Type III interferon inhibits bladder cancer progression by reprogramming macrophage-mediated phagocytosis and orchestrating effective immune responses.

BACKGROUND: Interferons (IFNs) are essential for activating an effective immune response and play a central role in immunotherapy-mediated immune cell reactivation for tumor regression. Type III IFN (λ), related to type I IFN (α), plays a crucial role in infections, autoimmunity, and cancer. However, the direct effects of IFN-λ on the tumor immune microenvironment have not been thoroughly investigated. METHODS: We used mouse MB49 bladder tumor models, constructed a retroviral vector expressing mouse IFN-λ3, and transduced tumor cells to evaluate the antitumor action of IFN-λ3 in immune-proficient tumors and T cell-deficient tumors. Furthermore, human bladder cancer samples (cohort 1, n=15) were used for immunohistochemistry and multiplex immunoflurescence analysis to assess the expression pattern of IFN-λ3 in human bladder cancer and correlate it with immune cells' infiltration. Immunohistochemistry analysis was performed in neoadjuvant immunotherapy cohort (cohort 2, n=20) to assess the correlation between IFN-λ3 expression and the pathological complete response rate. RESULTS: In immune-proficient tumors, ectopic Ifnl3 expression in tumor cells significantly increased the infiltration of cytotoxic CD8+ T cells, Th1 cells, natural killer cells, proinflammatory macrophages, and dendritic cells, but reduced neutrophil infiltration. Transcriptomic analyses revealed significant upregulation of many genes associated with effective immune response, including lymphocyte recruitment, activation, and phagocytosis, consistent with increased antitumor immune infiltrates and tumor inhibition. Furthermore, IFN-λ3 activity sensitized immune-proficient tumors to anti-PD-1/PD-L1 blockade. In T cell-deficient tumors, increased Ly6G-Ly6C+I-A/I-E+ macrophages still enhanced tumor cell phagocytosis in Ifnl3 overexpressing tumors. IFN-λ3 is expressed by tumor and stromal cells in human bladder cancer, and high IFN-λ3 expression was positively associated with effector immune infiltrates and the efficacy of immune checkpoint blockade therapy. CONCLUSIONS: Our study indicated that IFN-λ3 enables macrophage-mediated phagocytosis and antitumor immune responses and suggests a rationale for using Type III IFN as a predictive biomarker and potential immunotherapeutic candidate for bladder cancer.

Chitinase 3-like 1 expression associated with lymphatic metastasis and prognosis in urothelial carcinoma of the bladder.

Objectives: Lymphatic metastasis, an early stage of the metastasis process, is associated with adverse clinical outcomes in urothelial carcinoma of the bladder (UCB). However, the role of inflammation in triggering lymphatic metastasis remains unclear. Methods: We employed an RNA-sequencing cohort (n = 50) from Sun Yat-Sen Memorial Hospital (SYMH) to identify the most highly upregulated inflammatory gene associated with lymphatic metastasis. Using immunohistochemistry and immunofluorescence analyses, we validated the association of the identified molecule with clinical features and prognosis in an independent UCB cohort (n = 244) from SYMH. We also analysed TCGA-BLCA cohort (n = 408) to identify its potential biological pathways and immune landscape. Results: In our study, chitinase 3-like 1 (CHI3L1) emerged as a significantly overexpressed proinflammatory mediator in UCB tissues with lymphatic metastasis compared to those without lymphatic metastasis (81.1% vs. 47.8%, P < 0.001). Within UCB tissues, CHI3L1 was expressed in both stromal cells (52.8%) and tumor cells (7.3%). Moreover, CHI3L1+ stromal cells, but not tumor cells, exhibited independent prognostic significance for both overall survival (P < 0.001) and recurrence-free survival (P = 0.006). CHI3L1+ stromal cells were positively associated with D2-40+ lymphatic vessel density (P < 0.001) and the immunosuppressive PD-L1/PD-1/CD8 axis in UCB tissues (all P < 0.05). A bioinformatics analysis also identified a positive association between CHI3L1 expression and lymphangiogenesis or immunosuppression pathways. Conclusion: Our study established a clear association between stromal CHI3L1 expression and lymphatic metastasis, suggesting that stromal CHI3L1 expression is a potential prognostic marker for bladder cancer patients.

Effective Antitumor Immunity Can Be Triggered by Targeting VISTA in Combination with a TLR3-Specific Adjuvant.

Resistance to anti-PD-1/PD-L1 treatment is often associated with accumulation of intratumoral inhibitory macrophages. V-domain immunoglobulin suppressor of T-cell activation (VISTA) is a nonredundant immune checkpoint that can induce both T-cell and myeloid-cell immunosuppression. In this study, we found that high levels of VISTA+ immune cells were associated with advanced stage bladder cancer and predicted poor survival in patients. A combination of high infiltration of VISTA+ immune cells and PD-L1+ immune cells or PD-1+ T cells predicted the worst survival. Flow cytometry and multiplex immunofluorescence analyses confirmed that VISTA expression was higher in macrophages than in T cells or neutrophils, and only VISTA+CD163+ macrophage density predicted poor prognosis in patients with bladder cancer. Toll-like receptor (TLR) agonists are known to trigger the innate immune response in macrophages. We found that the VISTA-specific mAb 13F3 augmented the ability of a TLR3-specific adjuvant to induce macrophage activation in vitro. In the MB49 syngeneic mouse model of bladder cancer, treatment with 13F3 curbed tumor growth and prolonged survival when combined with a TLR3-specific adjuvant. The combination treatment reduced the intratumoral frequency of CD206+ anti-inflammatory macrophages and levels of the immunosuppressive molecule TGFß1, but it upregulated expression of immunostimulatory molecules (Ifna, Ifnb, and Trail) and increased the CD8+ T cell/regulatory T-cell ratio. These findings indicate that elevated VISTA expression in immune cells, particularly macrophages, is associated with an unfavorable prognosis in patients with bladder cancer and suggest that targeting VISTA in combination with a TLR3-specific adjuvant has translational potential.

