Genes In Bladder Cancer Research Articles

Development and experimental validation of an M2 macrophage and platelet-associated gene signature to predict prognosis and immunotherapy sensitivity in bladder cancer.

Platelets and M2 macrophages both play crucial roles in tumorigenesis, but their relationship and the prognosis value of the relative genes in bladder cancer (BLCA) remain obscure. In the present study, we found that platelets stimulated by BLCA cell lines could promote M2 macrophage polarization, and platelets were significantly associated with the infiltration of M2 macrophages in BLCA samples. Through the bioinformatic analyses, A2M, TGFB3, and MYLK, which were associated with platelets and M2 macrophages, were identified and verified invitro and then included in the predictive model. A platelet and M2 macrophage-related gene signature was constructed to evaluate the prognosis and immunotherapeutic sensitivity, helping to guide personalized treatment and to disclose the underlying mechanisms.

Comprehensive analysis of mitochondria-related genes indicates that PPP2R2B is a novel biomarker and promotes the progression of bladder cancer via Wnt signaling pathway

Bladder cancer (BC) is the fourth and tenth most common malignancy in men and women worldwide, respectively. The complexity of the molecular biological mechanism behind BC is a major contributor to the lack of effective treatment management of the disease. The development and genesis of BC are influenced by mitochondrial retrograde control and mitochondria-nuclear cross-talk. However, the role of mitochondrial-related genes in BC remains unclear. In this study, we analyzed TCGA datasets and identified 752 DE-MRGs in BC samples, including 313 down-regulated MRGs and 439 up-regulated MRGs. Then, the results of machine-learning screened four critical diagnostic genes, including GLRX2, NMT1, PPP2R2B and TRAF3IP3. Moreover, we analyzed their prognostic value and confirmed that only PPP2R2B was associated with clinical prognosis of BC patients and Cox regression assays validated that PPP2R2B expression was a distinct predictor of overall survival in BC patients. Them, we performed RT-PCR and found that PPP2R2B expression was distinctly decreased in BC specimens and cell lines. Functional experiments revealed that overexpression of PPP2R2B distinctly suppressed the proliferation, migration and invasion of BC cells via Wnt signaling pathway. In summary, these research findings offer potential molecular markers for the diagnosis and prognosis of BC, with the discovery of PPP2R2B particularly holding significant biological and clinical significance. This study provides valuable clues for future in-depth investigations into the molecular mechanisms of BC, as well as the development of new diagnostic markers and therapeutic targets.

TFRC, associated with hypoxia and immune, is a prognostic factor and potential therapeutic target for bladder cancer

BackgroundBladder cancer is a common malignancy of the urinary system, and the survival rate and recurrence rate of patients with muscular aggressive (MIBC) bladder cancer are not ideal. Hypoxia is a pathological process in which cells acquire special characteristics to adapt to anoxic environment, which can directly affect the proliferation, invasion and immune response of bladder cancer cells. Understanding the exact effects of hypoxia and immune-related genes in BLCA is helpful for early assessment of the prognosis of BLCA. However, the prognostic model of BLCA based on hypoxia and immune-related genes has not been reported.PurposeHypoxia and immune cell have important role in the prognosis of bladder cancer (BLCA). The aim of this study was to investigate whether hypoxia and immune related genes could be a novel tools to predict the overall survival and immunotherapy of BLCA patients.MethodsFirst, we downloaded transcriptomic data and clinical information of BLCA patients from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. A combined hypoxia and immune signature was then constructed on the basis of the training cohort via least absolute shrinkage and selection operator (LASSO) analysis and validated in test cohort. Afterwards, Kaplan–Meier curves, univariate and multivariate Cox and subgroup analysis were employed to assess the accuracy of our signature. Immune cell infiltration, checkpoint and the Tumor Immune Dysfunction and Exclusion (TIDE) algorithm were used to investigate the immune environment and immunotherapy of BLCA patients. Furthermore, we confirmed the role of TFRC in bladder cancer cell lines T24 and UMUC-3 through cell experiments.ResultsA combined hypoxia and immune signature containing 8 genes were successfully established. High-risk group in both training and test cohorts had significantly poorer OS than low-risk group. Univariate and multivariate Cox analysis indicated our signature could be regarded as an independent prognostic factor. Different checkpoint was differently expressed between two groups, including CTLA4, HAVCR2, LAG3, PD-L1 and PDCD1. TIDE analysis indicated high-risk patients had poor response to immunotherapy and easier to have immune escape. The drug sensitivity analysis showed that high-risk group patients were more potentially sensitive to many drugs. Meanwhile, TFRC could inhibit the proliferation and invasion ability of T24 and UMUC-3 cells.ConclusionA combined hypoxia and immune-related gene could be a novel predictive model for OS and immunotherapy estimation of BLCA patients and TFRC could be used as a potential therapeutic target in the future.

