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IntroductionBladder cancer is a common malignant tumor with significant heterogeneity, making personalized risk stratification crucial for optimizing treatment and prognosis. This study aimed to develop a prognostic model based on oxidative stress-related genes to guide risk assessment in bladder cancer.MethodsDifferentially expressed oxidative stress-related genes were identified using the GEO database. Functional enrichment and survival analyses were performed on these genes. A risk-scoring model was built and tested for prognostic value and therapeutic response prediction. Expression of key genes was validated by qRT-PCR in samples from two muscle-invasive and two non-muscle-invasive bladder cancer patients.ResultsSeveral oxidative stress-related genes were identified as significantly associated with survival. The risk-scoring model stratified patients into high- and low-risk groups, accurately predicting prognosis and therapeutic responses. qRT-PCR confirmed the differential expression of key genes in patient samples.DiscussionThe study provides a concise risk stratification model based on oxidative stress-related genes, offering a practical tool for improving personalized treatment in bladder cancer. Further validation is required for broader clinical application.

Bladder cancer usually has been diagnosed in elderly patients as it stays asymptomatic until it presents. Current detection methods for bladder cancer cannot be considered as an adequate screening strategy due to their high invasiveness and low sensitivity. However, there remains uncertainty about targets with high sensitivity and specificity for non-invasive bladder cancer examination. Our study aims to investigate the actionable non-invasive screening biomarkers in bladder cancer. Here, we employed scRNA-seq to explore the crucial biological processes for bladder cancer development. We then utilized bidirectional Mendelian randomization (MR) analysis to explore the bidirectional causal relationship between ATP-associated metabolites in urine and bladder cancer. Lastly, we used a BBN-induced mouse model of bladder cancer to validate the crucial gene identified by scRNA-seq and MR analysis. We found that (1) the ATP metabolism process plays a critical role in bladder cancer development; (2) there is a bidirectional and negative causal relationship between fructose-to-sucrose ratio in urine and the risk of bladder cancer; and (3) the higher expression of TPI1, a critical gene in the fructose metabolism pathway, was validated in BBN-induced bladder tumors. Our results reveal that fructose-to-sucrose ratio can serve as a potential target of urinalysis in bladder cancer.

The grate bars are a critical and easily consumable component of the sintering machine, and the control of their corrosion is of great importance to reduce their consumption. This investigation focused on revealing the physicochemical profile of the failure sintering grate bar and the potential corrosion mechanism. The results showed that the superficial area of the failure grate bar consisted of the adhesive layer, corrosion layer, and metal layer from outside to inside. The adhesion layer is characterised by a loose structure, consisting of higher contents of alkali chloride salts and sulphate, which were the typical corrosive substances. The main components of the corrosion layer were Fe2O3 and Cr2O3; the metal layer structure was dense, which remained the original composition of the grate bar. Based on the characteristics of sintering flue gas, the potential corrosion mechanism was summarised into three main types: (a) high-temperature oxidation, due to the periodic exposure of the grate bars to the high-temperature sintering flue; (b) chlorine corrosion, due to the existence of HCl, alkali (heavy) metal chloride salts (KCl, NaCl, PbCl2) in sintering flue gas, which formed the adhesive layer of grate bars; (c) sulphate corrosion, due to the existence of high SO2 contents and sulphate in the flue gas. The research findings are important to guide the development of grate bar corrosion control technologies.

The alteration of glycometabolism is a characteristic of cancer cells. Long non-coding RNAs (lncRNAs) have been documented to occupy a considerable position in glycometabolism regulation. This research aims to construct an effective prediction model for the prognosis of bladder cancer (BC) based on glycometabolism-associated lncRNAs (glyco-lncRNAs). Pearson correlation analysis was applied to get glyco-lncRNAs, and then, univariate cox regression analysis was employed to further filtrate survival time-associated glyco-lncRNAs. Multivariate cox regression analysis was utilized to construct the prediction model to divide bladder cancer (BC) patients into high- and low-risk groups. The overall survival (OS) rates of these two groups were analyzed using the Kaplan–Meier method. Next, gene set enrichment analysis and Cibersortx were used to explore the enrichment and the difference in immune cell infiltration, respectively. pRRophetic algorithm was applied to explore the relation between chemotherapy sensitivity and the prediction model. Furthermore, reverse transcriptase quantitative polymerase chain reaction was adopted to detect the lncRNAs constituting the prediction signature in tissues and urine exosomal samples of BC patients. A powerful model including 6 glyco-lncRNAs was proposed, capable of suggesting a risk score for each BC patient to predict prognosis. Patients with high-risk scores demonstrated a shorter survival time both in the training cohort and testing cohort, and the risk score could predict the prognosis without depending on the traditional clinical traits. The area under the receiver operating characteristic curve of the risk score was higher than that of other clinical traits (0.755 > 0.640, 0.485, 0.644, or 0.568). The high- and low-risk groups demonstrated very distinct immune cells infiltration conditions and gene set enriched terms. Besides, the high-risk group was more sensitive to cisplatin, docetaxel, and sunitinib. The expression of lncRNA AL354919.2 featured with an increase in low-grade patients and a decrease in T3-4 and Stage III–IV patients. Based on the experiment results, lncRNA AL355353.1, AC011468.1, and AL354919.2 were significantly upregulated in tumor tissues. This research furnishes a novel reference for predicting the prognosis of BC patients, assisting clinicians with help in the choice of treatment.