Screening ANLN and ASPM as bladder urothelial carcinoma-related biomarkers based on weighted gene co-expression network analysis.

Introduction: Bladder cancer (BLCA) is one of the most common malignancies in the urinary system with a poor prognosis and high treatment costs. Identifying potential prognostic biomarkers is significant for exploring new therapeutic and predictive targets of BLCA. Methods: In this study, we screened differentially expressed genes using the GSE37815 dataset. We then performed a weighted gene co-expression network analysis (WGCNA) to identify the genes correlated with the histologic grade and T stage of BLCA using the GSE32548 dataset. Subsequently, Kaplan Meier survival analysis and Cox regression were used to further identify prognosis-related hub genes using the datasets GSE13507 and TCGA-BLCA. Moreover, we detected the expression of the hub genes in 35 paired samples, including BLCA and paracancerous tissue, from the Shantou Central Hospital by qRT-polymerase chain reaction. Results: This study showed that Anillin (ANLN) and Abnormal spindle-like microcephaly-associated gene (ASPM) were prognostic biomarkers for BLCA. High expression of ANLN and ASPM was associated with poor overall survival.The qRT-PCR results revealed that ANLN and ASPM genes were upregulated in BLCA, and there was a correlation between the expression of ANLN and ASPM in cancer tissues and paracancerous tissue. Additionally, the increasing multiples in the ANLN gene was obvious in high-grade BLCA. Discussion: In summary, this preliminary exploration indicated a correlation between ANLN and ASPM expression. These two genes, serving as the risk factors for BLCA progression, might be promising targets to improve the occurrence and progression of BLCA.

Predictive model for urosepsis in patients with Upper Urinary Tract Calculi based on ultrasonography and urinalysis using artificial intelligence learning

ABSTRACT Purpose To construct a predicting model for urosepsis risk for patients with upper urinary tract calculi based on ultrasound and urinalysis. Materials and Methods A retrospective study was conducted in patients with upper urinary tract calculi admitted between January 2016 and January 2020. The patients were randomly grouped into the training and validation sets. The training set was used to identify the urosepsis risk factors and construct a risk prediction model based on ultrasound and urinalysis. The validation set was used to test the performance of the artificial neural network (ANN). Results Ultimately, 1716 patients (10.8% cases and 89.2% control) were included. Eight variables were selected for the model: sex, age, body temperature, diabetes history, urine leukocytes, urine nitrite, urine glucose, and degree of hydronephrosis. The area under the receiver operating curve in the validation and training sets was 0.945 (95% CI: 0.903-0.988) and 0.992 (95% CI: 0.988-0.997), respectively. Sensitivity, specificity, and Yuden index of the validation set (training set) were 80.4% (85.9%), 98.2% (99.0%), and 0.786 (0.849), respectively. Conclusions A preliminary screening model for urosepsis based on ultrasound and urinalysis was constructed using ANN. The model could provide risk assessments for urosepsis in patients with upper urinary tract calculi.

Predictive model for urosepsis in patients with Upper Urinary Tract Calculi based on ultrasonography and urinalysis using artificial intelligence learning.

PURPOSE: To construct a predicting model for urosepsis risk for patients with upper urinary tract calculi based on ultrasound and urinalysis. MATERIALS AND METHODS: A retrospective study was conducted in patients with upper urinary tract calculi admitted between January 2016 and January 2020. The patients were randomly grouped into the training and validation sets. The training set was used to identify the urosepsis risk factors and construct a risk prediction model based on ultrasound and urinalysis. The validation set was used to test the performance of the artificial neural network (ANN). RESULTS: Ultimately, 1716 patients (10.8% cases and 89.2% control) were included. Eight variables were selected for the model: sex, age, body temperature, diabetes history, urine leukocytes, urine nitrite, urine glucose, and degree of hydronephrosis. The area under the receiver operating curve in the validation and training sets was 0.945 (95% CI: 0.903-0.988) and 0.992 (95% CI: 0.988-0.997), respectively. Sensitivity, specificity, and Yuden index of the validation set (training set) were 80.4% (85.9%), 98.2% (99.0%), and 0.786 (0.849), respectively. CONCLUSIONS: A preliminary screening model for urosepsis based on ultrasound and urinalysis was constructed using ANN. The model could provide risk assessments for urosepsis in patients with upper urinary tract calculi.

The Handling of Oxalate in the Body and the Origin of Oxalate in Calcium Oxalate Stones.

Urolithiasis is one of the most common urologic diseases in industrialized societies. More than 80% of renal stones are composed of calcium oxalate, and small changes in urinary oxalate concentrations affect the risk of stone formation. Elucidation of the source of oxalate and its mechanism of transport is crucial for understanding the etiology of urolithiasis. Sources of oxalate can be both endogenous and exogenous. With regard to oxalate transport, tests were carried out to prove the function of solute-linked carrier 4 (SLC4) and SLC26. The molecular mechanism of urolithiasis caused by SLC4 and SLC26 is still unclear. The growing number of studies on the molecular physiology of SLC4 and SLC26, together with knockout genetic mouse model experiments, suggest that SLC4 and SLC26 may be a contributing element to urolithiasis. This review summarizes recent research on the sources of oxalate and characterization of the oxalate transport ionic exchangers SLC4 and SLC26, with an emphasis on different physiological defects in knockout mouse models including kidney stone formation. Furthermore, SLC4 and SLC26 exchangers provide new insight into urolithiasis and may be a novel therapeutic target for modification of urinary oxalate excretion.