Tumor-associated macrophage enhances PD-L1-mediated immune escape of bladder cancer through PKM2 dimer-STAT3 complex nuclear translocation.

Tumor-associated macrophages (TAMs) are important components of the tumor microenvironment (TME) and strongly associated with poor prognosis and drug resistance, including checkpoint blockade immunotherapy in solid tumor patients. However, the mechanism by which TAM affects immune metabolism reprogramming and immune checkpoint signalling pathway in the TME remains elusive. In this study we found that transforming growth factor-beta (TGF-ß) secreted by M2-TAMs increased the level of glycolysis in bladder cancer (BLCA) and played important role in PD-L1-mediated immune evasion through pyruvate kinase isoenzymes M2 (PKM2). Mechanistically, TGF-ß promoted high expression of PKM2 by promoting the nuclear translocation of PKM2 dimer in conjunction with phosphorylated signal transducer and activator of transcription (p-STAT3), which then exerted its kinase activity to promote PD-L1 expression in BLCA. Moreover, SB-431542 (TGF-ß blocker) and shikonin (PKM2 inhibitor) significantly reduced PD-L1 expression and inhibited BLCA growth and organoids by enhancing anti-tumor immune responses. In conclusion, M2-TAM-derived TGF-ß promotes PD-L1-mediated immune evasion in BLCA by increasing the PKM2 dimer-STAT3 complex nuclear translocation. Combined blockade of the TGF-ß receptor and inhibition of PKM2 effectively prevent BLCA progression and immunosuppression, providing a potential targeted therapeutic strategy for BLCA.

Explore the shared molecular mechanism between dermatomyositis and nasopharyngeal cancer by bioinformatic analysis.

BACKGROUND: Dermatomyositis (DM) is prone to nasopharyngeal carcinoma (NPC), but the mechanism is unclear. This study aimed to explore the potential pathogenesis of DM and NPC. METHODS: The datasets GSE46239, GSE142807, GSE12452, and GSE53819 were downloaded from the GEO dataset. The disease co-expression module was obtained by R-package WGCNA. We built PPI networks for the key modules. ClueGO was used to analyze functional enrichment for the key modules. DEG analysis was performed with the R-package "limma". R-package "pROC" was applied to assess the diagnostic performance of hub genes. MiRNA-mRNA networks were constructed using MiRTarBase and miRWalk databases. RESULTS: The key modules that positively correlated with NPC and DM were found. Its intersecting genes were enriched in the negative regulation of viral gene replication pathway. Similarly, overlapping down-regulated DEGs in DM and NPC were also enriched in negatively regulated viral gene replication. Finally, we identified 10 hub genes that primarily regulate viral biological processes and type I interferon responses. Four key genes (GBP1, IFIH1, IFIT3, BST2) showed strong diagnostic performance, with AUC>0.8. In both DM and NPC, the expression of key genes was correlated with macrophage infiltration level. Based on hub genes' miRNA-mRNA network, hsa-miR-146a plays a vital role in DM-associated NPC. CONCLUSIONS: Our research discovered pivot genes between DM and NPC. Viral gene replication and response to type I interferon may be the crucial bridge between DM and NPC. By regulating hub genes, MiR-146a will provide new strategies for diagnosis and treatment in DM complicated by NPC patients. For individuals with persistent viral replication in DM, screening for nasopharyngeal cancer is necessary.

Microtubule interacting and trafficking domain containing 1 deficiency leads to poor survival via tissue factor-mediated coagulation in bladder cancer.

