The clinic was established in July 2024 within the hospital’s existing specialty nursing outpatient service framework. Its operating model included staffing and qualification requirements, professional training, clearly defined nursing responsibilities, physician–nurse collaboration, standardized procedures, information-system support and quality management. Nurses worked within their authorized scope of practice, while urologists participated in medical assessment and treatment decisions when required. The service had four reported components: patient assessment and follow-up planning; treatment follow-up and adverse-event monitoring; rehabilitation guidance and health promotion; and assistance with healthcare policies and basic nursing care.

Monthly registrations increased from 147 in July 2024 to a peak of 710 in August 2026, with fluctuations during the reporting period. Total registration fees were CNY 152,758. The clinic delivered 14,246 prostate cancer-related injections, 3,523 urinary catheterizations, 2,777 intravesical instillation procedures and 2,142 urinary catheter removals. It also assisted patients with prostate or bladder cancer in applying for outpatient chronic and special disease insurance benefits. The study reports these counts as routine service activities, but it did not compare the procedures with those delivered elsewhere or evaluate their individual clinical effects.

Follow-up management was integrated into the clinic’s information system, which contained records for 1,111 patients. Of these, 953 patients had been followed up and 951 had successful follow-up records. Nurses also executed 3,553 follow-up tasks, of which 3,547 were successful, corresponding to the reported 99.83% task-level rate. The descriptive data do not specify the duration or effectiveness of patient follow-up, assess whether missed contacts influenced treatment adherence or health outcomes, or establish how the results would compare with another care model.

Because the research covered one tertiary hospital and relied on routinely collected records, it cannot establish how the clinic would operate in smaller facilities, under different staffing arrangements or in other health systems. The findings offer a documented example of a nurse-led outpatient service with defined responsibilities, standardized workflows, follow-up documentation and collaboration with urologists. The authors stated that further research is needed to evaluate the model’s clinical outcomes and economic implications. Accordingly, the registration growth, procedural workload and high proportion of completed follow-up tasks should be interpreted as descriptions of implementation and recorded service delivery, not as evidence of improved survival, fewer complications, lower costs or other patient benefits.

Subject of Research: Operation and service activity of a nurse-led chronic disease management clinic in hospital urology

Article Title: Development and implementation of a nurse-led chronic disease management clinic in the urology department of a tertiary hospital: a descriptive study

Article References: Liu, C., Xia, Y., Jia, X., Wang, R., Li, T., Ma, Y., & Long, H. (2026). Development and implementation of a nurse-led chronic disease management clinic in the urology department of a tertiary hospital: a descriptive study. BMC Nursing. https://doi.org/10.1186/s12912-026-05566-z

Image Credits: AI Generated

DOI: 10.1186/s12912-026-05566-z

Keywords: nurse-led care, urology, outpatient nursing, chronic disease management, prostate cancer, bladder cancer, patient follow-up, service implementation, descriptive study, Development, implementation, nurse-led

Annual exposures to PM₂.₅, particulate matter smaller than 10 micrometres (PM₁₀), nitrogen dioxide (NO₂) and nitrogen oxides (NOx) were estimated using spatiotemporal models at a 1 km × 1 km resolution. Complete residential histories were used to derive time-weighted cumulative exposures. Time-dependent Cox models estimated hazard ratios while adjusting for demographic, socioeconomic and lifestyle factors. The investigators also constructed polygenic risk scores to assess genetic susceptibility and examined joint effects, interaction indices, population attributable fractions and modeled intervention scenarios.

All four pollutants showed statistically significant dose-response associations with bladder cancer risk. Long-term exposure to PM₂.₅ had the largest reported hazard ratio, 2.020 (95% confidence interval, 1.919–2.127), followed by PM₁₀ at 1.657 (1.580–1.738), NO₂ at 1.508 (1.441–1.578) and NOx at 1.450 (1.391–1.513). The elevated risk associated with air pollution was evident across all polygenic-risk-score strata. Participants with both high genetic risk and high exposure had the greatest joint hazard ratios: 8.75 for PM₂.₅, 6.32 for PM₁₀, 4.79 for NOx and 4.97 for NO₂. Additive interaction analyses indicated strong synergy, particularly for PM₂.₅ among high-risk individuals (P < 0.001).

The abstract reported population attributable fractions of 36.8% for annual average PM₂.₅ concentrations at or above the fourth-quartile level, 28.2% for PM₁₀, 24.8% for NOx and 24.7% for NO₂. In a theoretical intervention scenario, reaching World Health Organization guideline levels was projected to avert up to 80% of PM₂.₅-related cases; this was a model-based projection, not an observed policy effect. Because the available evidence describes an observational analysis based on modeled residential exposures, residual confounding and exposure misclassification remain possible, and the abstract does not present the study’s complete set of limitations.

Subject of Research: Associations between long-term ambient air pollution, genetic susceptibility and bladder cancer risk in the UK Biobank

Article Title: Air pollutants, genetic susceptibility, and bladder cancer risk: a prospective study

Article References: Liu, J., Tang, R., Wang, H., Luo, S., Wang, J., & Wu, P. (2026). Air pollutants, genetic susceptibility, and bladder cancer risk: a prospective study. BMC Cancer. https://doi.org/10.1186/s12885-026-17167-9

Image Credits: AI Generated

DOI: 10.1186/s12885-026-17167-9

Keywords: air pollution, bladder cancer, UK Biobank, prospective cohort, PM₂.₅, PM₁₀, nitrogen dioxide, nitrogen oxides, polygenic risk, gene-environment interaction, pollutants, genetic

The study included 120 patients with bladder cancer and 120 healthy controls matched by age and sex. Investigators genotyped the rs833061 variant using ARMS-PCR and confirmed the genotypes by Sanger sequencing. Serum YKL-40 concentrations were measured with ELISA.

Multivariable binary logistic regression showed that the CT and TT genotypes remained independently associated with increased bladder cancer susceptibility after adjustment for age, sex, and smoking status. Patients had significantly higher serum YKL-40 concentrations than controls, and those concentrations increased progressively with tumor stage. TT genotype carriers had the highest serum YKL-40 levels.

