Genes In Bladder Cancer Research Articles

WD repeat protein 54-mediator of ErbB2-driven cell motility 1 axis promotes bladder cancer tumorigenesis and metastasis and impairs chemosensitivity

One of the most abundant protein-protein interaction domains in the human proteome is the WD40 repeat (WDR) domain. A Gene Expression Omnibus dataset revealed 37 differentially expressed WDR domain genes in bladder cancer (BC). WD repeat domain 54 (WDR54), an upregulated WDR domain gene, was selected for further investigation. Sixty pairs of frozen BC tumor and non-malignant bladder tissues and 83 paraffin-embedded BC tissue specimens were obtained. Loss-/gain-of-function experiments were carried out using BC and xenograft tumor models. WDR54 was overexpressed in BC cells, and its high expression was linked to tumor stage and lymph node metastases in patients. WDR54 contributed to the tumorigenesis and metastasis of BC and impaired its chemosensitivity. WDR54 prevented the degradation and ubiquitination of the mediator of ErbB2-driven cell motility 1 (MEMO1). WDR54 also promoted the interaction between MEMO1 and insulin receptor substrate 1 (IRS1) and activated the IRS1/AKT/β-catenin pathway in BC cells. Particularly, WDR54 depended on MEMO1 to exert its biological functions. Our study demonstrated the relevance of WDR54 in BC and provides insight into the molecular mechanism underlying BC.

Prognosis Prediction of Disulfidptosis-Related Genes in Bladder Cancer and a Comprehensive Analysis of Immunotherapy.

As a newly discovered mechanism of cell death, disulfidptosis is expected to help diagnose and treat bladder cancer patients. First, data obtained from public databases were analyzed using bioinformatics techniques. SVA packages were used to combine data from different databases to remove batch effects. Then, the differential analysis and COX regression analysis of ten disulfidptosis-related genes identified four prognostically relevant differentially expressed genes which were subjected to Lasso regression for further screening to obtain model-related genes and output model formulas. The predictive power of the prognostic model was verified and the immunohistochemistry of model-related genes was verified in the HPA database. Pathway enrichment analysis was performed to identify the mechanism of bladder cancer development and progression. The tumor microenvironment and immune cell infiltration of bladder cancer patients with different risk scores were analyzed to personalize treatment. Then, information from the IMvigor210 database was used to predict the responsiveness of different risk patients to immunotherapy. The oncoPredict package was used to predict the sensitivity of patients at different risk to chemotherapy drugs, and its results have some reference value for guiding clinical use. After confirming that our model could reliably predict the prognosis of bladder cancer patients, the risk scores were combined with clinical information to create a nomogram to accurately calculate the patient survival rate. A prognostic model containing three disulfidptosis-related genes (NDUFA11, RPN1, SLC3A2) was constructed. The functional enrichment analysis and immune-related analysis indicated patients in the high-risk group were candidates for immunotherapy. The results of drug susceptibility analysis can guide more accurate treatment for bladder cancer patients and the nomogram can accurately predict patient survival. NDUFA11, RPN1, and SLC3A2 are potential novel biomarkers for the diagnosis and treatment of bladder cancer. The comprehensive analysis of tumor immune profiles indicated that patients in the high-risk group are expected to benefit from immunotherapy.

Reliable prognostic definition and immunotherapy response prediction in bladder cancer, based on a novel aging-associated 5-gene signature model.

Bladder cancer (BC) is a urological tumor which can be associated with a poor prognosis. Aging is a crucial factor in cancer development, but the role and prognostic value of aging-related genes (ARGs) in BC are unclear. In this study, with reference to The Cancer Genome Atlas (TCGA) database, a 5-gene signature model was constructed for the analysis of BC prognosis, immune microenvironment, and immunotherapy response. Least absolute shrinkage and selection operator (LASSO) and univariate Cox regression analyses were applied. There was significant heterogeneity in the genetic variation and expression profiles of ARGs in BC. Striking variations were revealed in survival outcomes between high- and low-risk groups by Kaplan-Meier curves. The majority of samples of cases in the high-risk group belonged to the middle and late stage of the tumor and had a higher abundance of immune infiltration and immune checkpoint expression, and better immunotherapeutic effects. The risk score model of ARGs achieved more satisfactory results in the prediction of prognosis, clinical characteristics, immune infiltration, tumor mutational load, and immunotherapy in BC patients with good stability and reproducibility, offering innovative approaches and orientations for the diagnosis and treatment of patients with BC in the future.

