [SMD] 3.11; 95% confidence interval [CI] 2.38-3.84) and anti-Mullerian hormone (SMD 1.86; 95% CI 1.03-2.69), while reducing follicle-stimulating hormone (SMD -3.54; 95% CI -4.37 to -2.71) and luteinizing hormone (SMD -3.44; 95% CI -5.17 to -1.70). Follicular counts increased across developmental stages, with fewer atretic follicles. Reproductive outcomes improved, including normal estrous cycles (risk ratio [RR] 7.80; 95% CI 3.15-19.34), pregnancy occurrence (RR 3.72; 95% CI 2.14-6.44), and offspring number (SMD 1.57; 95% CI 1.04-2.09). ConclusionBM-MSC-based therapy consistently improved hormonal, follicular, and reproductive outcomes in preclinical POI models. More well-designed, standardized, and adequately controlled studies to confirm these findings are warranted. Systematic review registration: CRD42023449053

BackgroundDysregulated cell migration leading to metastasis remains the primary cause of cancer-related mortality. It has been challenging to understand how cells regulate migration. We have previously created the first selective inhibitor of cell migration, KBU2046. Here, we use it as a probe to identify regulatory processes. MethodsMetastatic and primary human prostate cancer cells were treated for different times and at different concentrations with KBU2046. Immunofluorescent microscopy examined protein localization in cells. Label-free mass spectrometry (MS) was performed on total cell proteins, Tandem Mass Tag (TMT) labeling MS was used on membrane fractions, and temporal phosphoproteomic profiling. Results were analyzed with a suite of bioinformatic tools. ResultsKBU2046-induced migrastasis is associated with the accumulation of activated integrin {beta}1 into focal adhesions. Whole-cell proteomics demonstrated suppression of processes that mediate intracellular protein trafficking and increases in mitochondrial energy-generation signatures. Evaluation of the membrane fraction identified increases in membrane repair and maintenance processes and decreases in those that drive motility. Temporal- and concentration-dependent phosphoproteomic profiling revealed that KBU2046 initiates a dynamic, cascading sequence of transient signaling waves rather than a static block. ConclusionsKBU2046-induced migrastasis appears to operate through spatial decoupling rather than structural degradation. By restricting the intracellular trafficking machinery required for receptor recycling, KBU2046 limits focal adhesion turnover, providing a correlative framework to inhibit metastatic dissemination independent of direct cytotoxicity. O_FIG O_LINKSMALLFIG WIDTH=122 HEIGHT=200 SRC="FIGDIR/small/736165v1_ufig1.gif" ALT="Figure 1"> View larger version (39K): org.highwire.dtl.DTLVardef@1cc69d3org.highwire.dtl.DTLVardef@137b843org.highwire.dtl.DTLVardef@1225e50org.highwire.dtl.DTLVardef@15dd8d2_HPS_FORMAT_FIGEXP M_FIG Graphic Abstract C_FIG