These observations connect a measured genetic variant with two related clinical features in the study population: bladder cancer status and circulating YKL-40. The source available for this report is the article abstract rather than a full assessment of the complete study. The authors characterized the genotype–phenotype relationship as preliminary and stated that the results require validation in larger multicentre cohorts.

Subject of Research: Association of VEGFA rs833061 polymorphism with bladder cancer susceptibility and serum YKL-40 concentrations in a case-control study

Article Title: Integrated analysis of VEGFA rs833061 (− 460T > C) promoter polymorphism and serum YKL-40 levels in bladder cancer: evidence of a genotype–phenotype association

Article References: Kaushik, R., Pawar, D., Sharma, A., Siwach, K., Rohilla, G., Narwal, S., Khatri, N., Arora, A., & Vashist, M. (2026). Integrated analysis of VEGFA rs833061 (− 460T > C) promoter polymorphism and serum YKL-40 levels in bladder cancer: evidence of a genotype–phenotype association. Molecular Biology Reports, 53(1), Article 1585. https://doi.org/10.1007/s11033-026-12776-w

Image Credits: AI Generated

DOI: 10.1007/s11033-026-12776-w

Keywords: bladder cancer, VEGFA, rs833061, YKL-40, genetic polymorphism, case-control study, serum biomarker, genotype-phenotype association, Integrated, analysis, promoter, polymorphism

The study included patients who presented to the institute between 2012 and 2021. Twelve of the 60 patients, or 20%, had metastatic disease at diagnosis, while the remaining 48 had localized disease. Among those with localized disease, nine underwent upfront radical cystectomy and the others received neoadjuvant chemotherapy.

Platinum-etoposide was used more frequently than platinum-gemcitabine in the neoadjuvant, adjuvant and metastatic settings, accounting for 57% of recorded treatment use. Of the 39 patients with localized disease who received neoadjuvant chemotherapy, 18, or 46%, achieved a complete response. These complete responders proceeded to concurrent chemoradiation as part of the bladder-preserving strategy.

Platinum-etoposide was associated with greater odds of complete response than platinum-gemcitabine: the reported odds ratio was 7.27, with a 95% confidence interval of 1.33 to 39.86 and a p-value of 0.02. The wide confidence interval indicates substantial uncertainty around the estimate, which came from a retrospective cohort with relatively few patients and more than one chemotherapy regimen. Across the study population, cumulative five-year event-free survival was 46.9% and cumulative five-year overall survival was 49.5%.

Multivariable analysis identified the platinum-gemcitabine protocol as an independent factor associated with worse event-free survival compared with platinum-etoposide. Initially metastatic disease was an independent factor associated with poorer overall survival compared with localized disease. These were statistical associations within the retrospective cohort, not evidence from a randomized comparison that either regimen or disease status caused the observed differences.

The findings support the feasibility of bladder preservation in selected patients whose localized disease responds completely to neoadjuvant chemotherapy and who subsequently undergo concurrent chemoradiation. The study did not provide a randomized comparison between bladder-preserving treatment and radical cystectomy, so it cannot establish that preserving the bladder produces equivalent survival outcomes. Retrospective selection, the small sample and treatment delivered at a single institution also limit generalization.

The investigators called for further prospective evaluation, and the results should therefore be interpreted as an encouraging observation rather than definitive evidence for changing treatment standards.

Subject of Research: Bladder-preserving treatment after chemotherapy for localized primary urinary bladder small cell carcinoma

Article Title: Bladder preservation is still feasible in the rare aggressive small cell carcinoma subtype

Article References: Ismail, Y., Kamal, A., Aboulkassem, H., Ashour, M. G., AbouGabal, A. A., Allam, R. M., Gad, M., Mostafa, M. E., & Taher, M. (2026). Bladder preservation is still feasible in the rare aggressive small cell carcinoma subtype. Medical Oncology, 43(11), Article 339. https://doi.org/10.1007/s12032-026-03437-w

Image Credits: AI Generated

DOI: 10.1007/s12032-026-03437-w

Keywords: bladder cancer, small cell carcinoma, bladder preservation, neoadjuvant chemotherapy, chemoradiation, platinum-etoposide, complete response, retrospective cohort, event-free survival, overall survival, Bladder, preservation

The investigation examined the expression and function of MG53 in bladder cancer. MG53 is a member of the tripartite motif family of E3 ubiquitin ligases, which regulate metabolic homeostasis and tumor-associated signaling. In bladder cancer cells, the team assessed proliferation, invasion, glycolytic metabolism, intracellular reactive oxygen species, or ROS, and apoptosis.

Co-immunoprecipitation and ubiquitination assays were used to investigate the interaction between MG53 and AMPKα. Overexpression of MG53 reduced cell proliferation, invasion, and glycolytic metabolism in bladder cancer cells. It was also accompanied by increased intracellular ROS accumulation and a higher apoptotic rate.

The cells showed increased levels of cleaved caspase-3 and a higher Bax-to-Bcl-2 ratio, while the decrease in glycolytic metabolism was consistent with attenuation of the Warburg effect. These measurements link MG53 overexpression with reduced proliferative and invasive behavior, altered metabolism, and increased cell death in the experimental systems. The reported results do not establish the order in which all of these changes occurred or whether each one directly caused another.

Biochemical experiments identified AMPKα as a molecular target of MG53. Co-immunoprecipitation indicated that MG53 and AMPKα interacted, while ubiquitination assays showed that MG53 promoted AMPKα ubiquitination. The authors further demonstrated that MG53 drove AMPKα toward proteasomal degradation.

Together, the experiments support a mechanism in which elevated MG53 reduces AMPKα abundance, attenuates glycolytic metabolism, and suppresses bladder cancer-cell proliferation and invasion. The evidence comes from molecular assays and bladder cancer-cell experiments; the supplied study summary does not provide the full range of experimental controls or the complete sequence of downstream events. Findings from xenograft models extended the cell results to an in vivo setting.