Investigation of the mutational status of the FGFR3 gene in urothelial bladder carcinoma

To study the somatic mutational status of the FGFR3 gene in urothelial bladder cancer (BC) and evaluate its relationship with the clinical and morphological characteristics of the tumor, deficiency of the DNA mismatch repair (dMMR), PD-L1 tumor status, and immunohistochemical (IHC) expression of the p16 protein. Surgical material of 40 patients with BC, on which the mutational status of the FGFR3 gene was studied using the molecular genetic method, as well as the MMR status, PD-L1 and p16 expression by the IHC method. FGFR3 mutations, such as G370C, S249C, S371C/Y373C, R248C, were detected in 35.0% of the studied BC samples. FGFR3 status did not depend on the gender and age of patients, as well as on the degree of tumor lymphoid infiltration (TILs). Statistically significant differences were found in the analysis of FGFR3 status depending on the histological structure and degree of tumor differentiation, as well as on the pT stage. The FGFR3 status of BC was not associated with the IHC expression of the studied proteins of the MMR system, as well as with the PD-L1 status. Higher levels of PD-L1 expression were demonstrated by BC tumor cells, in which no aberrations in FGFR3 were detected. There was no significant association between p16 status and the presence of FGFR3 mutations, but for FGFR3-positive carcinomas, the basal pattern of p16 staining by IHC was noted. A positive somatic mutational status of the FGFR3 gene was statistically significantly more common in the group of papillary low-grade non-muscle-invasive BC, demonstrating basal p16 IHC staining. In the study sample, there was no statistically significant relationship between the FGFR3 status of BC and gender and age differences, TILs, MMR status, PD-L1 status (SP142 and 22C3), and p16 status. The results of the study indicate the need to determine the FGFR3 status in patients with BC for further prescription of personalized therapy.

Notch signaling pathway-based classification of bladder cancer in relation to tumor immune infiltration.

The role of the Notch signaling pathway in the development of various tumors has received increasing attention, but the relationship between the Notch signaling pathway and the prognosis of bladder cancer has rarely been studied. The aim of this study was to investigate the function and risk evaluation value of Notch signaling pathway-related genes (NRGs) in bladder cancer. The list of genes related to the Notch signaling pathway was obtained from the molecular signature database. The bladder cancer dataset was obtained from The Cancer Genome Atlas (TCGA) database. Cox regression analysis and Lasso regression analysis were used to construct the characteristics for predicting the overall survival of patients with bladder cancer. The CIBERSORT algorithm was used to evaluate the infiltration of peripheral immune cells in different risk subgroups. NRG expression was remarkably dysregulated in bladder cancer. Next, bladder cancer was classified into two subtypes (C1 and C2) based on NRG expression levels. The two subtypes had a significant difference in prognosis and were closely related to clinical characteristics. Further analysis showed that immune cell infiltration and immune scores were also significantly different between the two subtypes. Notch signaling pathway-based bladder cancer typing has different prognoses and may be related to tumor immunity. NRGs can be identified for risk evaluation and help improve clinical decision-making.

Identifying stage-associated hub genes in bladder cancer via weighted gene co-expression network and robust rank aggregation analyses.

