Colorectal cancer (CRC) remains a leading cause of cancer-related mortality worldwide, with limited efficacy of conventional therapies due to immunosuppressive tumor microenvironments and high recurrence. While bispecific T-cell engagers (BiTEs) show promise by engaging T cells against tumors, their clinical translation is hindered by poor stability, on-target off-tumor effect, and systemic toxicity. Herein, we develop a tumor-targeted nanozyme (MnO2-dsDNA@BiTE/APT) that co-delivers hydrolytically stable double-strand DNA (dsDNA: a STING agonist) and PD-L1/CD3 BiTE to overcome these limitations. The nanozyme leverages MnO2 as a carrier for dsDNA, surface-loaded with BiTE via polyphenol-protein coordination, and functionalized with an aptamer (APT) for active targeting. Upon systemic administration, the nanozyme accumulates in tumors, releasing dsDNA, Mn2+, and BiTE. The synergistically activates the STING pathway to remodel the immunosuppressive microenvironment and enhances T cell-mediated cytotoxicity. This strategy represents a promising approach for potentiating immunotherapy in CRC by integrating innate immune activation with adaptive T cell engagement.

Prostate cancer (PCa) is the common malignant disease in older men. Cancer-associated fibroblasts (CAFs) are a vital components of the tumor microenvironment (TME)and the major subpopulation of cells that promote tumor heterogeneity. However, there are still few studies on the correlation between PCa and CAFs. Thus, we predicted the prognosis of PCa by investigating CAFs characteristics in PCa and constructing a prognostic model with CAFs-related features. Firstly, we obtained the scRNA-seq and clinical data on PCa from the GEO and TCGA databases. We adopted a survival analysis to evaluate the impact of three distinct CAFs subtypes on the prognosis of PCa patients. Besides, we identified different CAFs by integrated univariate Cox regression analysis, LASSO analysis, and multivariate Cox regression analysis. Based on the cancer-associated fibroblast-related genes (CAFRGs), we built a prognostic model to exhibit PCa prognostic relevance and validated the prognostic signature. We also screened the drugs for PCa. Furthermore, we explored the correlation between malignant features and PCa. We revealed that apCAFs and myCAFs were significantly correlated with PCa patient prognosis. 5 prognostic CAFRGs (SYNM, NR4A1, MSMB, HOPX, and GJC1) were screened by integrated analysis. We found that the low-risk group patients had significantly higher survival rates. And validation analyses targeting the prognostic model indicated that the high-risk group patients were more to exhibit higher BCR across external validation sets. The ssGSEA algorithm indicted that the majority of the immune cells had increased levels of infiltration and higher immune function scores in the high-risk group. In addition, CAFRG scores were correlated with angiogenesis, EMT, and cell cycle pathway activity. In conclusion, we build a prognostic model with CAFs prognostic characteristics for PCa to offer further prediction of PCa prognosis and immunotherapy response, which ultimately guides the clinical management of PCa.

Prostate cancer is the second most common cancer in men globally. Advances in diagnostic techniques, particularly multiparametric magnetic resonance imaging and the Prostate Imaging Reporting and Data System, have enhanced detection precision. However, optimal biopsy strategies for lesions with Prostate Imaging Reporting and Data System scores of 3-5 remain uncertain. Here we show that saturation targeted biopsy and ipsilateral systematic biopsy combined with targeted biopsy achieve comparable detection rates of clinically significant prostate cancer to the combined systematic and targeted biopsy approach for Prostate Imaging Reporting and Data System 3-5 lesions, while reducing unnecessary biopsies. Targeted biopsy alone remains insufficient, and omitting systematic biopsy in Prostate Imaging Reporting and Data System 5 lesions is not supported. These findings support tailored biopsy strategies based on Prostate Imaging Reporting and Data System scores, optimizing resource allocation and minimizing overdiagnosis. Further validation in larger cohorts with standardized protocols is necessary. Optimal biopsy strategies for lesions with Prostate Imaging Reporting and Data System (PI-RADS) scores of 3-5 remain uncertain. Here, the authors show that for PI-RADS 3–5 lesions, saturation targeted biopsy and ipsilateral systematic biopsy combined with targeted biopsy (ips-SB + TB) exhibit comparable detection rates of clinically significant prostate cancer to systematic plus targeted biopsy (SB + TB), supporting refined biopsy strategies that challenge the necessity of bilateral systematic biopsy. However, targeted biopsy alone remains insufficient, and omitting systematic biopsy in PI-RADS 5 lesions is not supported by current evidence.

