Huachansu (HCS), a class of toxic steroids extracted from toad venom, which has been shown to be a valuable anticancer drug in many kinds of cancers. However, the effect of HCS on bladder cancer has not been elucidated. In this study, we focused on the antitumor activities and related mechanisms of HCS on bladder cancer in vitro and in vivo. Cell viability of T24, EJ, RT-4, SV-HUC-1 cells after HCS treatment was measured by MTS, whereas the changes of cell morphology were observed by transmission electron microscopy. The early apoptosis induced by HCS was evaluated by flow cytometry, and the expression level of apoptosis-related molecules (Bax, Bcl-2, XIAP, PARP, cleaved-Caspases 3, 8, 9) was detected using Western blot. We then evaluated the impact of HCS on the expression of Fas/Fasl, TNF- alpha/TNFR1, and the activation of NF-Kappa B pathway, and furthermore the effect of these pathways in HCS induced-apoptosis were also detected. At last, xenograft tumor in nude mice was used to further investigate the antitumor effect of HCS in vivo. Our results showed that HCS could efficiently inhibit proliferation and induce apoptosis in human bladder cancer cell lines. The expression of Fas, Fasl, TNF- alpha were all elevated at both mRNA and protein level after HCS treatment. Furthermore, down regulation of TNF- alpha, TNFR1, Fas or inhibition of Fas/Fasl interaction decreased the relative number of death cells induced by HCS. In vivo, HCS treatment significantly suppressed tumor growth and induced apoptosis in xenografts tumor in nude mice. HCS could efficiently inhibit proliferation and induce apoptosis in human bladder cancer cells in vitro and in vivo, which is largely mediated by Fas/Fasl and TNF- alpha/TNFR1 pathway.

Background: Accumulating evidence suggests a tumor suppressive role for miR-34a in human carcinogenesis. However, its precise biological role remains largely elusive. This study aimed to reveal the association of the miR-34a expression and its modulation of sensitivity to cisplatin in muscle-invasive bladder cancer (MIBC). Methods: miR-34a expression in MIBC cell lines and patient tissues was investigated using qPCR. The methylation analysis of miR-34a promoter region was performed by MassARRAY. Synthetic short single or double stranded RNA oligonucleotides and lentiviral vector were used to regulate miR-34a expression in MIBC cells to investigate its function in vitro and in vivo. Results: miR-34a expression was frequently decreased in MIBC tissues and cell lines through promoter hypermethylation while it was epigenetically increased in MIBC cells following cisplatin treatment. Increased miR-34a expression significantly sensitized MIBC cells to cisplatin and inhibited the tumorigenicity and proliferation of cancer cells in vitro and in vivo. Furthermore, we identified CD44 as being targeted by miR-34a in MIBC cells following cisplatin treatment, and increased CD44 expression could efficiently reverse the effect of miR-34a on MIBC cell proliferation, colongenic potential and chemosensitivity. Conclusions: Cisplatin-based chemotherapy induced demethylation of miR-34a promoter and increased miR-34a expression, which in turn sensitized MIBC cells to cisplatin and decreased the tumorigenicity and proliferation of cancer cells that by reducing the production of CD44.

Background Recently, leucine-rich repeats and immunoglobulin-like domains 1 (LRIG1), a negative regulator of EGFR, was discovered is a novel agent for suppressing bladder cancer. The aim of this study was to investigate the impact of LRIG1 on the biological features of aggressive bladder cancer cells and the possible mechanisms of enhanced apoptosis induced by upregulation of LRIG1. Methods In this study, we examined the mRNA and protein expression of LRIG1 and EGFR in bladder cancers and normal bladder. Meanwhile, we overexpressed LRIG1 with adenovirus vector in T24/5637 bladder cancer cell lines, and we used real time-PCR, western blot, and co-immunoprecipitation analysis in order to examine the effects of LRIG1 gene on EGFR. Furthermore, we evaluate the impact of LRIG1 gene on the function of human bladder cancer cells and EGFR signaling. Results The expression of LRIG1 was decreased, while the expression of EGFR was increased in the majority of bladder cancer, and the ratio of EGFR/LRIG1 was increased in tumors versus normal tissue. We found that upregulation of LRIG1 induced cell apoptosis and cell growth inhibition, and further reversed invasion in bladder cancer cell lines in vitro by inhibiting phosphorylation of downstream MAPK and AKT signaling pathway. Conclusion Taken together, our findings provide us with an insight into LRIG1 function, and we conclude that LRIG1 evolved in bladder cancer as a rare feedback negative attenuator of EGFR, thus could offer a novel therapeutic target to treat patients with bladder cancer.

Distant metastasis is the leading cause of death in renal cell carcinoma (RCC), yet accurate prediction tools remain lacking. We aimed to develop and validate a machine learning model to predict synchronous distant metastasis-defined as metastasis present at the time of initial diagnosis-in RCC. We identified 106,448 RCC patients from the SEER database (2010-2020), divided into training (n = 52,368), internal validation (n = 22,444), and external validation (n = 31,636) cohorts. Nine machine learning algorithms were compared using area under the curve (AUC), calibration, and decision curve analysis. Model interpretability was assessed using SHAP analysis. Distant metastasis was present in 10.7% of patients. N1 stage (OR 8.28-9.46), tumor size > 7 cm (OR 6.30-7.72), T4 stage (OR 6.29-8.51), and sarcomatoid histology (OR 1.89-3.28) were independent risk factors, while chromophobe histology (OR 0.04-0.11) and multifocal tumors (OR 0.40-0.53) were protective. Gradient Boosting achieved AUCs of 0.906, 0.906, and 0.926 in training, internal, and external validation cohorts, respectively. The model demonstrated good calibration and clinical utility across threshold probabilities of 5%-80%. Performance remained stable across subgroups and sensitivity analyses. A web calculator was developed (https://952307952pxw.shinyapps.io/RCC-Calculator/). We developed a machine learning model that accurately predicts synchronous distant metastasis at the time of initial RCC diagnosis, with good generalizability. The online calculator may assist clinicians in risk stratification and individualized decision-making.

Background Metastatic renal cell carcinoma (mRCC) is associated with poor prognosis, with a 5-year survival rate of less than 15%. Cytoreductive nephrectomy (CN) has historically played a critical role in mRCC management, potentially enhancing systemic therapy efficacy by reducing tumor burden. However, its relevance in the era of targeted therapies and immune checkpoint inhibitors (ICIs) has been questioned. Objective This study evaluates the survival benefits of CN in mRCC patients using real-world, population-based data from the SEER database. Methods A retrospective cohort analysis of 6,030 mRCC patients was performed using data from 2010 to 2017. Propensity score matching (PSM) minimized selection bias, yielding 1,350 matched patients. Kaplan-Meier survival curves and multivariate Cox proportional hazards models assessed the impact of CN on overall survival (OS) and RCC-specific survival (CSS), stratified by demographic and clinical characteristics. Results CN was associated with a 71% reduction in all-cause mortality (HR = 0.29, 95% CI = 0.25–0.33) and RCC-specific mortality (HR = 0.29, 95% CI = 0.25–0.34). Five-year OS rates were 31.5% in the CN group versus 3.6% in the non-CN group. Survival benefits were consistent across subgroups, including patients with high-grade or advanced-stage tumors, underscoring the role of CN within multimodal treatment strategies. Conclusion CN confers significant survival advantages in mRCC, even in challenging clinical scenarios. These findings reinforce the importance of integrating CN into multimodal therapeutic frameworks, particularly alongside modern systemic therapies. Further prospective studies are warranted to optimize patient selection and treatment sequencing.