Distinct immune and inflammatory response patterns contribute to the identification of poor prognosis and advanced clinical characters in bladder cancer patients

MiR-125b suppresses bladder Cancer cell growth and triggers apoptosis by regulating IL-6/IL-6R/STAT3 axis in vitro and in vivo

Bladder cancer (BLCA) is an aggressive malignancy characterized by limited therapeutic options and a poor prognosis. Research has indicated that abnormally expressed miRNAs play a significant role in the pathogenesis of BLCA, although the specific mechanisms remain unclear. MiR-125b plays a tumor suppressor role in a variety of cancers and affects the biological processes of cancer cells such as proliferation, invasion, migration and apoptosis by regulating different signaling pathways. Elucidation of the molecular mechanisms underlying miR-125b may provide clinical therapeutic strategies for bladder cancer. Here, miR-125b was downregulated whereas its targets IL-6R and STAT3 were upregulated in BLCA, as evidenced by bioinformatics analysis. Kaplan-Meier analysis confirmed that miR-125b serves as an independent prognostic factor linked to overall survival (OS) in patients with bladder cancer. Furthermore, overexpression of miR-125b significantly inhibited BLCA cell proliferation, migration, and invasion, while promoting apoptosis, as evidenced by an increased Bax/Bcl-2 ratio and activated cleaved caspase-3. Further investigations demonstrated that miR-125b directly targets and downregulates both IL-6R and STAT3. In a xenograft model, miR-125b overexpression effectively inhibited tumor growth in bladder cancer by blocking IL-6/IL-6R and STAT3 signaling pathways. Collectively, these findings broaden our understanding of the mechanism by which miR-125b acting as a BLCA suppressor in apoptotic regulation by targeting the IL-6/IL-6R/STAT3 signaling pathway, providing novel insights regarding the design of novel miRNA based therapeutic strategies against BLCA.

Organ-specific cancer biomarker identification: a ten-year single-center study in southern China

Cancer biomarker discovery is essential for early detection and monitoring, yet there is a lack of comprehensive studies examining organ-specific biomarkers across various cancer types. In this study, we analyzed clinical data from 59,184 cancer patients diagnosed between 2013 and 2023, focusing on 11 major cancer systems. We used propensity score matching with 55,010 healthy controls to create balanced comparison groups. Serum biomarker profiles were assessed through principal component analysis, differential expression analysis, and ROC curve analysis. Our findings revealed organ-specific biomarker patterns, such as decreased CA724, ferritin, and β2-microglobulin in thoracic cancer, reduced serum phosphorus in neurological cancer, and elevated cystatin C and creatinine in urinary system cancer. Further analysis across 22 cancer types uncovered additional biomarkers, including elevated ALT in hepatobiliary cancer, altered coagulation factors in laryngeal cancer, increased monocytes in pancreatic cancer, and reduced complement C3 in intestinal cancer. These results provide valuable insights into the unique biomarker signatures for different cancers, contributing to the potential development of more targeted and efficient screening methods.

Rapid and accurate diagnosis of urinary tract infections using targeted next-generation sequencing: A multicenter comparative study with metagenomic sequencing and traditional culture methods

BACKGROUND

Urinary tract infections (UTIs) rank among the most prevalent bacterial infections globally. Traditional urine culture methods have significant limitations in detection time and sensitivity, prompting the need to evaluate targeted next-generation sequencing (tNGS) as a potential diagnostic tool.

METHODS

The study included a discovery cohort of 400 suspected UTI patients (202 analyzed) and a validation cohort of 200 patients (110 analyzed). The study assessed detection time, concordance rates, ability to identify polymicrobial infections, and antibiotic resistance genes (ARGs). Both clear and turbid urine samples were evaluated across different clinical settings.

RESULTS

In the discovery cohort, tNGS demonstrated 96.5% concordance with culture-positive samples, while showing superior specificity in culture-negative specimens (53.1% vs 28.1% for mNGS). Detection time for tNGS (12.89 h) was notably shorter than mNGS (17.38 h) and traditional culture (61.48 h). tNGS exhibited remarkable capability in identifying polymicrobial infections (55.4% of samples), significantly outperforming both mNGS (27.7%) and traditional culture methods, which failed to detect any co-infections. The method showed particular strength in detecting fastidious organisms like Ureaplasma parvum and fungal species such as Candida tropicalis. For antibiotic resistance prediction, tNGS detected more ARGs (52.67% vs 41.22% for mNGS) and achieved 100% sensitivity for vancomycin and methicillin resistance in Gram-positive pathogens. The validation cohort confirmed tNGS's robust performance, maintaining high concordance rates for both culture-positive (90.00%) and culture-negative samples (55.00%), demonstrating consistent reliability across different clinical settings CONCLUSIONS: tNGS demonstrates advantages in rapid and accurate UTI diagnosis, particularly in detecting polymicrobial infections and analyzing antibiotic resistance genes. It shows promise as an effective complementary tool for UTI diagnostics.