Benign prostatic hyperplasia (BPH) is a common chronic disease among elderly men, and its etiology remains unclear. This study aimed to investigate the expression, biological function, and underlying mechanism of JMJD3 in BPH. Here, we identified that JMJD3 is a crucial driver of BPH progression. In this work, both scRNA and bulk sequencing data revealed that JMJD3 is upregulated in BPH, which was further validated in prostate tissues from BPH patients. Functionally, Overexpressing JMJD3 could promote cell proliferation and cell cycles in WPMY-1 and RWPE-1 cells, respectively. Whereas, blocking JMJD3 with GSK-J4 or siRNA may induce cell apoptosis, and inhibit cell proliferation and cell cycles in BPH-1 cells. Furthermore, inhibition of JMJD3 with GSK-J4 could alleviate both testosterone and lipopolysaccharide (LPS) induced BPH in vivo. Mechanistically, JMJD3 demethylates H3K27me3 at the promoter of TGF-β1 to promote its expression and then promotes disease progression in BPH. In summary, our findings illustrate JMJD3's contribution to BPH progression and offer a potential JMJD3-targeted therapy for BPH. Our findings illustrated JMJD3's contribution to BPH progression, and GSK-J4 offers a potential JMJD3-targeted therapy for BPH.

Background: Overactive bladder (OAB) is a common condition that affects both men and women, but its relationship with central obesity and the dietary intake has not been adequately elucidated. Objectives: Our study aims to investigate associations between central obesity replacement indices, dietary intake of sugar and lipids, and OAB risk using National Health and Nutrition Examination Survey 2005–2016 data. Design: Cross-sectional study. Methods: This study analyzed 24,675 adults (4848 OAB cases). Weight, body mass index, and other central obesity replacement indices (waist circumference, weight-adjusted waist index, waist-to-height ratio (WHtR), body roundness index (BRI)) and dietary nutrients intake (carbohydrate, sugars, fat, saturated fatty acids, monounsaturated fatty acids, polyunsaturated fatty acids (PUFAs), and cholesterol) were assessed. Propensity score matching (1:2) balanced covariates. Multivariable logistic regression and generalized additive models evaluated dose-response relationships. Results: All central obesity indices showed significant positive associations with OAB ( p < 0.001), with WHtR and BRI demonstrating the strongest effects (adjusted odds ratio (OR) = 2.04, 95% confidence interval: 1.80–2.30). Nonlinear relationships were observed, particularly for WHtR (degrees of freedom = 3.30–6.16). Dietary analysis revealed that OAB patients had significantly higher consumption of total energy, carbohydrates, and sugars (all p < 0.05), and higher sugar intake increased OAB risk (OR = 1.32, p = 0.0016), while PUFAs were protective (OR = 0.79, p = 0.0159). Conclusion: Central obesity replacement indices, especially WHtR and BRI, strongly predict OAB risk. Dietary modifications, including reducing sugars and increasing PUFAs intake, may complement abdominal fat reduction for OAB prevention. These findings highlight the importance of combined weight management and dietary modifications for OAB prevention in high-risk populations.

