Identification of a Prognosis-Related Risk Signature for Bladder Cancer to Predict Survival and Immune Landscapes

An immune biomarker associated with EMT serves as a predictor for prognosis and drug response in bladder cancer

BACKGROUND

Bladder cancer (BLCA), which develops from the upper endometrial of the bladder, is the sixth most prevalent cancer across the globe. WDHD1 (WD repeat and HMG-box DNA binding protein 1 gene) directly affects signaling, the cell cycle, and the development of the cell skeleton. Uncertainty surrounds WDHD1's function in BLCA immunity and prognosis, though.

MATERIALS AND METHODS

Using weighed gene co-expression network analysis (WGCNA), initially, we first identified 32 risk factors in genes with differential expression for this investigation. Then, using a variety of bioinformatic techniques and experimental validation, we examined the connections between WDHD1 and BLCA expression, clinical pathological traits, WDHD1-related proteins, upper-skin-intermediate conversion (EMT), immune cell immersion, convergence factors, immune markers, and drug sensitivity.

RESULT

The findings demonstrated that we constructed a 32-gene risk-predicting model where WDHD1 was elevated as a representative gene expression in BLCA and related to a range of clinical traits. Furthermore, high WDHD1 expression was a standalone predictor associated with a worse survival rate. The most commonly recruited cells and their evolutionary patterns were highlighted to better comprehend WDHD1's function in cancer. High WDHD1 expression was associated with many aspects of immunology. Finally, the study found that individuals with high expression of WDHD1 were drug-sensitive to four different broad-spectrum anti-cancer drugs.

CONCLUSION

These results describe dynamic changes in the tumor microenvironment in BLCA and provide evidence for the hypothesis that WDHD1 is a novel biomarker of tumor development. WDHD1 may therefore be a useful target for the detection and management of BLCA.

Sexual dimorphism in bladder cancer: a review of etiology, biology, diagnosis, and outcomes

Bladder carcinoma represents a prevalent malignancy, wherein the influence of sex extends across its incidence, biological attributes, and clinical outcomes. This scholarly exposition meticulously examines pertinent investigations, elucidating the nuanced impact of sex on bladder cancer, and posits cogent avenues for future research and intervention modalities. In the initial discourse, an exhaustive scrutiny is undertaken of the etiological underpinnings of bladder cancer, encompassing variables such as tobacco consumption, occupational exposures, and genetic aberrations. Subsequently, a comprehensive dissection unfolds, delving into the intricate biological disparities inherent in sex vis-à-vis the initiation and progression of bladder cancer. This analytical framework embraces multifaceted considerations, spanning sex hormones, sex chromosomal dynamics, metabolic enzymatic cascades, and the intricate interplay with the microbiome. Lastly, a synthesized exposition encapsulates the ramifications of gender differentials on the diagnostic and prognostic landscapes of bladder cancer, underscoring the imperative for intensified investigative endeavors directed towards elucidating gender-specific variances and the formulation of tailored therapeutic strategies.

Metabolism-related gene vaccines and immune infiltration in ovarian cancer: A novel risk score model of machine learning

BACKGROUND

The present study aims to develop a metabolic gene signature to evaluate the survival rate of ovarian cancer (OC) patients and analyze the potential mechanisms of metabolic genes in OC because the difficulty in early detection of OC often leads to poor treatment outcomes.

METHODS

A non-negative matrix factorization algorithm was applied to determine molecular subtypes according to metabolism genes. To build a risk prognosis model, least absolute shrinkage and selection operator multivariate Cox analysis was carried out with weighted correlation network analysis (WCGNA). Glycolytic flux and mitochondrial function were evaluated by conducting seahorse analysis.

RESULTS

On the basis of metabolism-related genes, the two subtypes of OC samples present in The Cancer Genome Atlas database were distinguished. An analysis of WGCNA identified 1056 genes. Lastly, a 10-gene signature (CMAS, ADH1B, PLA2G2D, BHMT, CACNA1C, AADAC, ALOX12, CYP2R1, SCN1B and ME1) was constructed that demonstrated promising performance in predicting outcome in patients with OC. The RiskScore of the gene signature was linked to microenvironment cell infiltration and immune checkpoint. Higher RiskScores were associated with poorer results for OC patients. Seahorse analysis shows the influence of CMAS in cell energy metabolism.