Molecular map of cGAS-STING pathway-related genes in bladder cancer: the perspective toward immune microenvironment and prognosis.

The cGAS-STING pathway emerges as a pivotal innate immune pathway with the potential to profoundly influence all facets of tumor initiation and progression. The prognostic significance and immunological role of cGAS-STING pathway-related genes (CRGs) in individuals diagnosed with bladder cancer (BLCA) have not yet been fully elucidated. Performed unsupervised cluster analysis to identify distinct clusters. Utilizing LASSO and multivariate Cox regression analysis to construct a prognostic risk model. The IMvigor210, GSE13507 and GSE78220 cohorts were utilized to explore the potential value of risk score in immune therapy response and survival prediction. A risk model was developed utilizing four CRGs in order to forecast the overall survival (OS) of BLCA patients. The risk score to be a standalone risk factor, which was further corroborated by the external validation set obtained from the GEO database (GSE13507). We established an integrated nomogram that combined risk scoring and clinical information, exhibiting commendable clinical practicality in predicting the overall survival period of BLCA patients. It is noteworthy that risk score could differentiate tumor microenvironments among different risk groups and individuals who were more responsive to immunotherapy in IMvigor210 and GSE13507 cohorts. In vitro experiments, we noted an up-regulation of IRF3 and IKBKB upon the activation of the cGAS-STING pathway. Conversely, the activation of the cGAS-STING pathway resulted in a down-regulation of POLR3G and CTNNB1. CRG risk model shows promise as a potential stratification approach for bladder cancer patients.

Unraveling neoantigen-associated genes in bladder cancer: An in-depth analysis employing 101 machine learning algorithms.

The therapeutic outcomes for bladder cancer (BLCA) remain suboptimal. Concurrently, there is a growing appreciation for the role of neoantigens in tumors. In this study, we explored the mechanisms underlying the involvement of neoantigen-associated genes in BLCA and their impact on prognosis. Our analysis incorporated both single-cell sequencing and bulk sequencing data sourced from publicly available databases. By employing a comprehensive set of 10 machine learning algorithms, we generated 101 algorithm combinations. The optimal combination, determined based on consistency indices, was utilized to construct a prognostic model comprising nine genes (CAPG, ACTA2, PDIA6, AKNA, PTMS, SNAP23, ID2, CD3G, SP140). Subsequently, we validated this model in an independent cohort, demonstrating its robust testing efficacy. Moreover, we explored the correlations between various clinical traits, model scores, and genes. Leveraging extensive public data resources, we conducted a drug sensitivity analysis to provide insights for targeted drug screening. Additionally, consensus clustering analysis and immune infiltration analysis were performed on bulk sequencing datasets and immunotherapy cohorts. These analyses yield valuable insights into the role of neoantigens in BLCA, guiding future research endeavors.

CLIC3 interacts with NAT10 to inhibit N4-acetylcytidine modification of p21 mRNA and promote bladder cancer progression

Chromatin accessibility plays important roles in revealing the regulatory networks of gene expression, while its application in bladder cancer is yet to be fully elucidated. Chloride intracellular channel 3 (CLIC3) protein has been reported to be associated with the progression of some tumors, whereas the specific mechanism of CLIC3 in tumor remains unclear. Here, we screened for key genes in bladder cancer through the identification of transcription factor binding site clustered region (TFCR) on the basis of chromatin accessibility and TF motif. CLIC3 was identified by joint profiling of chromatin accessibility data with TCGA database. Clinically, CLIC3 expression was significantly elevated in bladder cancer and was negatively correlated with patient survival. CLIC3 promoted the proliferation of bladder cancer cells by reducing p21 expression in vitro and in vivo. Mechanistically, CLIC3 interacted with NAT10 and inhibited the function of NAT10, resulting in the downregulation of ac4C modification and stability of p21 mRNA. Overall, these findings uncover an novel mechanism of mRNA ac4C modification and CLIC3 may act as a potential therapeutic target for bladder cancer.