Single-cell and bulk RNA-sequence identified fibroblasts signature and CD8 + T-cell - fibroblast subtype predicting prognosis and immune therapeutic response of bladder cancer, based on machine learning: bioinformatics multi-omics study

BACKGROUND

Cancer-associated fibroblasts (CAFs) are found in primary and advanced tumours. They are primarily involved in tumour progression through complex mechanisms with other types of cells in the tumour microenvironment. However, essential fibroblasts-related genes (FRG) in bladder cancer still need to be explored, and there is a shortage of an ideal predictive model or molecular subtype for the progression and immune therapeutic assessment for bladder cancer, especially muscular-invasive bladder cancer based on the FRG.

MATERIALS AND METHODS

CAF-related genes of bladder cancer were identified by analysing single-cell RNA sequence datasets, and bulk transcriptome datasets and gene signatures were used to characterize them. Then, 10 types of machine learning algorithms were utilised to determine the hallmark FRG and construct the FRG index (FRGI) and subtypes. Further molecular subtypes combined with CD8+ T-cells were established to predict the prognosis and immune therapy response.

RESULTS

Fifty-four BLCA-related FRG were screened by large-scale scRNA-sequence datasets. The machine learning algorithm established a 3-genes FRGI. High FRGI represented a worse outcome. Then, FRGI combined clinical variables to construct a nomogram, which shows high predictive performance for the prognosis of bladder cancer. Furthermore, the BLCA datasets were separated into two subtypes - fibroblast hot and cold types. In five independent BLCA cohorts, the fibroblast hot type showed worse outcomes than the cold type. Multiple cancer-related hallmark pathways are distinctively enriched in these two types. In addition, high FRGI or fibroblast hot type shows a worse immune therapeutic response. Then, four subtypes called CD8-FRG subtypes were established under the combination of FRG signature and activity of CD8+ T-cells, which turned out to be effective in predicting the prognosis and immune therapeutic response of bladder cancer in multiple independent datasets. Pathway enrichment analysis, multiple gene signatures, and epigenetic alteration characterize the CD8-FRG subtypes and provide a potential combination strategy method against bladder cancer.

CONCLUSIONS

In summary, the authors established a novel FRGI and CD8-FRG subtype by large-scale datasets and organised analyses, which could accurately predict clinical outcomes and immune therapeutic response of BLCA after surgery.

Clinical biomarker profiles reveals gender differences and mortality factors in sepsis

Background

Sepsis is a major contributor to global morbidity and mortality, affecting millions each year. Notwithstanding the decline in sepsis incidence and mortality over decades, gender disparities in sepsis outcomes persist, with research suggesting higher mortality rates in males.

Methods

This retrospective study aims to delineate gender-specific clinical biomarker profiles impacting sepsis progression and mortality by examining sepsis cases and related clinical data from the past three years. Propensity score matching was used to select age-matched healthy controls for comparison.

Results

Among 265 sepsis patients, a significantly higher proportion were male (60.8%, P<0.001). While mortality did not significantly differ by gender, deceased patients were significantly older (mean 69 vs 43 years, P=0.003), more likely to have hypertension (54% vs 25%, P=0.019), and had higher SOFA scores (mean ~10 vs 4, P<0.01) compared to survivors. Principal Component Analysis (PCA) showed clear separation between sepsis patients and healthy controls. 48 serum biomarkers were significantly altered in sepsis, with Triiodothyronine, Apolipoprotein A, and Serum cystatin C having the highest diagnostic value by ROC analysis. Gender-stratified comparisons identified male-specific (e.g. AFP, HDLC) and female-specific (e.g. Rheumatoid factor, Interleukin-6) diagnostic biomarkers. Deceased patients significantly differed from survivors, with 22 differentially expressed markers; Antithrombin, Prealbumin, HDL cholesterol, Urea nitrogen and Hydroxybutyrate had the highest diagnostic efficiency for mortality.

Conclusion

These findings enhance our understanding of gender disparities in sepsis and may guide future therapeutic strategies. Further research is warranted to validate these biomarker profiles and investigate the molecular mechanisms underlying these gender differences in sepsis outcomes.