Prostate cancer remains one of the most common malignancies in men, and robot-assisted radical prostatectomy (RARP) is widely used for localized and selected locally advanced disease. However, balancing oncological control with urinary continence, erectile function, and neurovascular preservation remains challenging. This tension between technical capability and biological uncertainty has driven interest in artificial intelligence (AI) as structured support across the RARP workflow. This review summarizes AI applications in preoperative risk stratification, three-dimensional AI–driven augmented reality (3D-AI-AR) guidance, surgical video intelligence, predictive analytics, and performance assessment, with emphasis on clinical translation rather than technical novelty. Current evidence suggests that AI can support side-specific risk assessment, intraoperative orientation, outcome prediction, and objective feedback. In the prospective randomized RIDERS trial, 3D-AI-AR guidance during nerve-sparing RARP reduced residual positive surgical margins after selective excisional biopsies at preserved neurovascular bundles (22% vs. 39%) and postoperative radiotherapy (18% vs. 35%), and improved 12-month zero-pad continence recovery (91% vs. 71%), while potency and short-term biochemical recurrence (BCR) were similar between groups. Prediction models have reported an area under the receiver operating characteristic curve (AUC) of 0.77 for side-specific extraprostatic extension and an external-validation AUC of 0.89 for early BCR. Nevertheless, the field remains limited by retrospective designs, heterogeneous endpoints, limited external validation, cross-platform generalizability, workflow integration, and regulatory uncertainty. AI in RARP should therefore be regarded as assistive rather than substitutive. Routine implementation will require prospective multicenter validation, standardized reporting, calibrated clinical endpoints, and trustworthy human-centered deployment.

The broader clinical application of Bispecific T-cell engagers (BiTEs) is hindered by their short half-life, on-target off-tumor toxicity, and limited therapeutic effect for solid tumors. Herein, we constructed a bimetallic-enriched triple-kill nanobomb manganese/Co2+-dopamine@BiTE/HPT (MnO2/Co-DA@BiTE/HPT) based on metal-polyphenol to improve the immunosuppressive tumor microenvironment by activating innate and adaptive immunity, thereby enhancing the treatment efficacy of BiTEs (PD-L1/CD3). A hyaluronic acid-modified PD-L1 aptamer (HPT) was introduced to improve the active targeting of the nanobombs and bind with PD-L1 overexpressing colorectal cancer. Bimetallic (Mn2+/Co2+) activated the STING pathway; simultaneously, photothermal therapy (PTT) induces DNA fragmentation to cooperate with bimetallic to amplify the STING signal to “heat” the “cold” tumor microenvironment. The “hot” tumor with a large amount of T-cell infiltration facilitated BiTE recruitment of T cells to kill tumor cells. Furthermore, the efficient therapeutic potency of the triple-kill nanobombs (STING, BiTE, and PTT) was determined in subcutaneous colorectal cancer, distal, lung metastasis, and postoperative recurrence models, which indicated that MnO2/Co-DA@BiTE/HPT could improve the immune microenvironment, produce long-term immune memory, inhibit tumor growth, and prevent tumor recurrence and metastasis.

Abstract Background A multi‐centre, 2‐part, phase II study assessed adding rezvilutamide (a novel androgen receptor antagonist) to docetaxel in abiraterone‐refractory, metastatic castration‐resistant prostate cancer (mCRPC) patients who were naive to chemotherapy. Herein, we report results from part 1. Methods Part 1 encompassed both dose‐escalation and dose‐expansion phases. Eligible patients received oral rezvilutamide (160/240 mg, once daily [QD]) plus intravenous docetaxel (75 mg/m2, on the first day of every 3‐week cycle) for more than 10 cycles, followed by maintenance with rezvilutamide monotherapy (240 mg, QD). Rezvilutamide was administered daily starting from the second day of cycle 1. Docetaxel was co‐administered with oral prednisone at 5 mg twice daily. Safety served as the primary objective in Part 1. Results From 2, December 2020, to 5, August 2021, 36 patients were eligible for enrolment (18 patients with rezvilutamide 160 mg plus docetaxel and 18 patients with rezvilutamide 240 mg plus docetaxel). No one experienced dose‐limiting toxicity. 32 (88.9%) patients experienced grade 3 or higher treatment‐related adverse events. At week 12, 67.7% of the 31 evaluable patients showed a response in prostate‐specific antigen (PSA) levels. Among all 36 patients, the median times were 10.5 months (95% CI: 5.6–14.1) for PSA progression, 13.8 months (95% CI: 8.4–19.2) for radiological progression‐free survival and 16.2 months (95% CI: 12.9–22.5) for overall survival. The limitations were a small sample size and a non‐randomised design. Conclusions Rezvilutamide plus docetaxel followed by maintenance with rezvilutamide monotherapy demonstrated good tolerability and promising efficacy in chemotherapy‐naive, abiraterone‐refractory, mCRPC patients.