Computational Insights into Captopril's Inhibitory Potential Against MMP9 and LCN2 in Bladder Cancer: Implications for Therapeutic Application.

Captopril is a commonly used therapeutic agent in the management of renovascular hypertension (high blood pressure), congestive heart failure, left ventricular dysfunction following myocardial infarction, and nephropathy. Captopril has been found to interact with proteins that are significantly associated with bladder cancer (BLCA), suggesting that it could be a potential medication for BLCA patients with concurrent hypertension. DrugBank 5.0 was utilized to identify the direct protein targets (DPTs) of captopril. STRING was used to analyze the multiple protein interactions. TNMPlot was used for comparing gene expression in normal, tumor, and metastatic tissue. Then, docking with target proteins was done using Autodock. Molecular dynamics simulations were applied for estimate the diffusion coefficients and mean-square displacements in materials. Among all these proteins, MMP9 is observed to be an overexpressed gene in BLCA and its increased expression is linked to reduced survival in patients. Our findings indicate that captopril effectively inhibits both the wild type and common mutated forms of MMP9 in BLCA. Furthermore, the LCN2 gene, which is also overexpressed in BLCA, interacts with captopril-associated proteins. The overexpression of LCN2 is similarly associated with reduced survival in BLCA. Through molecular docking analysis, we have identified specific amino acid residues (Tyr179, Pro421, Tyr423, and Lys603) at the active pocket of MMP9, as well as Tyr78, Tyr106, Phe145, Lys147, and Lys156 at the active pocket of LCN2, with which captopril interacts. Thus, our data provide compelling evidence for the inhibitory potential of captopril against human proteins MMP9 and LCN2, both of which play crucial roles in BLCA. These discoveries present promising prospects for conducting subsequent validation studies both in vitro and in vivo, with the aim of assessing the suitability of captopril for treating BLCA patients, irrespective of their hypertension status, who exhibit elevated levels of MMP9 and LCN2 expression.

Exploration of the prognostic effect of costimulatory genes in bladder cancer.

A prognostic model of bladder cancer was constructed based on costimulatory molecules, and its stability and accuracy were verified in different datasets. The expression profile of bladder cancer RNA and the corresponding clinical data in The Cancer Genome Atlas (TCGA) database were analyzed employing computational biology, and a prognostic model was constructed for costimulating molecule-related genes. The model was applied in GSE160693, GSE176307, Xiangya_Cohort, GSE13507, GSE19423, GSE31684, GSE32894, GSE48075, GSE69795 and GSE70691 in TCGA dataset and Gene Expression Omnibus database. The role of costimulating molecules in bladder cancer tumor subtypes was also explored. By consistent cluster analysis, bladder cancer in the TCGA dataset was categorized into two subtypes: C1 and C2. The C1 subtype exhibited a poor prognosis, high levels of immune cell infiltration and significant enrichment of natural killer cells, T cells and dendritic cells in the C1 subtype. In addition, the ImmuneScore calculated by the ESTIMATE algorithm differed greatly between the two subtypes, and the ImmuneScore of the C1 subtype was greater than the C2 subtype in a significant manner. This study also assessed the relationship between costimulating molecules and immunotherapy response. The high-risk group responded poorly to immunotherapy, with significant differences in the amount of most immune cells between the two groups. Further, three indices of the ESTIMATE algorithm and 22 immune cells of the CIBERSORT algorithm were significantly correlated with risk values. These findings suggest the potential value of costimulating molecules in predicting immunotherapy response. A costimulatory molecule-based prognostic model for bladder cancer was established and validated across multiple datasets. This model introduces a novel mode for tailoring treatments to each individual with bladder cancer, and offers valuable insights for informed clinical choices. Simultaneously, this research also delved into the significance of costimulating molecules within distinct bladder cancer subtypes, shedding novel insights into improving immunotherapy strategies for the treatment of bladder cancer.