BACKGROUND: Patients with cancer are at an increased risk of developing a hypercoagulative phenotype and venous thromboembolism. However, no clinical trial has yet confirmed that anticoagulant therapy improves cancer prognosis, and the mechanism underlying hypercoagulation in patients with bladder cancer is not well understood. OBJECTIVES: We hypothesized that the prognostic genes affect tumor progression via tumor-mediated coagulation. METHODS: We detected the most significant prognostic genes of bladder cancer with The Cancer Genome Atlas dataset and validated them in 2 Gene Expression Omnibus datasets and 1 ArrayExpress dataset. Immunohistochemical tests were performed on a cohort of 80 individuals to further examine the prognostic genes. For the most reliable prognostic gene, its influence on coagulation was evaluated with gene knockdown followed by next-generation sequencing and cellular and animal experiments. RESULTS: Depletion of microtubule interacting and trafficking domain containing 1 (MITD1), a major prognostic gene of bladder cancer, significantly increased the tissue factor (TF) expression. MITD1 deficiency led to cytokinesis arrest, which, in turn, promoted the TF expression via unfolded protein response and c-Jun. The knockdown of IRE1, an essential kinase of unfolded protein response or the inactivation of c-Jun using c-Jun N-terminal kinase inhibitors weakened MITD1 deficiency- or dithiothreitol-induced TF upregulation. Cells lacking MITD1 promoted coagulation and metastasis in the experimental metastasis assay. CONCLUSION: Our findings suggest the novel role of tumor prognostic genes upon the development of hypercoagulative phenotype and venous thromboembolism, thereby underlining the importance of anticoagulant therapy and shedding light on the therapeutic value of targeting MITD1 in bladder cancer.

Ultrathin and Biodegradable Bismuth Oxycarbonate Nanosheets with Massive Oxygen Vacancies for Highly Efficient Tumor Therapy.

Nanomaterials doped with high atom number elements can improve the efficacy of cancer radiotherapy, but their clinical application faces obstacles, such as being difficult to degrade in vivo, or still requiring relatively high radiation dose. In this work, a bismuth oxycarbonate-based ultrathin nanosheet with the thickness of 2.8 nm for safe and efficient tumor radiotherapy under low dose of X-ray irradiation is proposed. The high oxygen content (62.5% at%) and selective exposure of the facets of ultrathin 2D nanostrusctures facilitate the escape of large amounts of oxygen atoms on bismuth nanosheets from surface, forming massive oxygen vacancies and generating reactive oxygen species that explode under the action of X-rays. Moreover, the exposure of almost all atoms to environmental factors and the nature of oxycarbonates makes the nanosheets easily degrade into biocompatible species. In vivo studies demonstrate that nanosheets could induce apoptosis in cancer cells after low dose of X-ray irradiation without causing any damage to the liver or kidney. The tumor growth inhibition effect of radiotherapy increases from 49.88% to 90.76% with the help of bismuth oxycarbonate nanosheets. This work offers a promising future for nanosheet-based clinical radiotherapies of malignant cancers.

Multifunctional amphibious superhydrophilic-oleophobic cellulose nanofiber aerogels for oil and water purification.

Aerogels are of a popular choice for oil-water separation and water purification due to their attractive properties, such as lightweight, large surface area, and high porosity. Developing robust aerogels with multifunctional characteristics is highly desirable but remains challenging nowadays. Herein, we develop a facile one-pot condensation strategy for the fabrication of superhydrophilic-oleophobic (SHI-OP) composite aerogels using cellulose nanofibers (CNF), 3-glycidy-loxypropyl trimethoxysilane (GPTMS), polyethyleneimine (PEI) and fluorine-contained compound (FS-60). The resulted aerogels exhibit a directional lamellar structure with interconnected macropores, super-lightweight with high porosity of 98.30 % and low density of 0.0256 g·cm-3. Also, the aerogels are mechanically durable against repeated compression. Meanwhile, the amphibious SHI-OP feature of the composite aerogels in both air and water states enables them to not only absorb trace amount of water from contaminated oils, but also separate oil-water mixtures with separation efficiency of over 99 % and high permeation flux of over 9060 L/m2·h. Moreover, the aerogels also show excellent dye adsorption capability and reusability toward anionic dyes with a maximum adsorption capacity of 1245.68 mg/g. Such robust and multifunctional aerogels with special surface wettability provide good opportunity for liquid purification and dye-containing wastewater treatment.

Presence, Subtypes, and Prognostic Significance of Tertiary Lymphoid Structures in Urothelial Carcinoma of the Bladder.