In those animal models, MG53 overexpression inhibited tumor growth, supporting a suppressive role for the protein in the experimental bladder cancer system. The work identifies MG53 as a candidate therapeutic target, but the researchers explicitly stated that its translational value remains to be established in future preclinical and clinical studies. Accordingly, the results provide a mechanistic and preclinical basis for further investigation of MG53-mediated AMPKα degradation, rather than evidence that MG53-directed treatment is ready for clinical use.

Subject of Research: Preclinical study of MG53-mediated AMPKα degradation in bladder cancer.

Article Title: MG53 suppresses the progression of bladder cancer through E3 ubiquitin ligase-mediated degradation of AMPKα

Article References: He, X., Zhang, H., Zhang, Y., Wu, J., Wang, T., Liu, Y., Jin, K., Tang, W., Ye, Q., & Wang, Q. (2026). MG53 suppresses the progression of bladder cancer through E3 ubiquitin ligase-mediated degradation of AMPKα. Medical Oncology, 43(11), Article 337. https://doi.org/10.1007/s12032-026-03448-7

Image Credits: AI Generated

DOI: 10.1007/s12032-026-03448-7

Keywords: MG53, TRIM72, bladder cancer, AMPKα, E3 ubiquitin ligase, protein degradation, glycolytic metabolism, reactive oxygen species, apoptosis, xenograft models, suppresses, progression

Arsenic has the strongest epidemiological support. A systematic review and meta-analysis of 68 studies cited by the article reported a pooled relative risk of 1.60, with a 95% confidence interval of 1.13–2.27, when comparing the highest with the lowest arsenic exposure tertiles. The relationship appeared nonlinear: the association was not significant at or below 10 micrograms per liter in drinking water, but increased steadily across concentrations from 10 to 429 micrograms per liter.

Ecological and case-control investigations in high-exposure regions have also linked drinking-water arsenic with bladder cancer and reported elevated arsenic concentrations in recurrent tumors alongside associations with tumor aggressiveness and early recurrence. By contrast, a prospective nested case-control study within the Alpha-Tocopherol, Beta-Carotene Cancer Prevention cohort, using pre-diagnostic toenail arsenic as a marker of long-term exposure, found no significant association with bladder cancer among Finnish male smokers. Its odds ratio was 1.13, with a 95% confidence interval of 0.70–1.81, for the highest versus lowest quartile.

The review therefore regards arsenic as a causal risk factor while noting that low-dose evidence remains inconclusive. Cadmium shows consistent but less causally secure associations. Case-control studies have repeatedly found higher concentrations in bladder tumor tissue than in adjacent non-cancerous tissue, while some studies have linked blood cadmium with muscle-invasive disease, lymph-node involvement, miRNA-21 expression and other markers associated with aggressive phenotypes.

The same meta-analysis reported a pooled relative risk of 1.38, with a 95% confidence interval of 1.04–1.82. A major limitation is that much of the evidence is cross-sectional, so it cannot establish whether cadmium accumulation preceded malignant transformation or partly resulted from it. Tobacco smoke is also a major cadmium source, making the metal a potential confounder and possible mediator of smoking-related risk.

Formal bladder-cancer-specific dose-response analyses remain limited, and the review classifies cadmium as likely causal while emphasizing the need for prospective studies and causal mediation analyses that separate its independent contribution from smoking. Chromium and lead occupy less secure positions in the review’s evidence hierarchy. Chromium concentrations are elevated in tumor tissue, and experimental work indicates that hexavalent chromium can promote proliferation and migration while inhibiting apoptosis through regulation of filamin A.

However, a prospective European Prospective Investigation into Cancer and Nutrition Florence cohort found no significant relationship between pre-diagnostic serum chromium and bladder cancer among never or long-term former smokers without occupational exposure. The tissue-versus-serum discrepancy may reflect the different exposure windows captured by each matrix, but it also prevents a definitive causal conclusion. Lead has produced broadly supportive yet conditional signals.

Elevated blood or urine concentrations and higher tumor levels have been reported, while body mass index and nutritional status appear to modify the association. These findings remain based largely on cross-sectional evidence and do not establish whether metabolic factors affect lead toxicity directly or merely track shared exposures. The authors consequently rate chromium as a probable risk factor and lead as a possible one.

Why can one study detect an association while another finds none? The review identifies exposure measurement as a central problem. Blood and urine concentrations mainly represent recent exposure, with biological half-lives measured in days or weeks, whereas concentrations in bladder tissue can reflect accumulation over years or decades.

Bladder carcinogenesis may involve a latency of 20–40 years or longer for arsenic, making a single serum sample poorly aligned with the relevant exposure window. Toenails and fingernails can integrate exposure over several months, although they can be affected by external contamination and grow slowly. The matrix used to measure a metal can therefore determine whether a long-term process appears as a strong tissue signal, a modest systemic association or a null result.

Repeated measurements and specimens that integrate longer exposure periods are needed to improve temporal alignment. Smoking introduces another layer of analytical difficulty. It is an established bladder-cancer risk factor and a source of cadmium and lead.

Adjusting for smoking as though it were solely a confounder may remove part of a true metal-mediated effect, whereas inadequate adjustment can inflate the apparent metal association. The review therefore calls for causal mediation analysis, formal interaction tests and stratified analyses rather than simple covariate adjustment. Metals also coexist in real environments and may have additive, synergistic or antagonistic effects that cannot be represented reliably by single-metal models.

Statistical approaches such as Bayesian Kernel Machine Regression and Weighted Quantile Sum regression could examine complex, nonlinear exposure profiles, according to the review, but better modeling must be paired with reliable longitudinal exposure assessment and mixture-focused toxicology. At the molecular level, the proposed mechanism begins with reactive oxygen species and mitochondrial dysfunction. Redox-active metals such as chromium can directly catalyze electron transfer, whereas cadmium and lead can indirectly weaken antioxidant systems including superoxide dismutase and glutathione peroxidase.

In cell and animal models, the resulting oxidative stress is associated with impaired mitochondrial membranes, disturbed electron transport, reduced ATP production and a self-reinforcing cycle of mitochondrial damage. Several observational studies of bladder cancer patients have also found elevated markers such as malondialdehyde, advanced oxidation protein products and total oxidant status, together with reduced antioxidant activity. These observations are consistent with a role for redox injury, but much of the causal mechanistic evidence comes from immortalized cancer-cell lines exposed to acute, high metal concentrations that may not reproduce chronic human exposure.