Background The Body Roundness Index (BRI) has been proved to be associated with several metabolic and age-related disorders, with epigenetic pathways potentially underlying these connections. We analyzed data from the Health and Retirement Database to investigate whether higher BRI is linked to epigenetic aging Methods Using cross-sectional data from the Health and Retirement Study, we investigated the relationship between BRI and epigenetic aging. Epigenetic age acceleration (EAA) was calculated from five established DNA methylation clocks as the residual values from regressing epigenetic age on chronological age. The continuous associations were evaluated using linear regression and restricted cubic spline models. Subgroup analyses were conducted to assess consistency across different population strata. Logistic regression was applied to examine the link between BRI and accelerated aging (EAA > 0). Results A total of 1,801 participants aged ≥ 50 years were included in this cross-sectional analysis, with a mean BRI of 6.01. Linear regression analyses demonstrated that higher BRI was significantly associated with increased epigenetic age acceleration based on GrimAge, PhenoAge, and DunedinPoAm. These findings remained consistent in restricted cubic spline analyses and across subgroup analyses. Logistic regression models further supported these associations, showing that the odds of accelerated aging rose by 19.7% for GrimAge, 31.8% for PhenoAge, and 38.8% for DunedinPoAm for each 2.27-unit increase in BRI. Conclusion BRI was strongly associated with epigenetic age acceleration measured by GrimAge, PhenoAge, and DunedinPoAm, suggesting that increased visceral adiposity may contribute to epigenetic alterations.

Background Oxidative stress (OS) is increasingly implicated in benign prostatic hyperplasia (BPH), yet the underlying cellular programs remain unclear. We integrated multi-omics and machine learning to identify OS-associated biomarkers and to characterize OS-linked stromal states, with targeted experimental validation. Methods Two bulk transcriptomic datasets (12 BPH, 16 controls) were integrated to identify DEGs and OS-associated DEGs, followed by WGCNA, enrichment analyses, and four machine-learning algorithms to prioritize hub genes and build a diagnostic nomogram. Consensus clustering defined molecular subtypes. Candidate compounds were screened in silico. Single-cell RNA-seq (124,616 cells) and spatial transcriptomics were analyzed for OS scoring, trajectories, and inferred intercellular communication. Experimentally, WPMY-1 prostatic stromal cells were exposed to LPS to induce OS; intracellular ROS (flow cytometry), ACOX2 expression (RT-qPCR/western blot), proliferation (EdU), and apoptosis (Annexin V) were assessed under ACOX2 overexpression or shRNA knockdown. ACOX2 expression in human prostate tissues was evaluated by immunohistochemistry. Results We identified 499 DEGs and 26 OS-DEGs. Machine learning converged on three upregulated hub genes: ACOX2, CTSB, and SERPINF1, which with diagnostic AUCs of 0.880 (0.753-1.000), 0.828 (0.663-0.993), and 0.854 (0.711-0.997); however, given the modest sample size, these findings should be interpreted as hypothesis-generating. Two BPH subtypes were identified (immune-infiltrated vs. non-immune). Single-cell analyses showed elevated OS scores across cell types, highest in fibroblasts; ACOX2-high fibroblasts were expanded in BPH and exhibited trajectory-associated increases in ACOX2 with enriched inferred signaling (including TNFSF12-TNFRSF12A). Spatial transcriptomics revealed regional OS heterogeneity and spatial association of hub-gene expression with OS-enriched areas. In vitro, LPS increased ROS and upregulated ACOX2, ACOX2 overexpression increased proliferation and reduced apoptosis, whereas knockdown showed opposite effects and attenuated LPS-associated proliferative phenotypes. IHC showed stronger ACOX2 staining in hyperplastic vs. normal prostate tissues. Conclusions These results nominate ACOX2, CTSB, and SERPINF1 as candidate OS-associated markers in BPH and support a hypothesis-generating multi-omics signature that warrants validation in larger independent human cohorts. Experimental perturbation and tissue staining provide validation for an ACOX2-associated activation-like phenotype under OS, motivating biomarker-guided stratification and OS-targeted therapeutic exploration.