Bladder cancer (BC) is among the most frequent cancers globally. Although substantial efforts have been put to understand its pathogenesis, its underlying molecular mechanisms have not been fully elucidated. The robust rank aggregation approach was adopted to integrate 4 eligible bladder urothelial carcinoma microarray datasets from the Gene Expression Omnibus. Differentially expressed gene sets were identified between tumor samples and equivalent healthy samples. We constructed gene co-expression networks using weighted gene co-expression network to explore the alleged relationship between BC clinical characteristics and gene sets, as well as to identify hub genes. We also incorporated the weighted gene co-expression network and robust rank aggregation to screen differentially expressed genes. CDH11, COL6A3, EDNRA, and SERPINF1 were selected from the key module and validated. Based on the results, significant downregulation of the hub genes occurred during the early stages of BC. Moreover, receiver operating characteristics curves and Kaplan-Meier plots showed that the genes exhibited favorable diagnostic and prognostic value for BC. Based on gene set enrichment analysis for single hub gene, all the genes were closely linked to BC cell proliferation. These results offer unique insight into the pathogenesis of BC and recognize CDH11, COL6A3, EDNRA, and SERPINF1 as potential biomarkers with diagnostic and prognostic roles in BC.

Construction and experimental validation of a B cell senescence-related gene signature to evaluate prognosis and immunotherapeutic sensitivity in bladder cancer.

Senescent B cells exhibit reduced antibody production and enhanced proinflammatory cytokine and chemokine secretion, exerting non-negligible functions in antitumor immunity. This study aims to clarify the prognosis value of B cell senescence-related genes in bladder cancer (BLCA). Twelve B cell senescence-related genes were identified based on previous studies and the single-cell RNA sequencing of a BLCA sample from Gene Expression Omnibus (GEO). The Cancer Genome Atlas BLCA cohort was used as the training dataset. Three cohorts from GEO, 35 clinical samples from the local hospital, and in vitro cell experiments were used for validation. The unsupervised clustering based on the 12 genes was associated with the prognosis and the tumor immunity. Through least absolute shrinkage and selection operator regression and random forest algorithm, G protein subunit gamma 11 (GNG11) and inhibitor of DNA binding 1 (ID1) of the 12 genes were determined as significant prognosis predictors and then included in the multivariate Cox regression model. The model was a reliable and robust prognosis biomarker across multiple large-scale cohorts (pooled HR = 1.76, 95% CI = 1.41-2.20). The tight association between the model and BLCA malignant degree was demonstrated in the local cohort (P < 0.01). The model could also predict the immunotherapeutic sensitivity, which was confirmed by the tumor immune dysfunction and exclusion algorithm (P < 0.0001) and IMvigor210 cohort (P < 0.0001). At last, in vitro cell experiments in IM-9 and GM12878 B cells indicated that GNG11 and ID1 were involved in the cellular aging process. Collectively, a B cell senescence-related gene signature was constructed to evaluate the prognosis and immunotherapeutic response in BLCA, providing novel insights into the biological mechanisms.

Construction of Pyroptosis-Related Prognostic and Immune Infiltration Signature in Bladder Cancer.

Pyroptosis is a kind of programmed cell death related to inflammation, which is closely related to cancer. The goal of this study is to establish and verify pyroptosis-related gene signature to predict the prognosis of patients with bladder cancer (BLCA) and explore its relationship with immunity. Somatic mutation, copy number variation, correlation, and expression of 33 pyroptosis-related genes were evaluated based on The Cancer Genome Atlas (TCGA) database. BLCA cases were divided into two clusters by consistent clustering and found that pyroptosis-related genes were related to the overall survival (OS) of BLCA. The least absolute shrinkage and selection operator (LASSO) Cox regression was used to construct the signature (including 7 pyroptosis-realated genes). Survival analysis curve and receiver operating characteristic curve (ROC) showed that this signature could predict the prognosis of BLCA patients. Univariate and multivariate Cox regression analysis showed the independent prognostic value of this model. Immune infiltration analysis showed that the six types of immune cells have significantly different infiltrations. The effect of immunotherapy is better in the low-risk group. In summary, our effort indicated the potential role of pyroptosis-related genes in BLCA and provided new perspectives on the prognosis of BLCA and new ideas for immunotherapy.