CONCLUSIONS

In the present study, a novel marker for evaluating the survival of OC patients was developed through the creation of a gene signature incorporating metabolism-related genes. Our knowledge of immunotherapy and microenvironment cell infiltration may be enriched by evaluating metabolism-related gene modification patterns.

A risk model based on lncRNA-miRNA-mRNA gene signature for predicting prognosis of patients with bladder cancer

OBJECTIVES

We aimed to analyze lncRNAs, miRNAs, and mRNA expression profiles of bladder cancer (BC) patients, thereby establishing a gene signature-based risk model for predicting prognosis of patients with BC.

METHODS

We downloaded the expression data of lncRNAs, miRNAs and mRNA from The Cancer Genome Atlas (TCGA) as training cohort including 19 healthy control samples and 401 BC samples. The differentially expressed RNAs (DERs) were screened using limma package, and the competing endogenous RNAs (ceRNA) regulatory network was constructed and visualized by the cytoscape. Candidate DERs were screened to construct the risk score model and nomogram for predicting the overall survival (OS) time and prognosis of BC patients. The prognostic value was verified using a validation cohort in GSE13507.

RESULTS

Based on 13 selected. lncRNAs, miRNAs and mRNA screened using L1-penalized algorithm, BC patients were classified into two groups: high-risk group (including 201 patients ) and low risk group (including 200 patients). The high-risk group's OS time ( hazard ratio [HR], 2.160; 95% CI, 1.586 to 2.942; P= 5.678e-07) was poorer than that of low-risk groups' (HR, 1.675; 95% CI, 1.037 to 2.713; P= 3.393 e-02) in the training cohort. The area under curve (AUC) for training and validation datasets were 0.852. Younger patients (age ⩽ 60 years) had an improved OS than the patients with advanced age (age > 60 years) (HR 1.033, 95% CI 1.017 to 1.049; p= 2.544E-05). We built a predictive model based on the TCGA cohort by using nomograms, including clinicopathological factors such as age, recurrence rate, and prognostic score.

CONCLUSIONS

The risk model based on 13 DERs patterns could well predict the prognosis for patients with BC.

The role of ARL4C in predicting prognosis and immunotherapy drug susceptibility in pan-cancer analysis

Background: ARLs, which are a class of small GTP-binding proteins, play a crucial role in facilitating tumor tumorigenesis and development. ARL4C, a vital member of the ARLs family, has been implicated in the progression of tumors, metastatic dissemination, and development of resistance to therapeutic drugs. Nevertheless, the precise functional mechanisms of ARL4C concerning tumor prognosis and immunotherapy drug susceptibility remain elusive. Methods: By combining the GTEx and TCGA databases, the presence of ARL4C was examined in 33 various types of cancer. Immunohistochemistry and immunofluorescence staining techniques were utilized to confirm the expression of ARL4C in particular tumor tissues. Furthermore, the ESTIMATE algorithm and TIMER2.0 database were utilized to analyze the tumor microenvironment and immune infiltration associated with ARL4C. The TISCH platform facilitated the utilization of single-cell RNA-seq datasets for further analysis. ARL4C-related immune escape was investigated using the TISMO tool. Lastly, drug sensitivity analysis was conducted to assess the sensitivity of different types of tumors to compounds based on the varying levels of ARL4C expression. Results: The study found that ARL4C was highly expressed in 23 different types of cancer. Moreover, the presence of high ARL4C expression was found to be associated with a poor prognosis in BLCA, COAD, KIRP, LGG, and UCEC. Notably, ARL4C was also expressed in immune cells, and its high expression was found to be correlated with cancer immune activation. Most importantly, the drug sensitivity analysis revealed a positive correlation between ARL4C expression and the heightened sensitivity of tumors to Staurosporine, Midostaurin, and Nelarabine. Conclusion: The findings from our study indicate that the expression level of ARL4C may exert an influence on cancer development, prognosis, and susceptibility to immunotherapy drugs. In addition, the involvement of ARL4C in the tumor immune microenvironment has expanded the concept of ARL4C-targeted immunotherapy.