OBJECTIVE: To evaluate the presence and subtypes of tertiary lymphatic structures (TLSs) in urothelial carcinoma of the bladder (UCB) and to analyze their associated clinicopathological characteristics and prognostic significance. METHODS: The study enrolled 580 patients with surgically treated UCB, including 313 non-muscle invasive bladder cancer (NMIBC) and 267 muscle-invasive bladder cancer (MIBC). The presence and subtypes of TLSs were identified by immunohistochemistry (CD20, CD3, Bcl-6, and CD21). TLSs were classified into non-GC (nGC) TLS and GC TLS subtypes based on germinal center (GC) formation. Disease-free survival (DFS) was used as an endpoint outcome to evaluate the prognostic significance of TLS and its subtypes in UCB. RESULTS: TLSs were more common in MIBC than in NMIBC (67.8% vs 48.2%, P < .001), and the tumor-infiltrating lymphocyte (TIL) mean density was significantly higher in MIBC than in NMIBC (24.0% vs 17.5%, P < .001). Moreover, a positive correlation was found between TLS presence and GC structure formation and TIL infiltration in UCB. Endpoint events occurred in 191 patients. Compared to patients with endpoint events, patients without disease progression exhibited higher TIL density and more TLSs (P < .05). Kaplan-Meier curves showed that TLS was associated with better DFS in NMIBC (P = .041) and MIBC (P = .049). However, the Cox multivariate analysis did not demonstrate the prognostic significance of TLS. CONCLUSIONS: TLS is heterogeneous in UCB, and that TLS and GC structures are related to TIL density and prognostic events. However, TLS as a prognostic indicator remains unclear, warranting further investigation.

Telemedicine network latency management system in 5G telesurgery: a feasibility and effectiveness study.

BACKGROUND: Network latency is the most important factor affecting the performance of telemedicine. The aim of the study is to assess the feasibility and efficacy of a novel network latency management system in 5G telesurgery. METHODS: We conducted 20 telesurgery simulation trials (hitching rings to columns) and 15 remote adrenalectomy procedures in the 5G network environment. Telemedicine Network Latency Management System and the traditional "Ping command" method (gold standard) were used to monitor network latency during preoperative simulated telesurgery and formal telesurgery. We observed the working status of the Telemedicine Network Latency Management System and calculated the difference between the network latency data and packet loss rate detected by the two methods. In addition, due to the lower latency of the 5G network, we tested the alert function of the system using the 4G network with relatively high network latency. RESULTS: The Telemedicine Network Latency Management System showed no instability during telesurgery simulation trials and formal telesurgery. After 20 telesurgery simulation trials and 15 remote adrenalectomy procedures, the p-value for the difference between the network latency data monitored by the Telemedicine Network Latency Management System and the "Ping command" method was greater than 0.05 in each case. Meanwhile, the surgeons reported that the Telemedicine Network Latency Management System had a friendly interface and was easy to operate. Besides, when the network latency exceeded a set threshold, a rapid alarm sounded in the system. CONCLUSION: The Telemedicine Network Latency Management System was simple and easy to operate, and it was feasible and effective to use it to monitor network latency in telesurgery. The system had an intuitive and concise interface, and its alarm function increased the safety of telesurgery. The system's own multidimensional working ability and information storage capacity will be more suitable for telemedicine work.

Deep learning signature based on multiphase enhanced CT for bladder cancer recurrence prediction: a multi-center study.

Background: Accurate stratification of recurrence risk for bladder cancer (BCa) is essential for precise individualized therapy. This study aimed to develop and validate a model for predicting the risk of recurrence in BCa patients postoperatively using 3-phase enhanced CT images. Methods: We retrospectively enrolled 874 BCa patients across four centers between January 2006 and December 2021. Patients from one center were used as training set, while the remaining patients went into the validation set. We trained a deep learning (DL) model based on convolutional neural networks using 3-phase enhanced CT images. The resulting prediction scores were entered into Cox regression analysis to obtain DL scores and construct a DL signature. DL scores and clinical features were then used as deep learning radioclinical signature. The predictive performance of DL signature was assessed according to concordance index and area under curve compared with deep learning radioclinical signature, clinical model and a widely accepted staging grading system. Recurrence-free survival (RFS) and overall survival (OS) were also predicted in order to further assess survival benefits. Findings: DL signature showed strong power for predicting recurrence (concordance index, 0.869; area under curve, 0.889) in validation set, outperforming other models and system. In addition, we divided RFS and OS into high and low risk groups by selecting appropriate cutoff values for DL signature, and calculated cumulative recurrence risk rates for both groups. Interpretation: Our proposed DL signature shows promising potential as clinical aid for predicting postoperative recurrence risk in BCa and for stratifying the risk of RFS and OS, which can be applied to guide personalized precision therapy. Funding: There are no sources of funding for this manuscript.

