Background Artificial intelligence (AI)-based chatbots have emerged as significant sources of medical and general information. However, their accuracy and completeness in addressing clinical trial-related adverse events (ctrAEs) remain understudied. Methods This study evaluates the performance of three large language models (GPT-4o, Gemini 1.5 pro and DeepSeek-R1) in responding to 62 clinically validated questions spanning eight clinical trial-related general questions, seven ctrAE categories (gastrointestinal, Central Nervous System, Allergic Reactions, Respiratory, Cardiac, Liver Function, Kidney) and 18 patient-specific scenarios. Expert evaluations of accuracy and completeness were conducted using a 4-point Likert scale (1: least; 4: most). Results Overall, all engines performed well in terms of accuracy and completeness. Scores indicating significant inaccuracy or incompleteness (1–2) were not found in DeepSeek, and exceptionally rare for ChatGPT, with only 6 out of 496 answer ratings (1.21%) falling into this category. Of the 62 questions evaluated, all 8 physician raters assigned DeepSeek a score of 4 (fully accurate or complete) for 39 questions related to accuracy and 34 questions related to completeness. In the 18 patient scenarios, DeepSeek's average accuracy score was 3.833 (median = 4), while the average completeness score was 3.799 (median = 4). Conclusion DeepSeek exhibits robust capabilities in delivering accurate and comprehensive guidance on ctrAE management, outperforming ChatGPT and Gemini. Its consistent high ratings across diverse clinical contexts suggest potential utility in supporting real-time decision-making for trial-related adverse events. Limitations include reliance on simulated scenarios and rater subjectivity. Future studies should validate these findings in live clinical settings. This work underscores the importance of model-specific validation prior to clinical implementation.

Renal cell carcinoma (RCC) is a prevalent malignancy of the urinary system. Despite significant advances achieved through targeted therapies and immunotherapies, therapeutic resistance remains a major obstacle to sustained clinical efficacy. This review comprehensively examines the molecular mechanisms driving resistance to both targeted therapy and immunotherapy in RCC from a multi-omics perspective. By integrating findings across diverse omics layers, we underscore the pivotal role of multi-level regulatory networks in mediating drug resistance and immune evasion. Our objective is to provide an in-depth understanding of these resistance mechanisms and to establish a theoretical framework for developing innovative therapeutic strategies aimed at overcoming resistance, thereby facilitating the advancement of precision oncology in RCC.

BACKGROUND:To investigate fibrosis-related gene expression profiles in benign ureteral strictures and their association with restenosis after ureteroplasty and to develop a predictive risk score model. METHODS:A total of 100 patients with benign strictures who underwent ureteroplasty were included.Stenotic tissues were collected intraoperatively, and the expression levels of 15 fibrosis-related genes were determined by quantitative real-time PCR. According to whether restenosis occurred at 12 months postoperatively, the patients were assigned to stenotic group (n = 39) and non-stenotic group (n = 61). Independent predictors were identified using logistic regression, a risk score model was constructed and model performance was assessed using receiver operating characteristic curve, calibration curves and decision curve analysis (DCA). The restenosis-free rates of the risk groups were compared through Kaplan-Meier survival analysis, and internal validation was performed through Bootstrap resampling. RESULTS:High expression levels of type I collagen α1 chain (COL1A1), transforming growth factor-β1 (TGFB1), Snail family member 1 (SNAI1), SMAD family member 3 (SMAD3) and thrombospondin 2 (THBS2) genes were identified as independent risk factors for postoperative restenosis (all p < 0.05). Kaplan-Meier analysis revealed that the restenosis-free rate at 12 months was significantly lower in the high-risk group than in the low-risk group (51.02% vs. 70.59%, log-rank p = 0.007). The area under the curve (AUC) of the risk scoring model was 0.854 [95% confidence interval (CI): 0.772-0.973], with a sensitivity of 87.12% and specificity of 84.55%. Bootstrap internal validation yielded a corrected AUC of 0.848 (95% CI: 0.812-0.891), confirming the model's stability. The calibration curve demonstrated good agreement between predicted probabilities and observed outcomes (Hosmer-Lemeshow test, p > 0.05). DCA showed that the model provided a net clinical benefit across a wide range of threshold probabilities. Further analysis showed that the expression levels of the above five genes were significantly positively correlated with the pathological fibrosis grade of stenotic tissues (all p < 0.001). CONCLUSIONS:The high expression levels of COL1A1, TGFB1, SNAI1, SMAD3 and THBS2 in benign ureteral strictures is closely related to the degree of tissue fibrosis and postoperative restenosis. The risk scoring model based on these genes showed good predictive performance and can thus serve as useful tool for clinical individualised treatment and prognostic assessment.