Dual-atom nanozymes (DAzymes) have garnered considerable attention as catalysts for reactive oxygen species (ROS)-based therapies, effectively leveraging ROS generation within the tumor microenvironment (TME). Herein, we introduce the FeMn-NCe DAzymes, which are meticulously engineered for enhanced peroxidase (POD)-mimetic activity and potent radiosensitization to advance radioimmunotherapy. Density functional theory (DFT) calculations reveal that FeMn-NCe DAzymes lower the energy barrier and increase the substrate affinity, enabling highly efficient catalytic performance. Within the TME, these DAzymes efficiently convert overexpressed hydrogen peroxide (H2O2) into hydroxyl radicals (•OH), potentially activating the cGAS-STING immune pathway. This POD-mimetic catalysis is further accelerated under X-ray irradiation, significantly enhancing radiosensitization. Additionally, a uniform coating of ultrasmall gold nanoparticles on FeMn-NCe significantly enhances X-ray absorption within cancer cells. The incorporation of the STING agonist diABZI onto the DAzymes induces long-term antitumor immunity, reprograms the immunosuppressive TME, and effectively suppresses tumor growth and metastasis following a single low-dose X-ray treatment. This work highlights a valuable strategy for designing DAzymes to advance radiodynamic immunotherapy.

BACKGROUND:Benign prostatic hyperplasia (BPH) is a prevalent age-associated urological disorder marked by excessive proliferation of epithelial and stromal cells within the prostate. Resveratrol (Res), a naturally occurring polyphenol, has shown potential in treating various inflammatory and hyperproliferative disorders, yet its pharmacological mechanisms in BPH remain unclear. PURPOSE:This study sought to comprehensively identify the therapeutic targets and signaling pathways underlying the protective effects of Res against BPH by combining network pharmacology, multi-omics analyses, molecular dynamics (MD), and experimental validation. METHODS:We developed an integrative strategy that incorporates network pharmacology, single-cell and bulk transcriptomic data analysis, molecular docking, MD simulation, and experimental validation. Candidate targets of resveratrol associated with BPH were systematically identified and subjected to enrichment analysis for relevant biological processes and signaling pathways. Key targets were further validated at the protein level, and the involvement of critical signaling cascades was experimentally confirmed. RESULTS:Network pharmacology identified 228 intersecting targets of Res and BPH, from which three core genes (TGF-β1, IGF1, and ITGA4) were further pinpointed through transcriptomic integration. Single-cell RNA sequencing demonstrated marked upregulation of these targets in hyperplastic prostate tissues. Molecular docking and MD simulations demonstrated strong binding affinities and stable interactions between Res and the core proteins. Functional enrichment analysis identified the PI3K/AKT signaling cascade as a principal pathway influenced by Res. Subsequent in vitro assays using prostate cells confirmed that Res markedly suppressed cell proliferation, enhanced apoptotic activity, alleviated oxidative stress, and downregulated pro-inflammatory cytokine expression. Notably, Res significantly attenuated PI3K and AKT phosphorylation, supporting its inhibitory effect on this pathway as a key component of its therapeutic action. CONCLUSION:This study demonstrates that Res protects against BPH by modulating multiple targets and signaling pathways, particularly through inhibition of the PI3K/AKT axis. These findings offer mechanistic evidence for the multi-target actions of Res and underscore its potential as a phytotherapeutic candidate for BPH management.