Cancer-associated fibroblasts-derived CXCL12 enhances immune escape of bladder cancer through inhibiting P62-mediated autophagic degradation of PDL1.

BACKGROUND: Cancer-associated fibroblasts (CAFs), the predominant stromal cell of tumor microenvironment (TME), play an important role in tumor progression and immunoregulation by remodeling extracellular matrix (ECM) and secreting cytokines. However, little is known about the details of the underlying mechanism in bladder cancer. METHODS: Bioinformatics analysis was performed to analyze the prognostic value of CAFs and CXCL12 using GEO, TCGA and SRA databases. The effects of CXCL12 on bladder cancer progression were investigated through in vitro and in vivo assays. The biological mechanism of the effect of CXCL12 on PDL1 were investigated using western blotting, immunoprecipitation, RT-PCR, immunofluorescence, mass spectrometry, protein stability, and flow cytometry. RESULTS: The results demonstrated that CAFs-derived CXCL12 promoted cancer cell migration and invasion and upregulated PDL1. Mechanistically, upon binding to its specific receptor, CXCL12 activated the downstream JAK2/STAT3 pathway and rapidly up-regulated the expression of deubiquitinase CYLD. CYLD deubiquitinated P62 causing P62 accumulation, which in turn inhibited the autophagic degradation of PDL1. In vivo experiments demonstrated that blocking CXCL12 inhibited tumor growth, reduced tumor PDL1 expression and increased immune cell infiltration. CONCLUSIONS: This study revealed a novel mechanism for the role of CXCL12 in P62-mediated PDL1 autophagic regulation. Combined application of CXCL12 receptor blocker and PD1/PDL1 blocker can more effectively inhibit PDL1 expression and enhance antitumor immune response. Targeting CAFs-derived CXCL12 may provide an effective strategy for immunotherapy in bladder cancer.

Modification of lysine-260 2-hydroxyisobutyrylation destabilizes ALDH1A1 expression to regulate bladder cancer progression.

ALDH1A1 is one of the classical stem cell markers for bladder cancer. Lysine 2-hydroxyisobutyrylation (Khib) is a newfound modification to modulate the protein expression, and the underlying mechanisms of how ALDH1A1 was regulated by Khib modification in bladder cancer remains unknown. Here, ALDH1A1 showed a decreased K260hib modification, as identified by protein modification omics in bladder cancer. Decreasing ALDH1A1 expression significantly suppressed the proliferation, migration and invasion of bladder cancer cells. Moreover, K260hib modification is responsible for the activity of ALDH1A1 in bladder cancer, which is regulated by HDAC2/3. Higher K260hib modification on ALDH1A1 promotes protein degradation through chaperone-mediated autophagy (CMA), and ALDH1A1 K260hib could sensitize bladder cancer cells to chemotherapeutic drugs. Higher ALDH1A1 expression with a lower K260hib modification indicates a poor prognosis in patients with bladder cancer. Overall, we demonstrated that K260hib of ALDH1A1 can be used as a potential therapeutic target for bladder cancer treatment.

Oxymatrine inhibits melanoma development by modulating the immune microenvironment and targeting the MYC/PD-L1 pathway.