The review notes that direct validation in physiologically relevant primary urothelial cells, patient-derived organoids and prospective cohorts is still needed. The downstream circuitry includes two reactive-oxygen-species-dependent routes and a route that can operate independently of reactive oxygen species. Oxidative stress can activate p38-MAPK, which feeds into NF-κB-mediated inflammation, and the PI3K/AKT pathway, which supports proliferation and survival.

Epigenetic changes may reinforce these signals: metal-associated increases in DNA methyltransferases have been linked to promoter hypermethylation and reduced expression of PTEN and CDKN2A, while miR-21 and miR-155 can rise and members of the miR-200 family can fall. Antimony provides experimental evidence for a distinct SUMO2/3-dependent, TGF-β/Smad2/3 pathway that promotes epithelial–mesenchymal transition without the same reactive-oxygen-species dependence. NRF2 adds stage-specific complexity: it can protect normal urothelial cells from oxidative injury early in carcinogenesis, but sustained activation in established tumors may support anti-apoptosis, angiogenesis, metabolic reprogramming and chemoresistance.

These pathways are interconnected, and experimental results do not yet establish that blocking one node will prevent cancer in exposed people. The proposed molecular disturbances extend beyond cancer cells. The review describes evidence that metals may reshape the tumor microenvironment through chronic inflammation, altered immune surveillance, activation of cancer-associated fibroblasts and changes in cellular metabolism.

Arsenic has been associated with PD-L1 regulation through STAT3 and NF-κB in experimental bladder-cancer systems, while oxidative injury may impair tumor-infiltrating lymphocytes and natural killer cells. Disruption of mitochondrial oxidative phosphorylation can also shift metabolism toward aerobic glycolysis, producing a lactate-rich environment that may favor tumor cells and suppress immune effectors. These findings remain relatively immature and context dependent: oxygen, nutrient, pH and immune-cell gradients may cause one pathway to dominate in one tumor region and another pathway to dominate elsewhere.

Single-cell sequencing, spatial profiling and post-translational-modification proteomics may help map this heterogeneity, but their use in large population studies presents cost, throughput and data-integration challenges. The review proposes a three-level framework linking environmental control, biomarker-guided surveillance and molecular treatment, but much of its clinical component remains conceptual. Primary prevention would reduce arsenic and cadmium exposure through environmental regulation and counseling in exposed communities.

Secondary prevention would identify individuals using combinations of metal measurements, oxidative-damage markers and susceptibility variants before assessing possible preventive interventions. Tertiary prevention would use molecular profiles to guide treatments such as epigenetic modifiers or SUMOylation inhibitors in established disease. Candidates including lycopene, phytosterols, kaempferol and excavatolide C have shown antioxidant or signal-modifying effects in laboratory models, but poor bioavailability and target-tissue delivery remain substantial barriers, and no clinical evidence cited establishes their benefit for bladder-cancer prevention.

Decitabine and UBC9-directed strategies also require further validation. The central research priority is prospective work that links repeated exposure measurements with molecular pathology, followed by rigorous trials in well-characterized exposed populations, while acknowledging that most mechanistic evidence still comes from cell and animal models rather than demonstrated clinical benefits in humans.

Subject of Research: Epidemiological and molecular evidence linking toxic metal exposure to bladder cancer risk and progression.

Article Title: From epidemiology to molecular pathology: current research status and future prospects on the role of toxic metal exposure in the development and progression of bladder cancer

Article References: Li, D., Sun, X., & Yu, T. (2026). From epidemiology to molecular pathology: current research status and future prospects on the role of toxic metal exposure in the development and progression of bladder cancer. Frontiers in Cell and Developmental Biology, 14, Article 1930640. https://doi.org/10.3389/fcell.2026.1930640

Image Credits: AI Generated

DOI: 10.3389/fcell.2026.1930640

Keywords: bladder cancer, toxic metals, arsenic, cadmium, chromium, lead exposure, systematic review, oxidative stress, molecular pathology, epidemiology, tumor microenvironment, cancer prevention

The study, published in Frontiers in Nutrition, was designed to investigate the pharmacological activity of nuciferine and identify possible molecular targets involved in its effects against bladder cancer. The investigators described bladder cancer as a refractory malignant tumor and noted that chemotherapy agents including cisplatin, methotrexate, doxorubicin and vinblastine can be accompanied by adverse effects. The present work did not compare nuciferine with those treatments, assess clinical outcomes or test the compound in patients; it focused instead on isolating the molecule, modeling a possible protein interaction and measuring the response in tumor-bearing mice.

For the chemical work, researchers obtained 0.5 kilograms of N. nucifera leaves from Guigang in China’s Guangxi Zhuang Autonomous Region and deposited a voucher specimen under the number 2026NNG001. The leaves were finely powdered and extracted with 80% ethanol by refluxing. The ethanol distillate was then extracted with ethyl acetate and fractionated by silica-gel column chromatography using a dichloromethane-methanol gradient with ratios of 100:1 and 50:1 by volume, producing three fractions. Fraction 3 weighed 110.0 milligrams and was further purified by preparative high-performance liquid chromatography on a C18 column with a methanol-water mobile phase of 82:18 by volume. This procedure yielded 5.0 milligrams of a white powder identified as nuciferine.

The researchers tracked the compound through the plant material with thin-layer chromatography, high-performance liquid chromatography and liquid chromatography-mass spectrometry. They also used high-resolution electrospray ionization mass spectrometry and nuclear magnetic resonance spectroscopy to establish its structure. The mass-spectrometric analysis yielded the molecular formula C19H21NO2 and a detected protonated molecular ion at a mass-to-charge ratio of 296.1640. Proton and carbon-13 nuclear magnetic resonance measurements then supported the assignment of the isolated material to nuciferine. These characterization steps mean that the tumor experiment involved chemically identified nuciferine rather than an unquantified mixture of compounds extracted from lotus leaves.