ABSTRACT Tumorigenesis can be induced by diverse environmental carcinogens, with mercury (Hg)—a global pollutant that accumulates in humans throughout life, crosses the blood‐brain and placental barriers, and is poorly excreted—classified as a Group 2B carcinogen; however, its contribution to human tumorigenesis remains insufficiently characterized. This critical knowledge gap stems primarily from confounding effects of human co‐exposure to other carcinogens and detoxifying agents, coupled with unclear correlations along the external exposure‐internal Hg burden‐tumorigenesis continuum due to insufficient organ‐specific Hg data in humans. To improve the understanding of Hg's role in tumorigenesis, we propose a research paradigm that integrates: 1) advancing Hg speciation analysis in human tissues and internal dynamics of Hg through in vivo transformation studies, to map organ‐specific Hg distributions; and 2) constructing a comprehensive database of demographic factors, Hg exposure profiles, and tumor biomarkers for artificial intelligence‐driven analyses to disentangle Hg‐specific effects from confounding factors. Bridging the gap between Hg exposure and tumorigenesis could help identify overlooked tumorigenic factors, advance targeted prevention strategies, and guide decision‐making in environmental and public health, ultimately improving public health outcomes.

Background In metastatic clear-cell renal cell carcinoma (mccRCC), residual lesions on CT after immune checkpoint blockade (ICB)-based therapy often remain anatomically visible despite uncertain biological viability. In this study, we evaluated whether 1-year [18F]fluorodeoxyglucose ([18F]FDG)-PET–CT-defined complete metabolic response (CMR), assessed at a prespecified landmark among patients who remained progression free throughout the first treatment year, provides complementary prognostic information beyond CT-based response assessment. Methods In this multicentre, observational cohort study with prospective follow-up at eight tertiary hospitals in China, we included patients (≥18 years) with histologically confirmed mccRCC who received first-line ICB-based combination therapy, remained progression free per Response Evaluation Criteria in Solid Tumours (RECIST) version 1.1 throughout the first treatment year, and completed paired baseline and 1-year [18F]FDG-PET–CT scans. Patients initiated first-line therapy between Jan 1, 2021, and Jan 31, 2024, and the analytical data cutoff was April 30, 2025. Response at the 1-year landmark was assessed using RECIST 1.1 and modified European Organisation for Research and Treatment of Cancer criteria. The primary endpoints were progression-free survival and overall survival from the 1-year landmark. All patients meeting prespecified eligibility criteria constituted the full analytical set for the primary endpoints. Findings Of 867 patients screened after baseline [18F]FDG-PET–CT, 339 met the prespecified landmark eligibility criteria and formed the final 1-year landmark cohort. 268 (79%) of 339 patients were male and 71 (21%) were female. At the 1-year landmark, conventional CT identified complete response in 28 (8%) of 339 patients and [18F] FDG-PET–CT identified CMR in 78 (23%) patients. Median follow-up from the 1-year landmark was 17·0 months (IQR 5·7–24·7). Median progression-free survival was 22·6 months (95% CI 20·0–not reached) in the CMR group versus 10·9 months (8·9–13·5) in the non-CMR group (hazard ratio [HR] 0·32, 95% CI 0·22–0·48; p<0·0001). Median overall survival was not reached (95% CI 30·0–not reached) in the CMR group versus 24·6 months (21·7–not reached) in the non-CMR group (HR 0·13, 95% CI 0·05–0·33; p<0·0001). In a multivariable model adjusting for International Metastatic Renal Cell Carcinoma Database Consortium risk, sarcomatoid features, CT response at 1 year, and maximum standardised uptake value at baseline, CMR remained independently associated with progression-free survival (time-averaged adjusted HR 0·43, 95% CI 0·27–0·68; p=0·00040) and overall survival (adjusted HR 0·19, 95% CI 0·06–0·62; p=0·0058). Interpretation In patients with mccRCC who remained progression free throughout the first year of first-line ICB-based therapy, 1-year [18F]FDG-PET–CT-defined CMR provided clinically relevant prognostic stratification beyond anatomical response assessment. These findings support prospective evaluation of PET-guided treatment de-escalation strategies. Funding National Natural Science Foundation of China, Basic Research Program of Jiangsu Province.