Establishment of a SUMO pathway related gene signature for predicting prognosis, chemotherapy response and investigating the role of EGR2 in bladder cancer.

Background: Bladder cancer is a prevalent malignancy with significant clinical implications. Small Ubiquitin-like Modifier (SUMO) pathway related genes (SPRG) have been implicated in the development and progression of cancer. Methods: In this study, we conducted a comprehensive analysis of SPRG in bladder cancer. We analyzed gene expression and prognostic value of SPRG and developed a SPRG signature (SPRGS) prognostic model based on four genes (HDAC4, TRIM27, EGR2, and UBE2I) in bladder cancer. Furthermore, we investigated the relationship between SPRGS and genomic alterations, tumor microenvironment, chemotherapy response, and immunotherapy. Additionally, we identified EGR2 as a key SPRG in bladder cancer. The expression of EGR2 in bladder cancer was detected by immunohistochemistry, and the cell function experiment clarified the effect of knocking down EGR2 on the proliferation, invasion, and migration of bladder cancer cells. Results: Our findings suggest that SPRGS hold promise as prognostic markers and predictive biomarkers for chemotherapy response and immunotherapy efficacy in bladder cancer. The SPRGS prognostic model exhibited high predictive accuracy for bladder cancer patient survival. We also observed correlations between SPRG and genomic alterations, tumor microenvironment, and response to chemotherapy. Immunohistochemical results showed that EGR2 was highly expressed in bladder cancer tissues, and its overexpression was associated with poor prognosis. Knockdown of EGR2 inhibited bladder cancer cell proliferation, invasion, and migration. Conclusion: This study provides valuable insights into the landscape of SPRGS in bladder cancer and their potential implications for personalized treatment strategies. The identification of EGR2 as a key SPRG and its functional impact on bladder cancer cells further highlights its significance in bladder cancer development and progression. Overall, SPRGS may serve as important prognostic markers and predictive biomarkers for bladder cancer patients, guiding treatment decisions and improving patient outcomes.

A new immune-related gene signature predicts the prognosis and immune escape of bladder cancer.

The biological roles of immune-related genes (IRGs) in bladder cancer (BC) need to be further elucidated. To elucidate the predictive value of IRGs for prognosis and immune escape in BC. We comprehensively analyzed the transcriptomic and clinical information of 430 cases, including 19 normal and 411 BC patients from the TCGA database, and verified 165 BC cases in the GSE13507 dataset. The risk model was constructed based on IRGs by applying LASSO Cox regression and exploring the relationship between the risk score and prognosis, gene mutations, and immune escape in BC patients. We identified 4 survival-related genes (PSMC1, RAC3, ROBO2 and ITGB3) among 6,196 IRGs in both the TCGA and GES13507 datasets,, which were used to establish a gene risk model by applying LASSO Cox regression. The results showed that the high-risk (HR) group was closely associated with poor survival or advanced pathological stage of BC. Furthermore, the risk score was found to be an independent risk factor for prognosis of BC patients. In addition, high-risk individuals showed a greater prevalence of TP53 mutations lower CD8+ T-cell and NK cell infiltration, higher Treg cell infiltration, higher expression of PD-L1, and higher immune exclusion scores than those in the low-risk (LR) group. Finally, the experimental verification shows that the model construction gene, especially PMSC1, plays an important role in the growth and metastasis of bladder cancer. These evidences revealed the vital role of IRGs in predicting prognosis, TP53 mutation and immune escape in BC patients.