Gasdermins in sepsis

Sepsis is a hyper-heterogeneous syndrome in which the systemic inflammatory response persists throughout the course of the disease and the inflammatory and immune responses are dynamically altered at different pathogenic stages. Gasdermins (GSDMs) proteins are pore-forming executors in the membrane, subsequently mediating the release of pro-inflammatory mediators and inflammatory cell death. With the increasing research on GSDMs proteins and sepsis, it is believed that GSDMs protein are one of the most promising therapeutic targets in sepsis in the future. A more comprehensive and in-depth understanding of the functions of GSDMs proteins in sepsis is important to alleviate the multi-organ dysfunction and reduce sepsis-induced mortality. In this review, we focus on the function of GSDMs proteins, the molecular mechanism of GSDMs involved in sepsis, and the regulatory mechanism of GSDMs-mediated signaling pathways, aiming to provide novel ideas and therapeutic strategies for the diagnosis and treatment of sepsis.

Construction and Validation of a Reliable Disulfidptosis-Related LncRNAs Signature of the Subtype, Prognostic, and Immune Landscape in Colon Cancer

Disulfidptosis, a novel form of regulated cell death (RCD) associated with metabolism, represents a promising intervention target in cancer therapy. While abnormal lncRNA expression is associated with colon cancer development, the prognostic potential and biological characteristics of disulfidptosis-related lncRNAs (DRLs) remain unclear. Consequently, the research aimed to discover a novel indication of DRLs with significant prognostic implications, and to investigate their possible molecular role in the advancement of colon cancer. Here, we acquired RNA-seq data, pertinent clinical data, and genomic mutations of colon adenocarcinoma (COAD) from the TCGA database, and then DRLs were determined through Pearson correlation analysis. A total of 434 COAD patients were divided in to three subgroups through clustering analysis based on DRLs. By utilizing univariate Cox regression, the least absolute shrinkage and selection operator (LASSO) algorithm, and multivariate Cox regression analysis, we ultimately created a prognostic model consisting of four DRLs (AC007728.3, AP003555.1, ATP2B1.AS1, and NSMCE1.DT), and an external database was used to validate the prognostic features of the risk model. According to the Kaplan-Meier curve analysis, patients in the low-risk group exhibited a considerably superior survival time in comparison to those in the high-risk group. Enrichment analysis revealed a significant association between metabolic processes and the genes that were differentially expressed in the high- and low-risk groups. Additionally, significant differences in the tumor immune microenvironment landscape were observed, specifically pertaining to immune cells, function, and checkpoints. High-risk patients exhibited a low likelihood of immune evasion, as indicated by the Tumor Immune Dysfunction and Exclusion (TIDE) analysis. Patients who exhibit both a high risk and high Tumor Mutational Burden (TMB) experience the least amount of time for survival, whereas those belonging to the low-risk and low-TMB category demonstrate the most favorable prognosis. In addition, the risk groups determined by the 4-DRLs signature displayed distinct drug sensitivities. Finally, we confirmed the levels of expression for four DRLs through rt-qPCR in both tissue samples from colon cancer patients and cell lines. Taken together, the first 4-DRLs-based signature we proposed may serve for a hopeful instrument for forecasting the prognosis, immune landscape, and therapeutic responses in colon cancer patients, thereby facilitating optimal clinical decision-making.

Hub gene associated with prognosis in bladder cancer is a novel therapeutic target

Objective

Bladder cancer is a clinical and social conundrum due to its high incidence and recurrence rate. It is urgent to find new targets for the diagnosis and treatment of bladder cancer and improve the prognosis and survival rate of bladder cancer patients. We sought a prognosis-related gene, built related models of evaluated bladder cancer and identified the function of the hub gene in bladder cancer.

Methods

We downloaded the data of bladder cancer patients from the TCGA database, and used differentially expressed genes (DEGs), copy number variation (CNV) and survival analysis to scan the hub genes associated with prognosis in bladder cancer. Then, multi-factor cox regression was used to obtain the bladder cancer prognosis correlation model. Then, we analyzed the relationship between the expression of hub gene and immune microenvironment of bladder cancer. The relationship between the expression of hub gene and prognosis in bladder cancer patients was verified by immunohistochemistry. Cell proliferation assay and drug sensitivity test in vivo were used to verify the inhibition of bladder cancer by targeted inhibitors.