Inspired by the environmental trend focusing on eco-friendly biomedicine, green biodegradable hydrogels are potential candidates for implantable materials of urological repair, localized therapy and device surface modification. In the urological setting, green hydrogels are loosely defined as water-rich polymer networks derived partially or entirely from renewable or bio-based feedstocks, made using mild and low-toxicity crosslinking strategies and engineered to degrade into low-physiological burden/low aquatic toxicity products. This review summarizes advancements in material sources, green fabrication strategies, degradation behavior, applications and translational barriers of biodegradable hydrogels in urology. Currently available evidence suggests that these systems can simultaneously improve urethral reconstruction, bladder wall repair, intravesical drug retention, and even the surface protection of catheters or stents via combining elements of wet adhesion, mechanical adaptability, controlled release, antifouling activity and microenvironment-responsive degradation. Reverse thermosensitive hydrogel formulations have convincingly validated the concept of local chemoablation in select urothelial tumors, while hydrogel spacers have been shown to be useful for prostate radiotherapy. Nevertheless, the majority of regenerative and anti-infective applications are still confined to preclinical or animal-study settings. Uncertain long-term biosafety, unknowns regarding degradation-product clearance from the body, insufficient mechanical stability during dynamic urine exposure, changes in physical properties induced by sterilization stressors, manufacturing variability and cost-effectiveness of systems for large-scale application as well as lack of clarity on regulatory pathways are some key barriers. Future directions in green urology must ensure comprehensive integration of these points: the design with renewables, engineering for tunability to urinary microenvironments, rigorous three-dimensional preclinical testing on biological model systems, scale-up renewable manufacturing and clinically meaningful mechanistic and functional endpoint evaluation to de-risk clinical translation of biodegradable hydrogels over time.

Clear cell renal cell carcinoma (ccRCC) is the most common and aggressive form of renal malignancy. Although therapeutic strategies such as targeted agents and immune checkpoint inhibitors have progressed, the prognosis for patients with advanced ccRCC remains unsatisfactory. Cysteine-rich epidermal growth factor-like domain 2 (CRELD2), a protein localized to the endoplasmic reticulum, is involved in several biological processes, yet its function in ccRCC has not been clearly characterized. We conducted an integrative multi-omics study to investigate the role of CRELD2 in ccRCC. The study incorporated mendelian randomization (MR), bulk and single-cell RNA sequencing, immunohistochemistry, immune infiltration analysis, and spatial transcriptomics to explore expression patterns, prognostic value, cellular distribution, and potential biological implications of CRELD2. MR and summary-data-based MR analyses identified CRELD2 as a genetically supported candidate associated with RCC susceptibility. Elevated CRELD2 expression was confirmed at both mRNA and protein levels in ccRCC and correlated with worse overall survival independently. Single-cell analysis revealed preferential CRELD2 enrichment in endothelial and B-cell compartments, with CRELD2-high subsets showing shared enrichment of TNFA/NFκB, MTORC1, ROS, and oxidative phosphorylation pathways. Immune infiltration analysis linked CRELD2 expression to a B-cell-related immune infiltration profile, while spatial transcriptomics showed CRELD2 enrichment in tertiary lymphoid structure (TLS)-associated regions. Across single-cell and spatial analyses, TNFA/NFκB-related immune-inflammatory signaling represented a recurrent CRELD2-associated pathway feature. This study pointed out the CRELD2-centered TLS-associated immune-inflammatory conceptual axis, linking CRELD2 expression, endothelial/B-cell cellular contexts, B-cell-related immune infiltration, TLS-associated spatial localization, and recurrent TNFA/NFκB pathway enrichment via multi-omics and supporting it as a candidate therapeutic biomarker in ccRCC for further functional investigations.