To look for a possible molecular target, the team performed an in silico molecular-docking analysis of nuciferine against signal transducer and activator of transcription 3, or STAT3. The compound structure was retrieved from PubChem, while a three-dimensional structure of STAT3 was obtained from the Protein Data Bank under the identifier 6NJS. The researchers prepared the protein and compound through AutoDock, screened their interaction with AutoDock Vina and visualized the predicted complex in PyMOL. The docking analysis produced a free binding energy of −6.2 kcal/mol and placed nuciferine in hydrogen-bonding contact with the glutamine-644 and tyrosine-657 residues in the modeled STAT3 structure.

The docking result was a computational prediction, not a demonstrated molecular interaction. It suggested that the geometry of nuciferine was compatible with a binding site in the STAT3 structure and provided a hypothesis for subsequent experiments. Docking alone cannot establish that nuciferine binds STAT3 inside intact cells, changes the protein’s function or causes any downstream effect on a tumor. The researchers therefore used a tumor-bearing mouse model to examine whether biological changes observed after treatment were consistent with the proposed pathway, alongside direct measurements of tumor growth and molecular labeling.

For the in vivo experiment, the investigators used mature male C57BL/6 mice that were six weeks old at purchase and allowed them one week to adapt to their surroundings. They injected 1 × 10^6 stably cultured mouse MB49 bladder-cancer cells into the right axilla of each animal to establish cell-based xenograft tumors. Once the tumors had grown for seven days, six mice received nuciferine at 40 milligrams per kilogram of body weight and six mice received solvent alone. The treatment was administered by intragastric gavage once daily for 10 days. All mice were then euthanized, and the solid tumors were collected, weighed and fixed in 4% paraformaldehyde. The protocol was approved by the Experimental Animal Ethics Committee of Guangxi Medical University under approval number 202509025.

Nuciferine treatment significantly reduced tumor growth relative to the untreated controls at a reported significance threshold of p < 0.05. Immunofluorescence analysis of tumor sections showed corresponding shifts in cell-death markers: TUNEL-positive cells increased, as did Bax-positive cells, while Bcl-2-positive cells decreased. TUNEL labeling identifies DNA fragmentation commonly associated with apoptosis, and Bax and Bcl-2 participate in the regulation of mitochondrial cell death. Taken together, the measured changes were consistent with greater apoptotic activity in the treated tumors. The experiment did not directly quantify every stage of apoptosis, so the staining pattern supports that interpretation without establishing the complete process by which tumor growth declined.

STAT3 labeling was also lower in tumors from nuciferine-treated mice than in controls, with the difference reported at p < 0.05. STAT3 is a transcription factor implicated in inflammatory reactions, tumorigenesis and several cancer-associated processes, including cell proliferation, angiogenesis, stemness and drug tolerance. The decline in STAT3-labeled cells was therefore consistent with the docking-based proposal that nuciferine might affect an apoptosis-related STAT3 pathway. However, the study did not include a direct binding assay, a genetic loss-of-function experiment or a separate intervention that blocked STAT3. It consequently could not determine whether reduced STAT3 caused the tumor response, was a consequence of it or reflected another process.

Several features limit the scope of the result. Each comparison group contained only six mice, and all were male animals bearing tumors derived from one mouse bladder-cancer cell line. The authors also noted that detailed cell-culture experiments were lacking and that the pharmacological mechanism remained incompletely explored. The design likewise did not establish how nuciferine would be absorbed, metabolized or distributed in humans, what doses might be safe or effective in clinical settings, or whether the observed activity would extend to human bladder tumors. No human participants were enrolled, and the results therefore cannot be interpreted as evidence of a clinical benefit from lotus-leaf nuciferine.

Within those limits, the reported experiment provides a coherent preclinical signal: chemically characterized nuciferine was associated with reduced bladder-cancer tumor growth after 10 days of oral administration in a mouse model, accompanied by increased apoptosis-related labeling, reduced Bcl-2 and STAT3 labeling, and a computationally favorable interaction with STAT3. The study advances nuciferine from a compound with previously reported biological activities to one tested against bladder tumors in vivo. Establishing its mechanism would require further in vitro and in vivo investigation of STAT3, including functional loss-of-function tests, while any assessment of clinical use would depend on evidence beyond this single short mouse experiment.

Subject of Research: Preclinical mouse and molecular-docking evaluation of lotus-derived nuciferine against bladder cancer

Article Title: Anti-bladder cancer effects of nuciferine, a bioactive compound extracted from Nelumbo nucifera leaves

Article References: Qin, B., Liang, H., Kuang, T., Wei, C., Qin, M., Li, J., Lu, H., & Guo, C. (2026). Anti-bladder cancer effects of nuciferine, a bioactive compound extracted from Nelumbo nucifera leaves. Frontiers in Nutrition, 13, Article 1881388. https://doi.org/10.3389/fnut.2026.1881388

Image Credits: AI Generated

DOI: 10.3389/fnut.2026.1881388

Keywords: nuciferine, Nelumbo nucifera, bladder cancer, mouse xenograft, STAT3, apoptosis, molecular docking, preclinical research, Anti-bladder, cancer, effects, bioactive

HER2, short for human epidermal growth factor receptor 2, is a protein that drives growth in some cancers and has become a critical therapeutic target. In bladder cancer, HER2 overexpression or amplification identifies patients who may respond to antibody-drug conjugates such as disitamab vedotin, a drug that has shown promise in HER2-positive urothelial tumors. The problem is that determining HER2 status currently requires immunohistochemistry or fluorescence in situ hybridization on tissue samples obtained through transurethral resection or biopsy. These procedures are invasive, carry procedural risks, sample only part of a heterogeneous tumor, and cannot always be repeated easily to track how the molecular profile changes over time.

The research team, led by investigators from Shaoxing University, Shaoxing People’s Hospital, and Zhuji People’s Hospital in Zhejiang Province, took a different approach. They turned to radiomics, a technique that extracts hundreds of quantitative features from medical images, features that are invisible to the human eye but encode information about tumor texture, shape, intensity distribution, and spatial patterns. When these features are fed into machine learning algorithms, they can reveal subtle relationships between image appearance and underlying biology, including molecular characteristics that pathologists normally detect only under the microscope.