Oncolytic viruses (OVs) are promising for cancer treatment as they specifically replicate in tumor cells. However, the systemic delivery of OVs still faces the challenges of poor tumor targeting, short circulation periods, and limited lytic efficacy. Herein, an OV-concealed targeting nanoagonist (OV-MnO2/HE) was prepared to enhance the delivery of OVs to triple-negative breast cancer (TNBC) via intravenous administration. Decomposable MnO2 biomineral shells covered the surface antigens of OVs to prevent their clearance after systemic administration. The targeting materials of HA-EGCG (HE) enhanced intratumoral accumulation via active targeting. After entering tumors, OV-MnO2/HE readily released Mn2+ and OVs, which could enhance the number of CD4+/CD8+ T cells and maturation dendritic cells (DCs) due to the synergetic effect of the STING pathway and OVs, thereby activating the immune response, resulting in the significant inhibition of TNBC growth. This work highlights the potential of the STING agonist in enhancing the antitumor efficacy of OVs and provides a potent platform for TNBC therapy.

INTRODUCTION:Clear cell renal cell carcinoma (ccRCC) is the most common subtype of kidney cancer and is associated with poor prognosis in advanced stages. This study aims to develop a prognostic model for patients with ccRCC based on a lysosome-related gene signature. METHODS:The clinical and transcriptomic data of kidney renal clear cell carcinoma (KIRC) patients were downloaded from TCGA, cBioportal, and GEO databases, and lysosome-related gene sets were acquired in the previous study. TCGA data were used as a training set to investigate the prognostic role of lysosomal-related genes in ccRCC, and cBioportal and GEO databases were used for validation. After the lysosome-related differentially expressed genes were found, machine learning method was used to construct a risk model, and Kaplan-Meier (K-M) and receiver operating characteristic curves were used to evaluate the performance of the model. RESULTS:Machine learning methods were utilized to identify seven gene signatures related to lysosome, which accurately predict the prognosis of ccRCC. Patients with higher risk scores demonstrate poorer overall survival (OS; HR: 2.467, 95% CI: 1.642-3.706, p < 0.001), and significant disparities in immune infiltration, immune score, and response to anticancer drugs are observed between the high-risk group and the low-risk group (p < 0.001). CONCLUSION:The prognostic model developed in this study demonstrates a high efficacy in accurately predicting the OS of ccRCC patients, thereby offering a novel perspective for the advancement of ccRCC treatment.

Background:Up to now, the underlying molecular mechanisms of benign prostatic hyperplasia (BPH) and prostate cancer (PCa) remain unclear. This study aimed to identify programmed cell death (PCD) associated genes in BPH and PCa development by integrated bioinformatics analysis and machine learning using publicly available genomic datasets. Methods:The GSE119195 and GSE55597 datasets were downloaded from the Gene Expression Omnibus (GEO) database, and differentially expressed genes (DEGs) were obtained using the Limma package for differential expression analysis. The intersection of core genes was filtered using four machine learning methods [least absolute shrinkage and selection operator (LASSO) regression, eXtreme gradient boosting (XGBoost), random forest, and Boruta]. Results:We identified 159 key genes from the intersection of two DEGs. Fifteen hub genes were obtained by intersecting 159 DEGs with PCD genes. Two hub genes [bone morphogenetic protein 5 (BMP5) and cytochrome p450 family 1 subfamily b member 1 (CYP1B1)] were ultimately chosen after further reducing the dimension of 15 hub genes using four machine learning techniques. The nomogram's findings showed that BMP5 and CYP1B1 together were a reliable indicator of the risk factors of PCa and BPH. Furthermore, the risk score in the GSE55597 dataset displayed an area under the curve (AUC) value of 0.988. Moreover, the risk score in the GSE119195 dataset displayed an AUC value of 1. In addition, PCa patients' prognosis was significantly correlated with CYP1B1, Gleason score, and tumor (T) in the tumor-node-metastasis (TNM) stage. Conclusions:We established a prediction model with a high predictive ability in the analyzed datasets. As a bioinformatics analysis, our study indicated that there are possible DEGs in the prostate, such as BMP5 and CYP1B1, which might provide further insight for the pathogenesis of BPH and PCa. However, these findings warrant further validation in prospective, real-world clinical studies.