Clear cell renal cell carcinoma (ccRCC) is characterized by high metastatic potential and frequent resistance to conventional therapies, highlighting the need for a deeper understanding of its tumor microenvironment. Here, we integrated single-cell RNA sequencing and spatial transcriptomics from large ccRCC cohorts to map the cellular landscape of ccRCC. We identified a distinct stromal cell subpopulation, Melanoma Cell Adhesion Molecule, MCAM+ endothelial cells (MCAM+ ECs), which spatially associates with EMT-like tumor cells and promotes disease progression. Mechanistically, our findings suggest that MCAM+ ECs facilitate metastatic features via a LAMB1-ITGB1-RhoA signaling axis, contributing to epithelial-mesenchymal transition (EMT) and extracellular matrix remodeling. Furthermore, transcriptional analysis and experimental validation revealed that SMAD1 acts as a pivotal regulator of MCAM+ EC reprogramming by modulating MCAM and LAMB1 expression. To assess clinical relevance, we applied an integrative machine learning framework to develop an MCAM+ EC-based Risk Score (MERS). This model effectively stratified patients by overall survival and metastatic risk, demonstrating superior prognostic accuracy compared to standard clinicopathological features. Collectively, our study elucidates a critical tumor-stroma crosstalk mechanism governed by the SMAD1-MCAM-LAMB1-ITGB1-RhoA axis, providing novel mechanistic insights into the metastatic process and identifying potential candidates for therapeutic intervention in ccRCC.

Abstract Background The rapid advancement of digital pathology has opened unprecedented opportunities for intelligent diagnosis in renal cell tumor. However, there remains a significant gap in the availability of reliable deep learning models capable of comprehensive kidney cancer detection, classification, grading, and survival prediction. Method This study retrospectively analyzed 11,135 whole-slide images (WSIs) from 7033 patients with renal tumor, sourced from four medical centers and two public cohorts. Histopathological representations were extracted using the foundation model Prov-GigaPath. A full-stack renal tumor diagnosis and prognosis framework was developed by combining fully supervised learning and weakly supervised multi-instance learning to enable both regional characterization and patient-level inference. Results The deep learning model demonstrated high accuracy in identifying normal tissue (AUC = 0.990), tumor tissue (AUC = 0.982), necrosis tissue (AUC = 0.994), sarcomatoid differentiation (AUC = 0.967), and pseudocapsule tissue (AUC = 0.990) across various pathological types of renal cell tumor. For nine major subtypes of renal cell tumor, classification AUC reached 0.956–0.998 across multi-center validation cohorts. WHO/ISUP nuclear grade prediction for clear cell renal cell carcinoma (ccRCC) and papillary renal cell carcinoma (pRCC) achieved an AUC of 0.867. A whole-slide-derived pan-renal cell tumor pathological risk score independently predicted overall survival and significantly outperformed WHO/ISUP grading in prognostic stratification ( p < 0.001). Conclusions We developed and validated a comprehensive AI framework integrating tissue-region detection, renal tumor subtype classification, nuclear grading, and survival prediction. These findings support its potential as a decision-support tool for renal tumor pathology, while prospective workflow-based studies are warranted to determine its clinical utility and impact on pathologist performance.

Making the decision between technically challenging partial nephrectomy (PN) and radical nephrectomy (RN) in patients with complex renal cell carcinoma (RCC) remains a significant challenge for urologists. Rapid glomerular filtration rate (GFR) decline (annual decline >3 mL/min/1.73 m²) after RN is considered an abnormal renal function state, and if this risk can be predicted preoperatively, PN may be pursued even when technically demanding. We retrospectively analyze contrast-enhanced computed tomography images and clinical data from 1621 patients across multiple centers. A multimodal deep learning model is developed to predict rapid GFR decline after RN. The model achieves an area under the curve of 0.788-0.873 in external test sets. It stratifies patients into high- and low-risk groups with significantly different risks of chronic kidney disease progression. Here we show that the model demonstrates potential for assisting treatment decisions in patients with complex RCC for whom PN is challenging but feasible.