Bioinformatics analysis of prognosis and immune microenvironment of immunological cell death-related gemcitabine-resistance genes in bladder cancer.

Bladder cancer (BC) is the most common malignant tumor of the urinary system. Gemcitabine resistance partly accounts for treatment failure and recurrence in BC. Immunological cell death (ICD) is correlated with chemoresistance. The prognosis of patients with similar tumor stage still varies in response to chemotherapy, recurrence, and disease progression. Therefore, our study aimed to provide a prognostic model based on ICD-related and gemcitabine-resistance genes for BC. The data of BC patients were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs), and differentially expressed gemcitabine resistance-related genes (DEGRRGs) were identified using the edgeR package. The survival-associated DEGRRGs were identified by univariate Cox analysis. A prognostic model was established by univariate Cox regression analysis and validated by GEO dataset. The outcome of low-risk group and high-risk group was analyzed by the Kaplan-Meier curve. The relationship between risk score and immune cell infiltration was investigated using the TIMER online database. The prognosis of patients in the ICD-high group was significantly better than ICD-low group. A prognostic model containing 5 gemcitabine resistance-related ICD-associated genes, including PTPRR, HOXB3, SIGLEC15, UNC5CL, and CASQ1, was established. In both TCGA prognostic model and GEO validation model, patients in the low-risk group had better outcomes than high-risk group. According to the receiver operating characteristic (ROC) curves, the risk score area under ROC curve (AUC) of the TCGA prognostic model were calculated to be 0.705, while the risk score of the GEO validation model were calculated to be 0.716. Patients in the high-risk group had a significantly higher immune score, stromal score, and infiltration of M0 macrophages, M1 macrophages, M2 macrophages, and activated CD4+ T cells. Patients in the high-risk group had significantly lower infiltration of the regulatory T cells, resting dendritic cell (DCs), and activated DCs. The present study highlighted the functional role of gemcitabine resistance-related ICD-associated genes, constructed a prognostic score for the outcome evaluation and searched for potential targets to overcome gemcitabine chemoresistance in BC.

Bioinformatics analysis of the correlation between m6A RNA methylation regulators and the immune infiltration and prognosis of bladder cancer.

To analyze the effect of N6-methyladenosine (m6A) RNA methylation regulators on the immune infiltration and prognosis of bladder cancer (BC). We explored the related signaling pathways and prognosis-related genes to provide candidate targets for the treatment and prognostic evaluation of BC. After downloading BC data from The Cancer Genome Atlas (TCGA) database, the expressions of m6A-related genes were obtained. We then performed correlation and sample cluster analysis of the m6A methylation regulator genes as well as difference comparison and survival analysis for the clustered patients using R software. Gene set enrichment analysis (GSEA) was carried out on cluster-grouped samples. Finally, the prognosis-related genes of BC among the m6A methylation regulators were screened. Genomic alterations in the m6A regulators were linked to a poor BC prognosis. HNRNPA2B1, HNRNPC, IGF2BP2, RBM15, YTHDF1, and YTHDF2 were found to be associated with advanced clinical stages of BC. Furthermore, the current study revealed that the levels of the m6A regulators were related to the expression levels and immune infiltration levels of immune regulators [immunosuppressive factors, immunostimulators, and major histocompatibility complex (MHC) molecules] in BC. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses suggested that in addition to the relevant immune responses, m6A regulators were involved in the poor prognosis of BC via their participation in blood vessels through regulatory RNA binding, telomeric DNA binding, microRNA (miRNA) binding, negative regulation of messenger RNA (mRNA) processing, negative regulation of DNA biosynthesis, branches of morphogenesis, positive regulation of the Notch receptor target gene transcription, etc. The expression of m6A RNA methylation regulators is closely linked to immune infiltration and prognosis in BC. Thus, it can be utilized as a potential molecular target for the treatment and prognostic assessment of BC.

A novel prognostic model based on cellular senescence-related gene signature for bladder cancer.