Oxymatrine, also known as ammothamnine or oxysophoridine, is a natural compound isolated from Sophora flavescens (in Chinese, Kushen), and many previous researchers have characterized its anti-inflammatory, anti-fibrotic and anti-tumor properties. However, the underlying anti-tumor immunological mechanism of oxymatrine remains elusive. In this study, we carried out experiments both in vitro and in vivo and investigated the anti-tumor effect of oxymatrine to inhibit the proliferation and migration of melanoma B16 cells, while promoting apoptosis. Oxymatrine upregulated CD4+ T, CD8+ T and NKT cells, downregulated Treg cells, promoted TNF-α secretion, and successfully modulated the immune microenvironment and ultimately suppressed melanoma development in subcutaneous tumor models established in mice. Evidence from network pharmacology and RNAseq suggested that possible targets of oxymatrine for melanoma treatment included PD-L1 and MYC. We observed oxymatrine inhibited PD-L1 and MYC expression in melanoma cells via qRT-PCR and western blotting analysis, and found MYC potentially regulated PD-L1 to mediate anti-tumor effects. These findings provide insight into the mechanism by which oxymatrine inhibits melanoma and enhances the anti-tumor immune effect. In summary, our study proposes a novel approach to suppress melanoma by targeting the MYC/PD-L1 pathway using oxymatrine, which may develop into a less toxic and more efficient anti-tumor agent for melanoma treatment.

Tyro3 receptor tyrosine kinase contributes to pathogenic phenotypes of fibroblast-like synoviocytes in rheumatoid arthritis and disturbs immune cell balance in experimental arthritis.

Rheumatoid arthritis (RA) is a systemic autoimmune disorder characterized by synovitis and joint damage, the underlying causes of which remain unclear. Our prior investigations revealed a notable correlation between the expression of Tyro3 Protein Tyrosine Kinase (Tyro3TK) and the progression of RA. To further elucidate the pathogenic role of Tyro3TK in RA, we analyzed the influence of Tyro3TK on pathogenic phenotypes of RA fibroblast like synoviocyte (FLS) in vitro and compared disease severity, joint damages and immunological parameters of K/BxN serum transfer arthritis (STA) in Tyro3TK-/- deficient mice and wild type controls. Our findings underscored the remarkable effectiveness of Tyro3TK blockade, as evidenced by diminished secretion of inflammatory cytokines and matrix metalloproteinases (MMPs), curtailed migration and invasiveness of RAFLS, and attenuated differentiation of pathogenic helper T cell subsets mediated by RAFLS. Correspondingly, our in vivo investigations illuminated the more favorable outcomes in Tyro3TK-deficient mice, characterized by reduced joint pathology, tempered synovial inflammation, and restored immune cell equilibrium. These data suggested that Tyro3TK might contribute to aggravated autoimmune arthritis and immunological pathology and act as a potential therapeutic target for RA.

Deep learning techniques for imaging diagnosis of renal cell carcinoma: current and emerging trends.

This study summarizes the latest achievements, challenges, and future research directions in deep learning technologies for the diagnosis of renal cell carcinoma (RCC). This is the first review of deep learning in RCC applications. This review aims to show that deep learning technologies hold great promise in the field of RCC diagnosis, and we look forward to more research results to meet us for the mutual benefit of renal cell carcinoma patients. Medical imaging plays an important role in the early detection of renal cell carcinoma (RCC), as well as in the monitoring and evaluation of RCC during treatment. The most commonly used technologies such as contrast enhanced computed tomography (CECT), ultrasound and magnetic resonance imaging (MRI) are now digitalized, allowing deep learning to be applied to them. Deep learning is one of the fastest growing fields in the direction of medical imaging, with rapidly emerging applications that have changed the traditional medical treatment paradigm. With the help of deep learning-based medical imaging tools, clinicians can diagnose and evaluate renal tumors more accurately and quickly. This paper describes the application of deep learning-based imaging techniques in RCC assessment and provides a comprehensive review.

Knowledge mapping and global trends in the field of low-intensity pulsed ultrasound and endocrine and metabolic diseases: a bibliometric and visual analysis from 2012 to 2022.