Macrophages play critical roles in tumorigenesis and progression; however, their functions in renal cell carcinoma (RCC) remain insufficiently characterized. In this study, we leveraged multiple perspectives, including bulk transcriptomics, single-cell RNA sequencing (scRNA-seq), and spatial transcriptomics, to conduct an integrated analysis of various databases. We identified two macrophage-associated gene signatures, SLC11A1 and IFI30, and established a classifier based on these genes that correlates with different RCC prognoses and molecular patterns. This classifier significantly predicts adverse outcomes for RCC patients and demonstrates marked differences in drug sensitivity analysis and immune infiltration. Furthermore, we conducted an in-depth analysis at the scRNA-seq and spatial transcriptomics levels to characterize the pseudotime trajectory, metabolism, and communication of macrophages expressing SLC11A1 or IFI30. We also validated the expression and functional impact of these two genes in tumor cell lines through clinical samples and in vitro experiments. This study emphasizes the significant association between macrophages and the diverse clinical features and molecular landscapes of RCC. Evaluating the characteristics of macrophages in RCC enhances our understanding of the tumor microenvironment and paves new avenues for targeted therapeutic strategies for RCC.

OBJECTIVE:The effectiveness of combining immune checkpoint inhibitors (ICIs) and tyrosine kinase inhibitors (TKIs) in neoadjuvant therapy for renal cell carcinoma (RCC) remains unclear. This study aim to compare the efficacy and safety of neoadjuvant ICI plus TKI combination therapy versus TKI monotherapy in locally RCC patients. METHODS:This study included 185 cases of locally RCC disease(TanyNanyM0) receiving neoadjuvant therapy from 29 centers across China from January 2019 to Feburary 2024. Primary endpoint was the objective response rate (ORR) in all patients and patients with tumor thrombus (TT). Secondary endpoints included recurrence-free survival (RFS), overall survival (OS), surgical outcomes, and safety. Statistical analysis was performed to compare the results between 2 groups. RESULTS:Combination therapy group had higher ORR compared to the TKI monotherapy group(30.9% vs. 16.3% in all patients, 34.5% vs. 15.6% in patients with TT) and pCR rate (14.8% vs. 0%). RFS rates were improved in patients with TT receiving combination therapy (P = .047). Furthermore, the combination therapy group had lower blood loss during surgery (200 mL vs. 300 mL, P = .004). The main limitation is the retrospective study design. CONCLUSIONS:Neoadjuvant ICI plus TKI combination therapy showed promising efficacy and acceptable toxicity. These findings suggest that further investigation is warranted to explore the potential of this treatment approach.

4590 Background: UTUC is rare and highly aggressive. The prognosis is poor, especially for high-risk patients, even after radical surgery. Adjuvant chemotherapy is the standard therapy, but with limited efficacy, indicating a need for more effective regimens. RC48, an anti-HER2 antibody-drug conjugate, combined with toripalimab, an anti-PD-1 monoclonal antibody, has shown promising results in locally advanced or metastatic urothelial carcinoma (C014 trial). We evaluate the efficacy and safety of RC48 combined with toripalimab as adjuvant therapy for patients with HER2 IHC 2+/3+ UTUC after radical surgery. Methods: This is a single-arm, prospective, phase 2 clinical trial (NCT05917158). Eligible criteria were patients with histologically confirmed HER2 IHC 2+/3+ UTUC after radical surgery and were staged as T2-4NanyM0 or TanyN1-2M0, with no prior neoadjuvant therapy. The intervention was intravenous RC48 (2 mg/kg) combined with toripalimab (3 mg/kg) triweekly for 6 cycles, followed by toripalimab (3 mg/kg) triweekly for up to 1 year. The primary endpoint was DFS, and the secondary endpoints were OS, safety, and MRD analysis. Results: 45 patients (35 males [77.8%], median age 68 years [IQR 58-71]) were enrolled. The patients were staged as: 43 (95.6%) in II, 1 (2.2%) in III, and 1 (2.2%) in IV. All patients were HER2-overexpression (80% in IHC 2+, 20% in IHC 3+). 25 patients (55.6%) met cisplatin-ineligibility. By the data cutoff date on January 14, 2025, the median follow-up time was 12.2 months (IQR 6.7-17.6). 4 relapses occurred: 2 in lymph nodes, 1 in the prostate, and 1 in lymph nodes and the bladder. The 1-year DFS rate was 90.0%, and the median DFS has not been reached. All patients experienced treatment-related adverse events (TRAEs). The most common TRAEs were hypoesthesia (51.1%), increased blood glucose (48.9%), anemia (46.7%), increased creatinine (46.7%), and hypertriglyceridemia (46.7%). TRAEs of grade ≥3 occurred in 20% of patients. 8.9% of patients experienced immune-related adverse events, including rash and hypothyroidism. Among the patients, 16 (35.6%) completed treatment, 19 (42.2%) were still undergoing intervention, 4 (8.9%) discontinued therapy due to TRAEs: 1 with hypoesthesia, 1 with lymphocytopenia and hypoesthesia, 1 with nausea, vomiting, and decreased appetite, and 1 with pruritus and diarrhea, and 2 withdrew after completing 4 cycles of combined regimen due to personal reasons. No deaths occurred during the follow-up period. Conclusions: This is the first prospective clinical trial evaluating the efficacy and safety of the new adjuvant regimen for patients with HER2-IHC 2+/3+ UTUC. It showed promising DFS outcomes and a manageable safety profile, highlighting its potential as a new adjuvant therapy in patients with HER2-IHC 2+/3+ UTUC. Clinical trial information: NCT05917158 .