Cellular senescence plays crucial role in the progression of tumors. However, the expression patterns and clinical significance of cellular senescence-related genes in bladder cancer (BCa) are still not clearly clarified. This study aimed to establish a prognosis model based on senescence-related genes in BCa. The transcriptional profile data and clinical information of BCa were downloaded from TCGA and GEO databases. The least absolute shrinkage and selection operator (LASSO), univariate and multivariate Cox regression analyses were performed to develop a prognostic model in the TCGA cohort. The GSE13507 cohort were used for validation. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and single-sample gene set enrichment analysis (ssGSEA) were performed to investigate underlying mechanisms. A six-gene signature (CBX7, EPHA3, STK40, TGFB1I1, SREBF1, MYC) was constructed in the TCGA databases. Patients were classified into high risk and low risk group in terms of the median risk score. Survival analysis revealed that patients in the higher risk group presented significantly worse prognosis. Receiver operating characteristic (ROC) curve analysis verified the moderate predictive power of the risk model based on the six senescence-related genes signature. Further analysis indicated that the clinicopathological features analysis were significantly different between the two risk groups. As expected, the signature presented prognostic significance in the GSE13507 cohort. Functional analysis indicated that immune-related pathways activity, immune cell infiltration and immune-related function were different between two risk groups. In addition, risk score were positively correlated with multiple immunotherapy biomarkers. Our study revealed that a novel model based on senescence-related genes could serve as a reliable predictor of survival for patients with BCa.

The tumor microenvironment and prognostic role of autophagy- and immune-related genes in bladder cancer.

Autophagy-related genes and immune-related genes contribute significantly to the initiation and prognosis of bladder cancer (BLCA). We aimed to explore differentially expressed autophagy-related genes (DEARGs) and immune-related genes (DEIRGs) in BLCA to create a prognostic risk assessment model and gain some insights into BLCA's molecular underpinnings. The prognostic DEARGs and DEIRGs were evaluated for BLCA through The Cancer Genome Atlas (TCGA) database (n= 399) and GSE13507 dataset (n= 165). The BLCA risk model was constructed and verified. The immune score, stromal score, and estimate score in different risk groups were calculated by the ESTIMATE algorithm. Immune infiltration levels were assessed by a single sample gene set enrichment analysis (GSEA) algorithm. In the risk model, AURKA, ACTC1, MYLK, PDGFD, PDGFRA and TNC were significantly associated with the overall survival. The pathways in cancer, T cell receptor signaling pathway and B cell receptor signaling pathway were significantly gathered in the high-risk group. Moreover, the risk score was significantly correlated with infiltrating immune cells, expression of critical immune checkpoints and mismatch repair genes including MSH6, MLH1, and MSH2. In this study, three DEARGs (AURKA, ACTC1, MYLK) and three DEIRGs (PDGFD, PDGFRA, TNC) were demonstrated to be potential prognostic biomarkers for BLCA patients through bioinformatics methods, which might be novel therapeutic targets and prognostic markers for BLCA, in follow up studies, we will combine experiments to verify this.

Impact of SOX2 function and regulation on therapy resistance in bladder cancer.

Bladder cancer (BC) is a malignant disease with high rates of recurrence and mortality. It is mainly classified as non-muscle-invasive BC and muscle-invasive BC (MIBC). Often, MIBC is chemoresistant, which, according to cancer stem cells (CSCs) theory, is linked to the presence of bladder cancer stem cells (BCSCs). Sex-determining region Y- (SRY) Box transcription factor 2 (SOX2), which is a molecular marker of BCSCs, is aberrantly over-expressed in chemoresistant BC cell lines. It is one of the standalone prognostic factors for BC, and it has an inherently significant function in the emergence and progression of the disease. This review first summarizes the role of SRY-related high-mobility group protein Box (SOX) family genes in BC, focusing on the SOX2 and its significance in BC. Second, it discusses the mechanisms relevant to the regulation of SOX2. Finally, it summarizes the signaling pathways related to SOX2 in BC, suggests current issues to be addressed, and proposes potential directions for future research to provide new insights for the treatment of BC.