Preliminary study on the role of the CSMD2 gene in bladder cancer

BackgroundCSMD2 has been reported as a potential prognostic factor in several cancers. However, whether CSMD2 affects bladder cancer (BC) remains unclear. MethodsPublic data were obtained from the TCGA (https://cancergenome.nih.gov) databases. CSMD2expression and its prognostic value were analyzed using bioinformatics methods. CSMD2 mRNA level in patients with BC and BC cell lines was evaluated via quantitative reverse transcriptase polymerase chain reaction. CSMD2 protein level in patients with BC was evaluated via immunohistochemistry. BC cell lines T24 and UMUC-3 were selected for loss-of-function assays targeting CSMD2. Cell viability was determined by CCK8 and clone formation experiments. Cell migration and invasion were evaluated using Transwell assays. Furthermore, the transcriptome of UMUC-3 with CSMD2 knockdown was sequenced to analyze potential signaling network pathways. Finally, the TIMER2.0 database was employed to identify the correlation between CSMD2 and immune cells in the tumor microenvironment. ResultsCSMD2 expression was up-regulated in BC tissues compared to adjacent tissues. High CSMD2 expression was associated with poor survival and could serve as an independent predictor for survival in patients with BC. Furthermore, down-regulation of CSMD2 notably restrained the viability, migration, and invasion abilities of T24 and UMUC-3 cells. Moreover, transcriptomic sequencing after CSMD2 knockdown in UMUC-3 cells revealed its involvement in the regulation of the malignant phenotype in BC. Finally, public databases suggest a connection between CSMD2 and immune cell infiltration in BC. ConclusionsThese findings suggest that CSMD2 may promote proliferation and tumorigenicity, and could represent a potential target for improving the prognosis of BC.

Clinical significance and immune landscape of angiogenesis-related genes in bladder cancer.

Angiogenesis is a major promotor of tumor progression and metastasis. Nevertheless, it is undetermined how angiogenesis-related genes (ARGs) influence bladder cancer. The profiles of bladder cancer gene expression were collected from the TCGA-BLCA cohort. The LASSO regression analysis was used to build an angiogenesis-related signature (ARG_score) with the prognostic ARGs. Verification analyses were conducted across the GSE48075 dataset to demonstrate the robustness of the signature. Differences between the two risk groups based on clinical outcomes, immune landscape, mutation status, chemotherapeutic effectiveness for anticancer drugs, and immunotherapy efficacy were analyzed. A nomogram was developed to improve the clinical efficacy of this predictive tool. The expression levels of model genes in normal bladder epithelial cell lines (SV-HUC-1) and bladder cancer cell lines (T24 and 5637) were detected by qRT-PCR assay. Four angiogenesis-associated gene signature was constructed based on the LASSO regression algorithm. The signature showed independent risk factors of overall survival for bladder cancer, validated using two external survival datasets. Additionally, we built a prognostic nomogram to improve the practicality of the ARG_score. High-risk individuals showed stronger immunocyte infiltration, immune-related functions, elevated expression of immune checkpoints, reduced TIDE score, and higher combined IPS-PD-1 and IPS-CTLA4 scores, suggesting a heightened responsiveness to immune checkpoint inhibitors. Furthermore, patients with low and high risk showed distinct responsiveness to anticancer drugs. The expression levels of 5 model genes (COL5A2, JAG1, MSX1, OLR1, and STC) were significantly increased in bladder cancer cell lines (T24 and 5637) compared with the normal bladder epithelial cell line SV-HUC-1. The model constructed based on ARGs may have wide application in predicting outcomes and therapeutic responses.

Bladder cancer gene expression prediction with explainable algorithms

Bladder cancer gene expression prediction with explainable algorithms

The Role of Longevity Assurance Homolog 2/Ceramide Synthase 2 in Bladder Cancer

The human CERS2 gene encodes a ceramide synthase enzyme, known as CERS2 (ceramide synthase 2). This protein is also known as LASS2 (LAG1 longevity assurance homolog 2) and TMSG1 (tumor metastasis-suppressor gene 1). Although previously described as a tumor suppressor for different types of cancer, such as prostate or liver cancer, it has also been observed to promote tumor growth in adenocarcinoma. In this review, we focus on the influence of CERS2 in bladder cancer (BC), approaching the existing literature about its structure and activity, as well as the miRNAs regulating its expression. From a mechanistic point of view, different explanations for the role of CERS2 as an antitumor protein have been proposed, including the production of long-chain ceramides, interaction with vacuolar ATPase, and its function as inhibitor of mitochondrial fission. In addition, we reviewed the literature specifically studying the expression of this gene in both BC and biopsy-derived tumor cell lines, complementing this with an analysis of public gene expression data and its association with disease progression. We also discuss the importance of CERS2 as a biomarker and the presence of CERS2 mRNA in extracellular vesicles isolated from urine.