Therapeutic resistance remains a defining challenge in oncology, limiting the durability of current therapies and contributing to disease relapse and poor patient outcomes. This review systematically integrates recent progress in understanding the molecular, cellular, and ecological foundations of drug resistance across chemotherapy, targeted therapy, and immunotherapy. We delineate how genetic alterations, epigenetic reprogramming, post-translational modifications, and non-coding RNA networks cooperate with metabolic reprogramming and tumor microenvironment remodeling to sustain resistant phenotypes. The influence of the microbiome is highlighted as an emerging determinant of therapeutic response through immune modulation and metabolic cross-talk. By summarizing key regulatory circuits, We establishe a unified framework linking clonal evolution, metabolic adaptability, and tumor ecological dynamics. We further synthesizes novel therapeutic strategies that convert resistance mechanisms into therapeutic vulnerabilities, including synthetic lethality approaches, metabolic targeting, and disruption of stem cell and stromal niches. Advances in single-cell and spatial omics, liquid biopsy, and artificial intelligence are emphasized as transformative tools for early detection and real-time prediction of resistance evolution. This review also identifies major translational gaps in preclinical modeling and proposes precision oncology frameworks guided by evolutionary principles. By bridging mechanistic understanding with adaptive clinical design, this work provides an integrated roadmap for overcoming therapeutic resistance and achieving sustained, long-term cancer control.

Renal cell carcinoma - related thrombus arising within venous system (venous tumor thrombus, VTT) represents a distinct compartment within cancer, situated at the frontline with the continual interaction with host blood cells. Various host immune blood cells may possibly interact with VTT influencing its biology. While many authors have reviewed the current state-of-the-art of the management of VTT, its biology and microenvironment has not been comprehensively reviewed to date. In this narrative review, we described the current concepts on formation of thrombus, its histopathology, immune microenvironment, genetic and molecular features with potential impact on prognostication and tailored therapy. Although it is the sophisticated and challenging surgery that remains the primary modality in the management of RCC with VTT, recent advances in the research on cancer biology and microenvironment shed some light on the numerous future perspectives. The formation of tumor thrombus is a complex process, understanding of which may trigger onset of novel therapies leading to the improvement of not only oncological results but also patients' safety in these life-threatening conditions.