The targets of aspirin in bladder cancer: bioinformatics analysis

BackgroundThe anti-carcinogenic properties of aspirin have been observed in some solid tumors. However, the molecular mechanism of therapeutic effects of aspirin on bladder cancer is still indistinct. We introduced a bioinformatics analysis approach, to explore the targets of aspirin in bladder cancer (BC).MethodsTo find out the potential targets of aspirin in BC, we analyzed direct protein targets (DPTs) of aspirin in Drug Bank 5.0. The protein-protein interaction (PPI) network and signaling pathway of aspirin DPTs were then analyzed subsequently. A detailed analysis of the KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway has shown that aspirin is linked to BC. We identified overexpressed genes in BC comparing with normal samples by Oncomine and genes that interlinked with aspirin target genes in BC by STRING.ResultsFirstly, we explored 16 direct protein targets (DPT) of aspirin. We analyzed the protein-protein interaction (PPI) network and signaling pathways of aspirin DPT. We found that aspirin is closely associated with a variety of cancers, including BC. Then, we classified mutations in 3 aspirin DPTs (CCND1, MYC and TP53) in BC using the cBio Portal database. In addition, we extracted the top 50 overexpressed genes in bladder cancer by Oncomine and predicted the genes associated with the 3 aspirin DPTs (CCND1, MYC and TP53) in BC by STRING. Finally, 5 exact genes were identified as potential therapeutic targets of aspirin in bladder cancer.ConclusionThe analysis of relevant databases will improve our mechanistic understanding of the role of aspirin in bladder cancer. This will guide the direction of our next drug-disease interaction studies.

Deep learning approach for cancer subtype classification using high-dimensional gene expression data

MotivationStudies have shown that classifying cancer subtypes can provide valuable information for a range of cancer research, from aetiology and tumour biology to prognosis and personalized treatment. Current methods usually adopt gene expression data to perform cancer subtype classification. However, cancer samples are scarce, and the high-dimensional features of their gene expression data are too sparse to allow most methods to achieve desirable classification results.ResultsIn this paper, we propose a deep learning approach by combining a convolutional neural network (CNN) and bidirectional gated recurrent unit (BiGRU): our approach, DCGN, aims to achieve nonlinear dimensionality reduction and learn features to eliminate irrelevant factors in gene expression data. Specifically, DCGN first uses the synthetic minority oversampling technique algorithm to equalize data. The CNN can handle high-dimensional data without stress and extract important local features, and the BiGRU can analyse deep features and retain their important information; the DCGN captures key features by combining both neural networks to overcome the challenges of small sample sizes and sparse, high-dimensional features. In the experiments, we compared the DCGN to seven other cancer subtype classification methods using breast and bladder cancer gene expression datasets. The experimental results show that the DCGN performs better than the other seven methods and can provide more satisfactory classification results.

CD8A as a Prognostic and Immunotherapy Predictive Biomarker Can Be Evaluated by MRI Radiomics Features in Bladder Cancer.