The study enrolled 190 patients with pathologically confirmed bladder cancer who had undergone preoperative computed tomography urography, known as CTU, between October 2019 and September 2024. CTU is a multiphase CT scan of the urinary tract that captures images at different time points after contrast injection, including corticomedullary, nephrographic, and excretory phases, each highlighting different tissue characteristics. All patients had known HER2 status determined by standard pathological testing, providing the ground truth against which the imaging models could be validated.

To build the predictive models, the researchers first delineated regions of interest covering the tumors on each CTU phase and extracted a large panel of radiomic features, including those based on gray-level run length matrices, gray-level co-occurrence matrices, and gray-level size zone matrices. These mathematical descriptors quantify patterns such as coarseness, contrast, homogeneity, and directional texture within the tumor image. Features were filtered using the Least Absolute Shrinkage and Selection Operator, or LASSO, a regression method that shrinks less informative coefficients toward zero and effectively selects the most predictive variables while guarding against overfitting.

The cohort was randomly divided into a training set of 133 patients and an independent test set of 57 patients. Five different machine learning classifiers were then trained on the selected features: logistic regression, support vector machine, k-nearest neighbors, extreme gradient boosting, and random forest. Among these, the random forest model built on corticomedullary-phase images emerged as the clear winner, achieving an area under the receiver operating characteristic curve of 0.798 in the training set and 0.734 in the test set. The corticomedullary phase, which captures the early arterial enhancement of renal cortex and tumor vasculature, appears to contain the richest information about tumor biology relevant to HER2 expression.

The researchers did not stop at imaging features alone. They integrated the radiomic signature with clinical parameters to build a combined clinical-radiomics model, and the results were striking. This hybrid model achieved an AUC of 0.876 in the training cohort and 0.763 in the test cohort, outperforming the radiomics-only approach. Model performance was further evaluated using calibration curves, which assess how well predicted probabilities match observed outcomes, and decision curve analysis, which quantifies the clinical net benefit of using the model at various decision thresholds. Both analyses confirmed that the combined model offered meaningful clinical utility.

Among the 190 patients, 118, or 62.1 percent, were HER2-positive, reflecting the substantial proportion of bladder cancers that harbor this targetable alteration. Patient ages ranged from 26 to 90 years, with median ages of 72 in the HER2-positive group and 68 in the HER2-negative group. The relatively high prevalence of HER2 positivity in this cohort underscores why a non-invasive screening approach could have broad clinical impact, since a large fraction of patients might be eligible for HER2-directed therapies if their status could be reliably determined before treatment planning.

The implications of this work extend beyond bladder cancer. Radiomics-based prediction of molecular markers represents a growing frontier in precision oncology, sometimes described as radiogenomics or imaging genomics. If validated in larger, multicenter cohorts, this approach could allow clinicians to triage patients for HER2-targeted therapy using images already acquired for diagnosis, reducing the need for repeated invasive procedures and enabling faster treatment decisions. It could also be applied longitudinally, tracking molecular evolution of tumors over the course of therapy without additional biopsies.

The authors acknowledge that this was a single-center retrospective study, and external validation across diverse populations and scanner platforms will be essential before clinical adoption. Standardization of image acquisition and feature extraction, guided by initiatives such as the Image Biomarker Standardization Initiative, remains a key challenge for the field. Nevertheless, the demonstration that a routine CTU scan, combined with machine learning, can predict HER2 status with acceptable diagnostic performance marks a significant step toward non-invasive molecular profiling of bladder cancer, bringing the promise of personalized, image-guided oncology closer to everyday practice.

Subject of Research: Radiomics-based CT urography machine learning prediction of HER2 status in bladder cancer

Article Title: Radiomics-based computed tomography urography image analysis for prediction of HER2 status in bladder cancer

Article References: Wu, B., Zhou, T., Hou, C., Mao, J., Lu, Z., Zhu, F., & Zhao, Z. (2026). Radiomics-based computed tomography urography image analysis for prediction of HER2 status in bladder cancer. BMC Medical Imaging. https://doi.org/10.1186/s12880-026-02758-6

Image Credits: AI Generated

DOI: 10.1186/s12880-026-02758-6

Keywords: bladder cancer, HER2, radiomics, CT urography, machine learning, random forest, LASSO, medical imaging, precision oncology, non-invasive diagnostics, BMC Medical Imaging, computed tomography

A team of researchers led by Zhan Jiang Yu and Zhe Hao Wu, working across three hospitals in Jiangxi Province, China, has built a deep learning model that ingests routine contrast-enhanced CT images and predicts whether a patient’s tumor will return within two years of surgery. The work is notable not just for its accuracy, which was substantial, but for its transparency. Using a mathematical technique called SHAP, the model can show clinicians exactly which features of the image and the patient’s clinical profile drove each prediction, addressing one of the most persistent objections to artificial intelligence in medicine: that neural networks are inscrutable black boxes whose advice cannot be trusted or audited.

The study enrolled 192 patients with non-muscle-invasive bladder cancer between June 2017 and May 2023. The largest hospital, the Second Affiliated Hospital of Nanchang University, contributed 139 patients who formed the training set, including 74 who experienced a recurrence. Two other centers, Jiangxi Cancer Hospital and a district hospital in Fuzhou, contributed 53 additional patients whose scans the model had never seen, providing an independent test set that included 24 recurrence events. This multicenter design matters. Models trained and tested on data from a single institution often fail when deployed elsewhere, because scanner settings, patient populations, and imaging protocols differ subtly from hospital to hospital. By validating on external data, the researchers gave their model a far more demanding examination.

Before any prediction could happen, the team had to confront a practical problem: CT images are not always sharp enough for fine-grained analysis. Their solution was to apply super-resolution image reconstruction powered by a generative adversarial network, a class of artificial intelligence in which two neural networks compete against each other, one generating enhanced images and the other trying to detect the fakes, until the generator produces images detailed enough to fool its opponent. Applied to the contrast-enhanced CT scans, this technique recovered fine tissue textures that standard reconstruction can blur away, giving the downstream models richer information to work with. It is a clever piece of engineering that turns an ordinary diagnostic scan into a high-fidelity substrate for machine learning.