Bladder cancer (BLCA) is a common urinary malignancy with high metastatic potential. However, the mechanisms underlying its progression remain unclear. This study aimed to investigate the role and regulatory mechanisms of NR4A3, a nuclear receptor involved in apoptosis and tumor suppression, in BLCA progression, particularly its impact on anoikis resistance and metastasis. NR4A3 expression levels were analyzed using the GEPIA database. Functional studies were conducted by overexpressing NR4A3 in adherent and suspension-cultured BLCA cells. Apoptosis, invasion, migration, and ER stress marker (Bip and CHOP) expression were evaluated. Subcutaneous and lung metastasis models in BALB/c nude mice were used for in vivo validation. GEPIA analysis showed that NR4A3 is significantly downregulated in BLCA. NR4A3 overexpression increased apoptosis, reduced invasion and migration, and upregulated Bip and CHOP expression. In vivo, NR4A3 overexpression significantly reduced lung metastasis in BALB/c nude mice (n = 8 per group, p < .001). Mechanistically, NR4A3 promoted ER stress by regulating the EWSR1/Ezrin pathway, thereby suppressing anoikis resistance. NR4A3 functions as a tumor suppressor in BLCA by enhancing endoplasmic reticulum stress and inhibiting anoikis resistance through the EWSR1/Ezrin pathway. It may serve as a promising therapeutic target for metastatic BLCA.

Background/Objectives: We focused on the expression of a novel immune marker, cytoplasmic stimulator of interferon genes (STING), in the cohort of primary renal cell cancer (RCC) with venous tumor thrombus (VTT), in conjunction with the assessment of tumor-infiltrating leucocytes (TILs). Methods: The study group comprised 82 patients with clear cell RCC and VTT, operated on in the years 2012–2019 in two university urological centers. Tissue microarrays were constructed, and respective antibodies were used for staining purposes. The biomarkers were analyzed in primary RCC and VTT. Results: The frequency of STING expression in both analyzed compartments was similar (p = 0.18). Its presence correlated with no clinicopathological features but for necrosis in VTT only (p = 0.0023). PD-L1 expression in the primary tumor was associated with STING in tumor cells in the same compartment (p = 0.02). On the contrary, VISTA expression was correlated with the presence of STING in VTT. TIL presence was associated with positive PD-L1 (p = 0.008) and STING (p < 0.05) expression in the primary tumor. Strong STING expression in VTT was associated with inferior overall survival (OS) (p = 0.0061). TIL presence emerged as a robust prognostic factor for OS in both primary tumor (p = 0.021) and VTT (p = 0.034). Conclusions: We presented for the first time the prognostic values of STING in a contemporary cohort of RCC patients with VTT. STING expression in VTT showed prognostic potential, while TIL assessment proved to be a particularly valuable prognostic tool that can be readily implemented in routine pathological evaluation.

Renal cancer, particularly clear cell renal cell carcinoma (ccRCC), is characterized by significant intratumoral heterogeneity, which poses challenges for diagnosis and treatment. Single-cell sequencing (SCS) provides unprecedented insights into the cellular landscape of renal cancer, allowing for detailed characterization of tumor heterogeneity at the single-cell level. This review highlights how SCS has been instrumental in elucidating the origins of different renal cancer subtypes, understanding mechanisms of tumor initiation and progression, and dissecting the complex tumor microenvironment (TME). It discusses the identification of novel biomarkers and therapeutic targets, as well as the potential of SCS to inform personalized treatment strategies. The review also explores the integration of SCS with spatial omics technologies, which enhances the understanding of cellular interactions within their spatial context. Moreover, it addresses the challenges and future directions in applying SCS to clinical practice, emphasizing its significance in advancing renal cancer biology and improving clinical interventions.

Surgery has undergone a revolutionary development since the innovations in anesthesiology, aseptic techniques, and antibiotics. The use of modern techniques, especially minimally invasive techniques, has led to a new era of microsurgery and reduced patient trauma. Nevertheless, the new technologies have also brought about a diversification of surgical equipment and complexity of operations, prolonging physician training cycles and increasing costs. The emergence of surgical robots has solved the challenge of operating in small anatomical spaces, and their technology has continued to advance and has been used in several scenarios in the medical field to improve medical efficiency. This review systematically summarizes the technological evolution of surgical robots, the current status of their clinical applications, and provides a comprehensive assessment of their advantages and challenges. Further, this paper discusses the technological improvement paths of surgical robots and predicts their future development directions, including intelligence, specialization, precision, minimally invasiveness, and the enhancement of telesurgical capabilities. These advances will deepen the understanding of the development path of surgical robotics technology, facilitate the integration and dissemination of related knowledge, and promote the clinical application and technological innovation of surgical robots.