Multi-omics analysis reveals critical metabolic regulators in bladder cancer.

The crosstalk between genomic alterations and metabolic dysregulation in bladder cancer is largely unknown. A deep understanding of the interactions between cancer drivers and cancer metabolic changes will provide novel opportunities for targeted therapeutic strategies. Three primary bladder cancer specimens with paired normal tissues or blood samples were subjected to whole-exome sequencing, DNA methylation array and whole-transcriptome sequencing by next-generation sequencing technology. We applied the methods to multi-omics data combining the Cancer Genome Atlas (TCGA) bladder cancer samples, including somatic mutation, DNA copy number, DNA methylation and gene expression profile for validation. We identified 34 mutated cancer driver genes in bladder cancer. KDM6A was the most significantly mutated cancer driver gene. Metabolicpathways were enriched in both differentially methylated regions (DMRs) and differentially expressed genes. Twenty-nine DMRs in the TSS200 region were highly correlated with the upregulation of gene expression, and 24 DMRs in the genome were highly correlated with the downregulation of gene expression. A total of 201 genes had highly correlated DNA methylation and expression. Thirty-four genes, including the known metabolic genes CXXC5, PRR5, ABCB8 and BAHD1, were further validated in the TCGA cohort. Multi-omics alterations identified two new candidate driver genes, WIPI2 and GFM2, that warrant future studies. This study provides a comprehensive and systematic analysis, focusing on identifying key regulatory factors that may lead to cancer metabolic heterogeneity. Further understanding and verification of the cancer genes driving metabolic reprogramming and their role in the progression of bladder cancer will help to identify new therapeutic targets.

A transcriptome study of p53-pathway related prognostic gene signature set in bladder cancer

p53 pathway is important in tumorigenesis. However, no study has been performed to specifically investigate the role of p53 pathway genes in bladder cancer (BLCA). In this study, transcriptomics data of muscle invasive bladder cancer patients (n = 411) from The Cancer Genome Atlas (TCGA) were investigated. Using the hallmark p53 pathway gene set, the Non-Negative Matrix factorization (NMF) analysis identified two subtypes (C1 and C2). Clinical, survival, and immunological analysis were done to validate distinct characteristics of the subtypes. Pathway enrichment analysis showed the subtype C1 with poor prognosis having enrichment in genes of the immunity related pathways, where C2 subtype with better prognosis being enriched in genes of the steroid synthesis and drug metabolism pathways. A signature gene set consisting of MDGA2, GNLY, GGT2, UGT2B4, DLX1, and DSC1 was created followed by a risk model. Their expressions were analyzed in RNA extracted from the blood and matched tumor tissues of BLCA patients (n = 10). DSC1 had significant difference of expression (p = 0.005) between the blood and tumor tissues in our BLCA samples. Contrary to the usual normal bladder tissue to blood ratio, DLX1 expression was lower (p = 0.02734) in tumor tissues than in blood. Being the first research of p53 pathway related signature gene set in bladder cancer, this study potentially has a substantial impact on the development of biomarkers for BLCA.

Development of a prognostic signature for immune-associated genes in bladder cancer and exploring potential drug findings.