TRP Ion Channels in Immune Cells and Their Implications for Inflammation

The transient receptor potential (TRP) ion channels act as cellular sensors and mediate a plethora of physiological processes, including somatosensation, proliferation, apoptosis, and metabolism. Under specific conditions, certain TRP channels are involved in inflammation and immune responses. Thus, focusing on the role of TRPs in immune system cells may contribute to resolving inflammation. In this review, we discuss the distribution of five subfamilies of mammalian TRP ion channels in immune system cells and how these ion channels function in inflammatory mechanisms. This review provides an overview of the current understanding of TRP ion channels in mediating inflammation and may offer potential avenues for therapeutic intervention.

Identification of bladder cancer subtypes and predictive model for prognosis, immune features, and immunotherapy based on neutrophil extracellular trap-related genes

Bladder cancer is the most common malignant tumor of urinary system, and its morbidity and mortality are increasing rapidly. Although great advances have been made in medical technology in recent years, there is still a lack of effective prognostic and therapeutic methods for bladder cancer. NETs are reticulated DNA structures decorated with various protein substances released extracellularly by neutrophils stimulated by strong signals. Recently, it has been found that NETs are closely related to the growth, metastasis and drug resistance of many types of cancers. However, up to now, the research on the relationship between NETs and bladder cancer is still not enough. In this study, we aimed to conduct a comprehensive analysis of NRGs in bladder cancer tissues to evaluate the relationship between NRGs and prognosis prediction and sensitivity to therapy in patients with bladder cancer. We scored NRGs in each tissue by using ssGSEA, and selected gene sets that were significantly associated with NRGs scores by using the WCGNA algorithm. Based on the expression profiles of NRGs-related genes, NMF clustering analysis was performed to identify different BLCA molecular subtypes. For the differentially expressed genes between subtypes, we used univariate COX regression, LASSO regression and multivariate COX regression to further construct a hierarchical model of BLCA patients containing 10 genes. This model and the nomogram based on this model can accurately predict the prognosis of BLCA patients in multiple datasets. Besides, BLCA patients classified based on this model differ greatly in their sensitivity to immunotherapy and targeted therapies, which providing a reference for individualized treatment of patients with bladder cancer.

The genetic associations of COVID-19 on genitourinary symptoms

Background

Recently emerged reports indicated that patients with coronavirus disease 2019 (COVID-19) might experience novo genitourinary symptoms after discharge. Nevertheless, the causal associations and underlying mechanisms remain largely unclear.

Methods

Genome-wide association study (GWAS) statistics for COVID-19 and 28 genitourinary symptoms with consistent definitions were collected from the COVID-19 Host Genetic Initiative, FinnGen, and UK Biobanks. Mendelian randomization (MR) analyses were applied to explore the causal effects of COVID-19 on genitourinary symptoms by selecting single-nucleotide polymorphisms as instrumental variables. Meta-analyses were conducted to evaluate the combined causal effect. Molecular pathways connecting COVID-19 and its associated disorders were evaluated by weighted gene co-expression network analysis (WGCNA) and enrichment analyses to extract insights into the potential mechanisms underlying the connection.

Results

The MR and meta-analyses indicated that COVID-19 was causally associated with increased risk for calculus of the lower urinary tract (LUTC, OR: 1.2984 per doubling in odds of COVID-19, 95% CI: 1.0752-1.5680, p = 0.007) and sexual dysfunction (SD, OR: 1.0931, 95% CI: 1.0292-1.1610, p = 0.004). Intriguingly, COVID-19 might exert a slight causal protective effect on the progression of urinary tract infections (UTIs) and bladder cancer (BLCA). These results were robust to sensitivity analyses. Bioinformatic analyses indicated that the inflammatory-immune response module may mediate the links between COVID-19 and its associated disorders at the molecular level.

Conclusions

In response to post-COVID-19 symptoms, we recommend that COVID-19 patients should strengthen the prevention of LUTC and the monitoring of sexual function. Meanwhile, the positive effects of COVID-19 on UTIs and BLCA should attach equal importance.

The Application of Single-Cell RNA Sequencing in the Inflammatory Tumor Microenvironment

The initiation and progression of tumors are complex. The cancer evolution-development hypothesis holds that the dysregulation of immune balance is caused by the synergistic effect of immune genetic factors and environmental factors that stimulate and maintain non-resolving inflammation. Throughout the cancer development process, this inflammation creates a microenvironment for the evolution and development of cancer. Research on the inflammatory tumor microenvironment (TME) explains the initiation and progression of cancer and guides anti-cancer immunotherapy. Single-cell RNA sequencing (scRNA-seq) can detect the transcription levels of cells at the single-cell resolution level, reveal the heterogeneity and evolutionary trajectory of infiltrated immune cells and cancer cells, and provide insight into the composition and function of each cell group in the inflammatory TME. This paper summarizes the application of scRNA-seq in inflammatory TME.