Simple SummaryIt is necessary to explore a reliable predictive biomarker for immunotherapeutic strategies in bladder cancer. As an important member of tumor-infiltrating immune cells, cytotoxic T cells are the ultimate effectors of cancer rejection because of their specificity against cancer cells and cytolytic capabilities. Based on RNA expression data, we found that among T cytotoxic pathway-related genes, CD8A is a novel protective gene in bladder cancer. CD8A expression is highly associated with tumor microenvironment characteristics and tumor mutation burden, which partially explain CD8A as a prognostic and immunotherapy predictive biomarker in bladder cancer. In addition, we performed the radiogenomics in bladder cancer based on the RNA-sequence data and MRI-based radiomics features in our center. In this way, an MRI-based radiomics signature has the potential to preoperatively predict the expression of CD8A, thereby contributing to the preoperative prediction of prognosis and immunotherapeutic susceptibility in bladder cancer.As an important member of T cytotoxic pathway-related genes, CD8a molecule (CD8A) may be a useful biomarker of immunotherapeutic response and immune cell infiltration. We aimed to investigate the clinical predictive value of CD8A in prognosis and tumor microenvironment (TME) and preoperatively predict the expression of CD8A using radiogenomics in bladder cancer (BCa). Among 12 T cytotoxic pathway-related genes, CD8A was a novel protective gene and had the highest correlations with T cells and Macrophages M1 in BCa. In advanced cancer patients treated with immunotherapy, low CD8A expression was associated with immunotherapeutic failure and poor survival outcomes. CD8A expression was highly related to tumor mutation burden, critical immune checkpoint genes and several types of tumor-infiltrating immune cells, predicting effective response to immunotherapy. The preoperative MRI radiomics features and RNA-sequence data of 111 BCa samples were used to develop a radiomics signature that achieved good performance in the prediction of CD8A expression in both the training (area under curve (AUC): 0.857) and validation sets (AUC: 0.844). CD8A is a novel indicator for predicting the prognosis and immunotherapeutic response in BCa. A radiomics signature has the potential to preoperatively predict the expression of CD8A in BCa patients.

A novel prognostic model based on three integrin subunit genes-related signature for bladder cancer.

BackgroundPresently, a comprehensive analysis of integrin subunit genes (ITGs) in bladder cancer (BLCA) is absent. This study endeavored to thoroughly analyze the utility of ITGs in BLCA through computer algorithm-based bioinformatics.MethodsBLCA-related materials were sourced from reputable databases, The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). R software-based bioinformatics analyses included limma-differential expression analysis, survival-Cox analysis, glmnet-Least absolute shrinkage and selection operator (LASSO), clusterProfiler-functional annotation, and gsva-estimate-immune landscape analysis. The expression difference of key genes was verified by quantitative real-time polymerase chain reaction (qRT-PCR).ResultsAmong the 11 ITGs that were abnormally expressed in BLCA, ITGA7, ITGA5, and ITGB6 were categorized as the optimal variables for structuring the risk model. The high-risk subcategories were typified by brief survival, abysmal prognosis, prominent immune and stromal markers, and depressed tumor purity. The risk model was also an isolated indicator of the impact of clinical outcomes in BLCA patients. Moreover, the risk model, specifically the high-risk subcategory with inferior prognosis, became heavily interlinked with the immune-inflammatory response and smooth muscle contraction and relaxation.ConclusionThis study determined three ITGs with prognostic values (ITGA7, ITGA5, and ITGB6), composed a novel (ITG-associated) prognostic gene signature, and preliminarily probed the latent molecular mechanisms of the model.

Comprehensive analysis of alternative polyadenylation regulators concerning CD276 and immune infiltration in bladder cancer

Alternative polyadenylation (APA) is emerging as a crucial regulatory mechanism in bladder cancer (BC), while it remains elusive whether APA influences the tumor immune microenvironment (TIME) in BC. We identified two distinct subtypes of BC by APA-related regulatory genes expression profiles. The two subtypes have different pathological grades, prognostic outcomes, tumor immune infiltration characteristics, and pathway enrichment. Subsequently, CPSF3 was identified as a potential immune infiltration-related gene in BC. Highly expressed CPSF3 was positively correlated with unfavorable prognosis and high CD276 expression in BC. Moreover, we verified the expression of CPSF3 in BC tissues and cell lines by qRT-PCR. In conclusion, the study indicates that APA regulatory factors play an important role in immune infiltration of BC, and that CPSF3 was a potentially prognostic marker and immunotherapy target for BC.