Results

In bladder cancer, we screened seven hub genes (ACLY, CNP, NKIRAS2, P3H4, PDIA6, VPS25 and XPO1) associated with survival. Moreover, the multifactor regression model constructed with hub gene can well distinguish the prognosis of bladder cancer. Hub gene is mostly associated with immune microenvironment. Immunohistochemical results basically confirmed the importance of XPO1 in bladder cancer. Selinexor (an inhibitor of XPO1) could effectively inhibit the proliferation of bladder cancer in the cell proliferation experiments by CCK-8 assays and it could suppress the growth of bladder cancer in mouse bladder cancer model.

Conclusions

In this study, a prognostic model with seven hub genes has provided great help for the prognosis prediction of bladder cancer patients. And XPO1 is an important target affecting the prognosis of bladder cancer, and inhibition of XPO1 can effectively inhibit bladder cancer proliferation and growth.

Molecular characteristics of microsatellite stable early-onset colorectal cancer as predictors of prognosis and immunotherapeutic response

The incidence of early-onset colorectal cancer (EO-CRC, in patients younger than 50) is increasing worldwide. The specific gene signatures in EO-CRC patients are largely unknown. Since EO-CRC with microsatellite instability is frequently associated with Lynch syndrome, we aimed to comprehensively characterize the tumor microenvironment (TME) and gene expression profiles of EO-CRC with microsatellite stable (MSS-EO-CRC). Here, we demonstrated that MSS-EO-CRC has a similar pattern of tumor-infiltrating immune cells, immunotherapeutic responses, consensus molecular subtypes, and prognosis as late-onset CRC with MSS (MSS-LO-CRC). 133 differential expressed genes were identified as unique gene signatures of MSS-EO-CRC. Moreover, we established a risk score, which was positively associated with PD-L1 expression and could reflect both the level of tumor-infiltrating immune cells and the prognosis of MSS-EO-CRC patients. Application of this score on the anti-PD-L1 treatment cohort demonstrated that the low-risk score group has significant therapeutic advantages and clinical benefits. In addition, candidate driver genes were identified in the different-sidedness of MSS-EO-CRC patients. Altogether, MSS-EO-CRC exhibits distinct molecular profiles that differ from MSS-LO-CRC even though they have a similar TME characterization and survival pattern. Our risk score appears to be robust enough to predict prognosis and immunotherapeutic response and therefore could help to optimize the treatment of MSS-EO-CRC.

Acidic urine is associated with poor prognosis in patients with bladder cancer undergoing radical cystectomy

Purpose

To assess the prognostic value of acidic urine (low urine pH) in patients with bladder cancer undergoing radical cystectomy.

Materials and methods

We reviewed patients enrolled in the Seoul National University Prospectively Enrolled Registry for Urothelial Cancer-Cystectomy (SUPER-UC-Cx) who underwent radical cystectomy for bladder cancer between March 2016 and December 2020 at the Seoul National University Hospital. During this period, 368 patients were registered in our database. To eliminate confounding factors, we excluded patients diagnosed with non-urothelial cancer and end-stage renal disease.

Results

A total of 351 patients with a mean age of 69.8 ± 10.5 years and median follow-up of 16.0 months were eligible for the analysis. The mean preoperative urine pH was 6.0. The patients were divided into low (pH ≤ 5.5) and high (pH≥6.0) urine pH groups for comparison. All clinicopathological features, including the tumor size, grade, and stage were comparable between the low and high urine pH groups. A Cox regression analysis was performed to assess the independent effect of acidic urine on patient survival. A multivariate analysis showed that high T stage (T3-4) (hazard ratio (HR) 5.18, P<0.001), decreased renal function (estimated glomerular filtration rate <60 mL/min/1.73 m²) (HR 2.29, P=0.003), and low urine pH (≤5.5) (HR 1.69, P=0.05) were associated with shortened recurrence-free survival (RFS). Regarding the overall survival (OS), high T stage (T3-4) (HR 7.15, P<0.001) and low urine pH (≤5.5) (HR 2.66, P=0.029) were significantly associated with shortened survival. A Kaplan–Meier analysis demonstrated that the acidic urine group showed shorter RFS (P=0.04) and OS (P=0.028) than the other groups.

Conclusions

Acidic urine was independently associated with reduced RFS and OS in patients with bladder cancer undergoing radical cystectomy. Acidic urine contributing to an acidic tumor environment may promote aggressive behavior in bladder cancer.