Bladder cancer, predominantly affecting men, is a prevalent malignancy of the urinary system. Although platinum-based chemotherapy has demonstrated certain enhancements in overall survival when compared to surgery alone, the efficacy of treatments is impeded by the unfavorable side effects of conventional chemotherapy medications. Nonetheless, immunotherapy exhibits potential in the treatment of bladder cancer. To create an immune-associated prognostic signature for bladder cancer, bioinformatics analyses were performed utilizing The Cancer Genome Atlas (TCGA) database in this study. By identifying differential gene expressions between the high-risk and low-risk groups, a potential therapeutic drug was predicted using the Connectivity Map database. Subsequently, the impact of this drug on the growth of T24 cells was validated through MTT assay and 3D cell culture techniques. The signature included 1 immune-associated LncRNA (NR2F1-AS1) and 16 immune-associated mRNAs (DEFB133, RBP7, PDGFRA, CGB3, PDGFD, SCG2, ADCYAP1R1, OPRL1, PGR, PSMD1, TANK, PRDX1, ADIPOR2, S100A8, AHNAK, EGFR). Based on the assessment of risk scores, the patients were classified into cohorts of low-risk and high-risk individuals. The cohort with low risk demonstrated a considerably higher likelihood of survival in comparison to the group with high risk. Furthermore, variations in immune infiltration were noted among the two categories. Cephaeline, a possible medication, was discovered by analyzing variations in gene expression. It exhibited promise in suppressing the viability and growth of T24 bladder cancer cells. The novel predictive pattern allows for efficient categorization of patients with bladder cancer, enabling focused and rigorous treatment for those expected to have a worse prognosis. The discovery of a possible curative medication establishes a basis for forthcoming immunotherapy trials in bladder cancer.

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

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. 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. 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. 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.

The Value of Epidermal Growth Factor Receptor Expression in Predicting Aggressive Behaviors of Bladder Neoplasms

Background: It has been shown that some cancers express the epidermal growth factor receptor (EGFR). Several variables influence bladder cancer prognosis, including stage, grade, and gene expression. Objectives: We used immunohistochemistry to measure the prevalence and prognostic significance of EGFR expression in bladder tumors in our population. Methods: Thirty bladder tumors were the subjects of this cross-sectional study. To evaluate the biological behavior of the tumors, histopathological analysis was performed. We carried out EGFR immunohistochemical staining to evaluate gene expression. Results: EGFR was expressed in 25 (83.3%) patients. Expression of this biomarker was independent of tumor characteristics such as lymphatic invasion, muscle invasion, and tumor grade and stage (P value > 0.05). Conclusions: Remembering each patient's tumor characteristics determine that prognosis is crucial. The prognostic value of EGFR expression in predicting aggressive behavior in bladder tumors is marginal, but it is necessary to evaluate therapeutic response.

Integrating Bulk and Single-Cell RNA Sequencing Reveals Heterogeneity, Tumor Microenvironment, and Immunotherapeutic Efficacy Based on Sialylation-Related Genes in Bladder Cancer.

As known abnormal sialylation exerts crucial roles in the growth, metastasis, and immune evasion of cancers, but the molecular characteristics and roles in bladder cancer (BLCA) remain unclear. This study intends to establish BLCA risk stratification based on sialylation-related genes and elucidate its role in prognosis, tumor microenvironment, and immunotherapy of BLCA. Bulk RNA-seq and scRNA-seq data were downloaded from open-access databases. The scRNA-seq data were processed using the R package "Seurat" to identify the core cell types. The tumor sub-typing of BLCA samples was performed by the R package "ConsensusClusterPlus" in the bulk RNA-seq data. Signature genes were identified by the R package "limma" and univariate regression analysis to calculate risk scores using the R package "GSVA" and establish risk stratification of BLCA patients. Finally, the differences in clinicopathological characteristics, tumor microenvironment, and immunotherapy efficacy between the different groups were investigated. 5 core cell types were identified in the scRNA-seq dataset, with monocytes and macrophages presenting the greatest percentage, sialylation-related gene expression, and sialylation scores. The bulk RNA-seq samples were classified into 3 tumor subtypes based on 19 prognosis-related sialylation genes. The 10 differential expressed genes (DEGs) with the smallest p-values were collected as signature genes, and the risk score was calculated, with the samples divided into high and low-risk score groups. The results showed that patients in the high-risk score group exhibited worse survival outcomes, higher tumor grade, more advanced stage, more frequency of gene mutations, higher expression levels of immune checkpoints, and lower immunotherapy response. We established a novel risk stratification of BLCA from a glycomics perspective, which demonstrated good accuracy in determining the prognostic outcome, clinicopathological characteristics, immune microenvironment, and immunotherapy efficacy of patients, and we are proposing to apply it to direct the choice of clinical treatment options for patients.