From these enhanced images, the researchers extracted two complementary kinds of information. The first was radiomics: hundreds of quantitative measurements describing tumor texture, shape, and intensity patterns, such as features derived from gray-level co-occurrence matrices and neighboring gray-tone difference matrices, which capture how pixel intensities repeat and cluster within the tumor. These handcrafted features encode characteristics that the human eye perceives only vaguely as a tumor looking heterogeneous or mottled. The second source was deep learning features, learned automatically by a convolutional neural network that processed the images directly and distilled them into abstract numerical representations. Finally, the team compiled clinical variables, including tumor number and T stage, the standard measure of how deeply the tumor has invaded the bladder wall.

The centerpiece of the study is what the authors call Fusion Model C, which combines all three information streams. Trained exclusively on the first center’s data, it achieved an area under the receiver operating characteristic curve of 0.917 in the training set, with a 95 percent confidence interval of 0.874 to 0.960, and 0.865 on the unseen external test set, with a confidence interval of 0.756 to 0.974. For context, an AUC of 0.5 reflects random guessing, while 1.0 reflects perfect discrimination, so a value of 0.865 on external data represents strong, clinically meaningful performance. The fused model clearly outperformed a radiomics-only model, which managed an AUC of 0.754 on the test set, demonstrating that the deep learning features and clinical variables carried predictive power that texture statistics alone could not supply.

Accuracy alone, however, was not the study’s only ambition. The researchers interrogated their model with Shapley additive explanations, a technique borrowed from cooperative game theory that assigns each input feature a precise contribution to every individual prediction. The analysis revealed that tumor number, T stage, and a single deep learning feature were the three highest-ranked predictors overall. In other words, the model had independently learned something the clinical literature already suspected, that patients with multiple tumors and higher T stages recur more often, while also discovering predictive image patterns that no traditional risk table captures. Calibration curves, Brier scores, and decision-curve analysis further supported the model’s reliability, with the decision curves in particular suggesting that using the model to guide surveillance decisions would yield more net benefit than treating all patients identically or treating none.

The clinical implications are significant because surveillance for non-muscle-invasive bladder cancer is burdensome and expensive. Current practice relies on risk stratification systems from the European Organization for Research and Treatment of Cancer and the Spanish Urological Oncology Treatment Group, which combine factors such as tumor count, size, stage, grade, and prior recurrence rate to sort patients into risk categories. These categories determine how often patients undergo cystoscopy, an uncomfortable camera examination of the bladder, and whether they receive intravesical therapies such as Bacillus Calmette-Guérin instillations. A model that reads a preoperative CT scan, which many patients already undergo, could refine this stratification before any treatment decision is made, potentially sparing low-risk patients some procedures while flagging high-risk patients for intensified follow-up.

The study’s authors are careful about scope, and rightly so. The work is retrospective, meaning the researchers analyzed scans and outcomes that had already been collected rather than following new patients forward in time. The test set, while external, contained only 53 patients and 24 recurrence events, which widens the confidence intervals and means the reported performance carries real statistical uncertainty. The model was also developed and validated in a specific Chinese patient population, and its behavior in other populations, with different scanners and ethnic profiles, remains to be demonstrated. Prospective validation, in which the model’s predictions are locked in before outcomes are known, would be the natural next step before any deployment in clinical practice.

Even with those caveats, the study offers a compelling glimpse of where cancer surveillance is heading. The combination of generative adversarial super-resolution, radiomics, deep learning, and explainable artificial intelligence transforms a routine preoperative scan into a personalized prognosis engine, one that can justify its conclusions to the physicians who must act on them. The research was supported by the Jiangxi Provincial Health Commission, the Jiangxi Provincial Academic and Technical Leader Training Program, and the National Natural Science Foundation of China, and the authors report no competing interests. If future prospective studies confirm these results, the two-year question that haunts every bladder cancer patient leaving the operating room may one day be answered, with quantified confidence, before the patient even wakes up.

Subject of Research: An explainable deep learning model using contrast-enhanced CT to predict two-year recurrence of non-muscle-invasive bladder cancer

Article Title: An interpretable deep learning model based on enhanced CT predicts the recurrence of non-muscle-invasive bladder cancer within 2 years

Article References: Yu, Z. J., Wu, Z. H., Huang, J. B., Zeng, Z. F., Chao, H. C., & Zeng, T. (2026). An interpretable deep learning model based on enhanced CT predicts the recurrence of non-muscle-invasive bladder cancer within 2 years. BMC Medical Imaging. https://doi.org/10.1186/s12880-026-02738-w

Image Credits: AI Generated

DOI: 10.1186/s12880-026-02738-w

Keywords: bladder cancer, NMIBC, deep learning, radiomics, contrast-enhanced CT, generative adversarial network, super-resolution, SHAP, recurrence prediction, machine learning, medical imaging, predictive medicine

The research, led by Yu Shen and Haibo Shen of the Department of Urology at Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, together with colleagues at Shanghai Jing’an District Central Hospital and the Shanghai Institute of Immunology, set out to resolve a longstanding puzzle. GSDMB is known to be highly expressed in bladder cancer, and previous work had implicated the gasdermin family in anti-tumor immunity, but the precise functional role of GSDMB in shaping the response to immune checkpoint inhibitors had remained unclear. The new study provides what the authors describe as a novel mechanism linking a tumor-intrinsic signaling pathway to the recruitment and activation of cytotoxic immune cells within the tumor microenvironment.

At the heart of the discovery is a signaling axis that the researchers designate as GSDMB–DDX5–Sema7a–CD8+ T cell. According to the study, when GSDMB is overexpressed in bladder cancer cells, it does something unexpected for a protein of its class: it translocates to the nucleus. Once inside the nucleus, GSDMB physically interacts with DEAD-box helicase 5, or DDX5, a well-characterized RNA helicase that participates in the regulation of transcription. Through this interaction, the GSDMB–DDX5 complex upregulates the expression of Semaphorin 7A, or Sema7a, a secreted signaling molecule that the study identifies as the critical downstream effector of the pathway.