Gene Expression Monotonicity across Bladder Cancer Stages Informs on the Molecular Pathogenesis and Identifies a Prognostic Eight-Gene Signature

Despite advancements in molecular classification, tumor stage and grade still remain the most relevant prognosticators used by clinicians to decide on patient management. Here, we leverage publicly available data to characterize bladder cancer (BLCA)’s stage biology based on increased sample sizes, identify potential therapeutic targets, and extract putative biomarkers. A total of 1135 primary BLCA transcriptomes from 12 microarray studies were compiled in a meta-cohort and analyzed for monotonal alterations in pathway activities, gene expression, and co-expression patterns with increasing stage (Ta–T1–T2–T3–T4), starting from the non-malignant tumor-adjacent urothelium. The TCGA-2017 and IMvigor-210 RNA-Seq data were used to validate our findings. Wnt, MTORC1 signaling, and MYC activity were monotonically increased with increasing stage, while an opposite trend was detected for the catabolism of fatty acids, circadian clock genes, and the metabolism of heme. Co-expression network analysis highlighted stage- and cell-type-specific genes of potentially synergistic therapeutic value. An eight-gene signature, consisting of the genes AKAP7, ANLN, CBX7, CDC14B, ENO1, GTPBP4, MED19, and ZFP2, had independent prognostic value in both the discovery and validation sets. This novel eight-gene signature may increase the granularity of current risk-to-progression estimators.

In Silico Establishment and Validation of Novel Lipid Metabolism-Related Gene Signature in Bladder Cancer

Background

Aberrant lipid metabolism is an alteration common to many types of cancer. Dysregulation of lipid metabolism is considered a major risk factor for bladder cancer. Accordingly, we focused on genes related to lipid metabolism and screened novel markers for predicting the prognosis of bladder cancer.

Methods

RNA-seq data for bladder cancer were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The nonnegative matrix factorization (NMF) algorithm was used to classify the molecular subtypes. Weighted correlation network analysis (WGCNA) was applied to identify coexpressed genes, and least absolute shrinkage and selection operator (LASSO) multivariate Cox analysis was used to construct a prognostic risk model. External validation data and in vitro experiments were used to verify the results from in silico analysis.

Results

Bladder cancer samples were grouped into two clusters based on the NMF algorithm. A total of 1467 genes involved in coexpression modules were identified in WGCNA. We finally established a 5-gene signature (TM4SF1, KCNK5, FASN, IMPDH1, and KCNJ15) that exhibited good stability across different datasets and was also an independent risk factor for prognosis. Furthermore, the predictive efficacy of our model was generally higher than the predictive efficacy of other published models. Distinct risk groups of patients also showed significantly different immune infiltration cell patterns and associations with clinical variables. Moreover, the 5 signature genes were verified in clinical samples by quantitative real-time polymerase chain reaction (qRT-PCR) and immunohistochemistry, which were in agreement with the in silico analysis. For in vitro experiments, knockdown of IMPDH1 markedly inhibited cell proliferation in bladder cancer.

Conclusion

We established a 5-gene prognosis signature based on lipid metabolism in bladder cancer, which could be an effective prognostic indicator.

Single-Cell Sequencing Unveils the Heterogeneity of Nonimmune Cells in Chronic Apical Periodontitis

Chronic apical periodontitis (CAP) is a unique dynamic interaction between microbial invasions and host defense mechanisms, resulting in infiltration of immune cells, bone absorption, and periapical granuloma formation. To help to understand periapical tissue pathophysiology, we constituted a single-cell atlas for 26,737 high-quality cells from inflammatory periapical tissue and uncovered the complex cellular landscape. The eight types of cells, including nonimmune cells and immune cells, were identified in the periapical tissue of CAP. Considering the key roles of nonimmune cells in CAP, we emphasized osteo-like cells, basal/stromal cells, endothelial cells, and epithelial cells, and discovered their diversity and heterogeneity. The temporal profiling of genomic alterations from common CAP to typical periapical granuloma provided predictions for transcription factors and biological processes. Our study presented potential clues that the shift of inflammatory cytokines, chemokines, proteases, and growth factors initiated polymorphic cell differentiation, lymphangiogenesis, and angiogenesis during CAP.