Background: Bladder urothelial carcinoma (BLCA) is one of the most common malignant tumors with high morbidity and recurrence rate. The study aims to establish a prediction model to elaborate the relation between inflammatory response and prognosis of BLCA and thus to evaluate the potential prognostic value of inflammatory response–related genes (IRGs) in therapeutic choices.Methods: The study utilized the gene expression profiles from the The Cancer Genome Atlas and Gene Expression Omnibus (GSE32894) datasets. Differentially expressed IRGs between normal and tumor tissues were identified, and 10 of them were correlated with overall survival (OS) (p < 0.05). Then, the LASSO–Cox regression analysis was applied to optimize the signature. RNA sequencing data of patients with BLCA from GSE32894 were applied as a validation set. Cox regression analyses of the seven-gene signature were performed to examine the efficiency of signature in predicting prognosis. Receiver operating characteristic curve analysis was applied to measure the predictive performance of the risk score for OS. Analysis of independent prognostic factors, downstream functional enrichment, drug sensitivity, and immune features were included in this study.Results: The IRG signature (LDLR, ROS1, MMP14, TNFAIP6, MYC, PTGER4, and RIPK2) was used to divide patients into high- and low-risk groups. Cox regression analyses revealed that the risk score was an independent predictive factor. Functional enrichment analysis revealed that genes were enriched in prognosis-related molecular functions and immune-related biological processes. Drug sensitivity and tumor microenvironment correlation analysis indicated that the signature was related to immunotherapy effect.Conclusion: The study defined a new prognostic signature consisting of seven IRGs, which could effectively predict the prognosis of patients with BLCA and reveal relationship of immune features in BLCA with different risk scores. The study also provided a possible indicator for targeted therapy.

Bladder cancer is a highly metastatic tumor and one of the most common malignancies originating in the urinary tract. Despite the efficacy of immune checkpoints, including programmed cell death-1 (PD-1) and cytotoxic T-lymphocyte-associated protein 4 (CTLA-4), the effect of immunotherapy for bladder cancer remains unsatisfactory. Therefore, it is urgent to develop new targets to expand immunotherapeutic options. In this study, we utilized single-cell sequencing to explore the cell composition of tumors and detected a subset of Treg cells with high expression of T-cell immunoreceptor with immunoglobulin and immunoreceptor tyrosine-based inhibitory motif domain (TIGIT) and interleukin (IL)-32. The antitumor immune response was suppressed by this subset of Treg cells, while IL-32 promoted bladder cancer metastasis. Nevertheless, targeting TIGIT not only reversed immunosuppression by restoring the antitumor immune response mediated by T cells but also suppressed the secretion of IL-32 and inhibited the metastasis of bladder cancer cells. Thus, our study provided novel insights into immunosuppression in bladder cancer and highlighted TIGIT as a novel target for immunotherapy of bladder cancer. We also illustrated the mechanism of the dual effect of targeting TIGIT and revealed the metastasis-promoting effect of IL-32 in bladder cancer. Collectively, these findings raise the possibility of utilizing TIGIT as a target against bladder cancer from the bench to the bedside.

Introduction: Bladder cancer is a common malignant tumor with significant heterogeneity, making personalized risk stratification crucial for optimizing treatment and prognosis. This study aimed to develop a prognostic model based on oxidative stress-related genes to guide risk assessment in bladder cancer. Methods: Differentially expressed oxidative stress-related genes were identified using the GEO database. Functional enrichment and survival analyses were performed on these genes. A risk-scoring model was built and tested for prognostic value and therapeutic response prediction. Expression of key genes was validated by qRT-PCR in samples from two muscle-invasive and two non-muscle-invasive bladder cancer patients. Results: Several oxidative stress-related genes were identified as significantly associated with survival. The risk-scoring model stratified patients into high- and low-risk groups, accurately predicting prognosis and therapeutic responses. qRT-PCR confirmed the differential expression of key genes in patient samples. Discussion: The study provides a concise risk stratification model based on oxidative stress-related genes, offering a practical tool for improving personalized treatment in bladder cancer. Further validation is required for broader clinical application. [ABSTRACT FROM AUTHOR]

Autonomous nanorobots represent an advanced tool for precision therapy to improve therapeutic efficacy. However, current nanorobotic designs primarily rely on inorganic materials with compromised biocompatibility and limited biological functions. Here, we introduce enzyme-powered bacterial outer membrane vesicle (OMV) nanorobots. The immobilized urease on the OMV membrane catalyzes the decomposition of bioavailable urea, generating effective propulsion for nanorobots. This OMV nanorobot preserves the unique features of OMVs, including intrinsic biocompatibility, immunogenicity, versatile surface bioengineering for desired biofunctionalities, capability of cargo loading and protection. We present OMV-based nanorobots designed for effective tumor therapy by leveraging the membrane properties of OMVs. These involve surface bioengineering of robotic body with cell-penetrating peptide for tumor targeting and penetration, which is further enhanced by active propulsion of nanorobots. Additionally, OMV nanorobots can effectively safeguard the loaded gene silencing tool, small interfering RNA (siRNA), from enzymatic degradation. Through systematic in vitro and in vivo studies using a rodent model, we demonstrate that these OMV nanorobots substantially enhanced siRNA delivery and immune stimulation, resulting in the utmost effectiveness in tumor suppression when juxtaposed with static groups, particularly evident in the orthotopic bladder tumor model. This OMV nanorobot opens an inspiring avenue to design advanced medical robots with expanded versatility and adaptability, broadening their operation scope in practical biomedical domains. [ABSTRACT FROM AUTHOR]