Sema7a, once produced by the tumor cells, is secreted into the surrounding tumor microenvironment, where it performs a crucial recruiting function. The researchers demonstrate that secreted Sema7a facilitates the infiltration of CD8+ T cells into the tumor. These cytotoxic T lymphocytes are the principal assassins of the adaptive immune system, capable of recognizing and killing tumor cells directly, and their presence within a tumor, rather than merely around its margins, is one of the strongest predictors of response to immunotherapy. Tumors that are densely infiltrated by CD8+ T cells are often described as immunologically hot, whereas tumors that exclude these cells tend to resist checkpoint inhibitors regardless of how many T cells circulate in the bloodstream.

The study goes further than simply counting infiltrating cells. The researchers found that the CD8+ T cells recruited into GSDMB-expressing tumors were not only more numerous but also more functionally potent. Tumor-infiltrating CD8+ T cells in this setting showed enhanced expression of three hallmark mediators of cytotoxic anti-tumor activity: interferon-gamma, tumor necrosis factor-alpha, and granzyme B. Interferon-gamma and tumor necrosis factor-alpha are inflammatory cytokines that coordinate and amplify immune attacks on tumors, while granzyme B is a serine protease that T cells deliver into target cells to trigger their death. The coordinated elevation of all three molecules indicates that the recruited T cells arrive in an activated, tumor-killing state rather than in an exhausted or suppressed condition.

This mechanism has direct consequences for anti-PD-1 therapy. Immune checkpoint inhibitors such as anti-PD-1 antibodies work by releasing the molecular brakes that tumors place on T cells, but they can only succeed if tumor-reactive T cells are present in the tumor microenvironment in the first place. By promoting the infiltration and activation of CD8+ T cells, GSDMB effectively increases the supply of targetable immune cells, allowing anti-PD-1 treatment to operate on a larger and more vigorous T cell population. The authors report that GSDMB synergizes with the efficacy of immune checkpoint inhibitor therapy in bladder cancer through this promotion of CD8+ T cell infiltration and effector function, establishing the protein as a genuine partner to checkpoint blockade rather than an incidental correlate.

The mechanistic findings are notable because they assign a transcriptional regulatory role to GSDMB, a member of the gasdermin family whose members are classically associated with pyroptosis, a form of inflammatory programmed cell death. The demonstration that GSDMB can move into the nucleus and, through its interaction with the helicase DDX5, drive the transcription of Sema7a expands the known functional repertoire of this protein family. It also reframes gasdermin biology in the context of cancer immunology: rather than acting solely as an executor of cell death, GSDMB in bladder cancer appears to function as a tumor-intrinsic organizer of the immune microenvironment, shaping which immune cells enter the tumor and how aggressively they behave once inside.

Beyond its mechanistic interest, the study carries practical implications for patient care. The authors conclude that GSDMB may serve as a potential prognostic biomarker for outcomes in patients with bladder cancer treated with anti-PD-1 therapy. If validated in larger clinical cohorts, a GSDMB-based test could help oncologists identify, before treatment begins, which patients are likely to respond to checkpoint inhibitors and which might be better served by alternative or combination strategies. This kind of predictive stratification is a pressing unmet need in bladder cancer, where anti-PD-1 agents are used in both metastatic settings and in certain non-muscle-invasive disease contexts, yet response rates vary widely between individuals.

The research also suggests potential therapeutic avenues that extend beyond biomarker development. If the GSDMB–DDX5–Sema7a pathway can be pharmacologically enhanced in tumors with low endogenous GSDMB activity, or if Sema7a itself can be delivered or mimicked to draw CD8+ T cells into immunologically cold tumors, clinicians might one day convert non-responsive bladder cancers into responsive ones. Conversely, the pathway offers a mechanistic explanation for resistance that could be targeted diagnostically: patients whose tumors lack GSDMB expression, and therefore lack the Sema7a-driven recruitment signal, might be candidates for therapies that recruit immune cells through alternative routes, such as oncolytic viruses, cancer vaccines, or chemokine-modulating agents.

The study was conducted with oversight from the Institutional Animal Care and Use Committee of Xinhua Hospital and the hospital’s Ethics Committee, with informed consent obtained from all human participants, and it was supported by grants from the Shanghai Jing’an District Health Commission and the Cross-disciplinary Fund of Xinhua Hospital. Published as an open-access article, the work adds bladder cancer to the growing list of malignancies in which tumor-intrinsic molecular programs are being mapped onto the architecture of the immune microenvironment. As the field of immuno-oncology moves from broad checkpoint blockade toward rational, mechanism-guided combination therapy, findings such as the GSDMB–DDX5–Sema7a axis illustrate how a single tumor protein can orchestrate an entire chain of immune events, from gene transcription in the cancer cell nucleus to the arrival of armed cytotoxic T cells at the tumor front, and how understanding that chain may ultimately determine whether a patient’s immune system can be mobilized to fight back.

Subject of Research: The role of GSDMB in enhancing anti-PD-1 immunotherapy response through Sema7a-mediated CD8+ T cell infiltration in bladder cancer

Article Title: GSDMB synergizes anti-PD-1 efficacy via Sema7a-mediated CD8+ T Cell infiltration in bladder cancer

Article References: Shen, Y., Zhang, S., Yu, S., Chen, K., Li, J., Chen, Z., Ren, T., Liu, H., Xu, D., Wang, Y., & Shen, H. (2026). GSDMB synergizes anti-PD-1 efficacy via Sema7a-mediated CD8+ T Cell infiltration in bladder cancer. Cancer Immunology, Immunotherapy. https://doi.org/10.1007/s00262-026-04597-4

Image Credits: AI Generated

DOI: 10.1007/s00262-026-04597-4

Keywords: bladder cancer, GSDMB, Sema7a, DDX5, CD8+ T cells, anti-PD-1, immune checkpoint inhibitors, immunotherapy, tumor microenvironment, biomarker, granzyme B, interferon-gamma