Identification of stemness index-related long noncoding RNA SNHG12 in human bladder cancer based on WGCNA

BackgroundCancer stem cells (CSCs) have an key role in the beginning, progression and treatment of bladder cancer. In the current study, our target was to identify CSCS-related genes in bladder cancer. MethodsBladder cancer (BLCA) transcriptome data were acquired from The Cancer Genome Atlas (TCGA) database. WGCNA was used to screen genes connected with the mRNA expression-based stemness index (mRNAsi).Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were used to analyze the biological function of mRNAsi-related genes. Univariate Cox regression and LASSO Cox regression algorithms were applied to build a risk score model. Additionally, a ceRNA regulatory netwok based on key mRNAsi-related genes was established via TargetScan, miRDB, miRTarBas and miRcode database,and lncRNA SNHG12 was selected for further in vitro and invivo functional assays. ResultsBetween BLCA and normal samples were identified 1560 differentially expressed genes (DEGs).845 DEGs were most significantly associated with mRNAsi according to WGCNA analysis, which were mainly enriched in GO terms and KEGG pathways related to cell proliferation. Univariate Cox regression and LASSO Cox regression algorithms screened 25 mRNAsi-related genes to construct the risk score model with the significant ability to estimate prognosis of BLCA patients. A ceRNA network, including 8 lncRNA, 11 miRNA and 9 mRNAsi-related mRNA, was constructed.We found that lncRNAs ADAMTS9-AS1 and SNHG12 were observably related to the survival of BLCA patients. To verify this finding, we selected SNHG12 for further study. RT-PCR experiments revealed that SNHG12 was high expression in both bladder cancer tissues and cells.SNHG12 promoted proliferation, invasion, migration, apoptosis and stemness of bladder cancer cells in vitro and tumour proliferation in vivo. ConclusionOur study identified 25 biomarkers associated with stemness indices in BLCA and established a ceRNA network based on key mRNAsi-related genes.SNHG12 promoted BLCA proliferation, invasion, migration, apoptosis and stemness in vitro. It was also showed that SNHG12 promoted tumour growth.

Identification and analysis of microRNA editing events in recurrent bladder cancer based on RNA sequencing: MicroRNA editing level is a potential novel biomarker.

Background: With the continued advancement of RNA-seq (RNA-sequencing), microRNA (miRNA) editing events have been demonstrated to play an important role in different malignancies. However, there is yet no description of the miRNA editing events in recurrent bladder cancer. Objective: To identify and compare miRNA editing events in primary and recurrent bladder cancer, as well as to investigate the potential molecular mechanism and its impact on patient prognosis. Methods: We examined the mRNA and miRNA transcriptomes of 12 recurrent bladder cancer cases and 13 primary bladder cancer cases. The differentially expressed mRNA sequences were analyzed. Furthermore, we identified the differentially expressed genes (DEGs) in recurrent bladder cancer. The Gene Ontology (GO) functional enrichment analyses on DEGs and gene set enrichment analysis were performed. The consensus molecular subtype (CMS) classification of bladder cancer was identified using the Consensus MIBC package in R (4.1.0); miRNA sequences were then further subjected to differentially expressed analysis and pathway enrichment analysis. MiRNA editing events were identified using miRge3.0. miRDB and TargetScanHuman were used to predict the downstream targets of specific differentially edited or expressed miRNAs. The expression levels of miR-154-5p and ADAR were validated by RT-qPCR. Finally, survival and co-expression studies were performed on the TCGA-BLCA cohort. Results: First, the mRNA expression levels in recurrent bladder cancer changed significantly, supporting progression via related molecular signal pathways. Second, significantly altered miRNAs in recurrent bladder cancer were identified, with miR-154-5p showing the highest level of editing in recurrent bladder cancer and may up-regulate the expression levels of downstream targets HS3ST3A1, AQP9, MYLK, and RAB23. The survival analysis results of TCGA data revealed that highly expressed HS3ST3A1 and RAB23 exhibited poor prognosis. In addition, miR-154 editing events were found to be significant to CMS classification. Conclusion: MiRNA editing in recurrent bladder cancer was detected and linked with poor patient prognosis, providing a reference for further uncovering the intricate molecular mechanism in recurrent bladder cancer. Therefore, inhibiting A-to-I editing of miRNA may be a viable target for bladder cancer treatment, allowing current treatment choices to be expanded and individualized.