Biomaterial-based modulation of the microenvironment represents a promising neuroprotective strategy for spinal cord injury (SCI). We first fabricated hyaluronic acid (HA)-graft-epigallocatechin gallate (EGCG) nanoparticles (HEN). These nanoparticles can synergistically exert anti-inflammatory and antioxidant effects, while HA can modulate the immune microenvironment. To further enhance therapeutic efficacy, Cabazitaxel (Cab) was incorporated into HEN to generate multifunctional Cabazitaxel-loaded HA-EGCG nanoparticles (Cab-HEN), which inhibited scar formation and modulated microtubule homeostasis, thereby promoting the beneficial regeneration of nerve axons in a rat SCI model. Through in situ injection at the T9 injury site, Cab-HEN significantly downregulated the expression of inflammatory factors, effectively mitigated oxidative damage induced by excessive reactive oxygen species (ROS), and reduced fibrin deposition and scar formation. Furthermore, Cab-HEN regulated microtubules and enhanced the regeneration of nerve fibers. Evaluations based on electrophysiological assessments, Basso, Beattie, and Bresnahan (BBB) scores, and bladder function recovery revealed the nanoparticles’ remarkable therapeutic efficacy in SCI. Therefore, biomaterials can facilitate axonal regeneration, tissue remodeling, and functional restoration following injury.

Background: Clear cell renal cell carcinoma (ccRCC) is a prevalent urological malignancy, accounting for approximately 1.6% of all cancer-related deaths in 2022. While endocrine-disrupting chemicals (EDCs) have been implicated as risk factors for ccRCC, the toxicological profiles and immune mechanisms underlying Bisphenol A (BPA) exposure in ccRCC progression remain inadequately understood. Materials and Methods: Protein-protein interaction (PPI) analysis and visualization were performed on overlapping genes between ccRCC and BPA exposure. This was followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses to elucidate potential underlying mechanisms. Subsequently, 108 distinct machine learning algorithm combinations were evaluated to identify the optimal predictive model. An integrated CoxBoost and Ridge regression model was constructed to develop a prognostic signature, the performance of which was rigorously validated across two independent external datasets. Finally, molecular docking analyses were employed to investigate interactions between key genes and BPA. Results: A total of 114 overlapping targets associated with both ccRCC and BPA were identified. GO and KEGG analyses revealed enrichment in cancer-related pathways, including pathways in cancer, endocrine resistance, PD-L1 expression and PD-1 checkpoint signaling, T-cell receptor signaling, endocrine function, and immune responses. Machine learning algorithm selection identified the combined CoxBoost-Ridge approach as the optimal predictive model (achieving a training set concordance index (C-index) of 0.77). This model identified eight key genes (CHRM3, GABBR1, CCR4, KCNN4, PRKCE, CYP2C9, HPGD, FASN), which were the top-ranked by coefficient magnitude in the prognostic model. The prognostic signature demonstrated robust predictive performance in two independent external validation cohorts (C-index = 0.74 in cBioPortal; C-index = 0.81 in E-MTAB-1980). Furthermore, molecular docking analyses predicted strong binding affinities between BPA and these key targets (Vina scores all <-6.5 kcal/mol), suggesting a potential mechanism through which BPA may modulate their activity to promote renal carcinogenesis. Collectively, These findings suggested potential molecular mechanisms that may underpin BPA-induced ccRCC progression, generating hypotheses for future experimental validation. Conclusions: These findings enhance our understanding of the molecular mechanisms by which BPA induces ccRCC and highlight potential targets for therapeutic intervention, particularly in endocrine and immune-related pathways. This underscores the need for collaborative efforts to mitigate the impact of environmental toxins like BPA on public health.

Studies have demonstrated an elevated risk of urological malignancies in individuals undergoing dialysis, which consequently leads to unfavorable prognoses and diminished quality of life for patients with end-stage kidney disease. Nevertheless, the absence of standardized recommendations for cancer screening and limited utilization of conventional screening methods within the dialysis population remain prevalent issues. Methods: A meta-analysis was conducted on cohort studies published prior to June 2024, aiming to quantify the cancer risk among individuals undergoing dialysis. Random-effects meta-analyses were employed to combine standardized incidence rates (SIRs) along with their corresponding 95