Background: Low-intensity pulsed ultrasound (LIPUS) is a highly promising therapeutic method that has been widely used in rehabilitation, orthopedics, dentistry, urology, gynecology, and other multidisciplinary disease diagnoses and treatments. It has attracted extensive attention worldwide. However, there is currently a lack of comprehensive and systematic research on the current status and future development direction of the LIPUS field. Therefore, this study comprehensively analyzed LIPUS-related reports from the past decade using bibliometrics methods, and further conducted research specifically focusing on its application in endocrine and metabolic diseases. Methods: We downloaded LIPUS literature from 2012 to 2022 reported in the Web of Science Core Collection Science Citation Index-Expanded and Social Sciences Citation Index, and used bibliometric analysis software such as VOSviewer and CiteSpace to execute the analysis and visualize the results. Results: We searched for 655 English articles published on LIPUS from 2012 to 2022. China had the highest number of published articles and collaborations between China and the United States were the closest in this field. Chongqing Medical University was the institution with the highest output, and ULTRASOUND IN MEDICINE AND BIOLOGY was the journal with the most related publications. In recent years, research on the molecular mechanisms of LIPUS has continued to deepen, and its clinical applications have also continued to expand. The application of LIPUS in major diseases such as oxidative stress, regeneration mechanism, and cancer is considered to be a future research direction, especially in the field of endocrinology and metabolism, where it has broad application value. Conclusion: Global research on LIPUS is expected to continue to increase, and future research will focus on its mechanisms of action and clinical applications. This study comprehensively summarizes the current development status and global trends in the field of LIPUS, and its research progress in the field of endocrine and metabolic diseases, providing valuable reference for future research in this field.

A Nano-Autophagy Inhibitor Triggering Reciprocal Feedback Control of Cholesterol Depletion for Solid Tumor Therapy.

Solid tumors are characterized by enhanced metabolism of lipid, particularly cholesterol, inspiring the exploration of metabolic therapy through cholesterol oxidase (COD)-mediated cholesterol deprivation. However, the therapeutic efficacy of COD is limited due to the hypoxic tumor microenvironment and the protective autophagy triggered by cholesterol deprivation. Herein, a combination therapy for metabolically treating solid tumors through COD in conjunction with molybdenum oxide nanodots (MONDs), which serve as both potent oxygen generators and autophagy inhibitors, is reported. MONDs convert H2 O2 (arising from COD-mediated cholesterol oxidation) into O2 , which is then recycled by COD to form reciprocal feedback for cholesterol depletion. Concurrently, MONDs can overcome autophagy-induced therapeutic resistance frequently occurring in conventional nutrient deprivation therapy by activating AKT/mTOR pathway phosphorylation. Combination therapy in the xenograft model results in an ≈5-fold increase in therapeutic efficiency as compared with COD treatment alone. This functionally cooperative metabolic coupling strategy holds great promise as a novel polytherapy approach that will benefit patients with solid tumors.

Integrated multiomics analysis and machine learning refine molecular subtypes and prognosis for muscle-invasive urothelial cancer.

Muscle-invasive urothelial cancer (MUC), characterized by high aggressiveness and significant heterogeneity, is currently lacking highly precise individualized treatment options. We used a computational pipeline to synthesize multiomics data from MUC patients using 10 clustering algorithms, which were then combined with 10 machine learning algorithms to identify molecular subgroups of high resolution and develop a robust consensus machine learning-driven signature (CMLS). Through multiomics clustering, we identified three cancer subtypes (CSs) that are related to prognosis, with CS2 exhibiting the most favorable prognostic outcome. Subsequent screening enabled identification of 12 hub genes that constitute a CMLS with robust predictive power for prognosis. The low-CMLS group exhibited a more favorable prognosis and greater responsiveness to immunotherapy and was more likely to exhibit the "hot tumor" phenotype. The high-CMLS group had a poor prognosis and lower likelihood of benefitting from immunotherapy, but dasatinib and romidepsin may serve as promising treatments for them. Comprehensive analysis of multiomics data can offer important insights and further refine the molecular classification of MUC. Identification of CMLS represents a valuable tool for early prediction of patient prognosis and for screening potential candidates likely to benefit from immunotherapy, with broad implications for clinical practice.