Bladder Cancer Samples Research Articles

Development of a Molecular-Subtype-Associated Immune Prognostic Signature That Can Be Recognized by MRI Radiomics Features in Bladder Cancer

Background: Bladder cancer (BLCA) is highly heterogeneous with distinct molecular subtypes. This research aimed to investigate the heterogeneity of different molecular subtypes from a tumor microenvironment perspective and develop a molecular-subtype-associated immune prognostic signature that can be recognized by MRI radiomics features. Methods: Individuals with BLCA in The Cancer Genome Atlas (TCGA) and IMvigor210 were classified into luminal and basal subtypes according to the UNC classification. The proportions of tumor-infiltrating immune cells (TIICs) were examined using The Cell Type Identification by Estimating Relative Subsets of RNA Transcripts algorithm. Immune-linked genes that were expressed differentially between luminal and basal subtypes and associated with prognosis were selected to develop the immune prognostic signature (IPS) and utilized for the classification of the selected individuals into low- and high-risk groups. Functional enrichment analysis (GSEA) was performed on the IPS. The data from RNA-sequencing and MRI images of 111 BLCA samples in our center were utilized to construct a least absolute shrinkage and selection operator (LASSO) model for the prediction of patients' IPSs. Results: Half of the TIICs showed differential distributions between the luminal and basal subtypes. IPS was highly associated with molecular subtypes, critical immune checkpoint gene expression, prognoses, and immunotherapy response. The prognostic value of the IPS was further verified through several validation data sets (GSE32894, GSE31684, GSE13507, and GSE48277) and meta-analysis. GSEA revealed that some oncogenic pathways were co-enriched in the group at high risk. A novel performance of a LASSO model developed as per ten radiomics features was achieved in terms of IPS prediction in both the validation (area under the curve (AUC): 0.810) and the training (AUC: 0.839) sets. Conclusions: Dysregulation of TIICs contributed to the heterogeneity between the luminal and basal subtypes. The IPS can facilitate molecular subtyping, prognostic evaluation, and personalized immunotherapy. A LASSO model developed as per the MRI radiomics features can predict the IPSs of affected individuals.

Identification of a glutamine metabolism reprogramming signature for predicting prognosis, immunotherapy efficacy, and drug candidates in bladder cancer.

Bladder cancer is the most common malignancy of the urinary system. However, patient prognosis and treatment outcomes in bladder cancer are difficult to predict owing to high tumor heterogeneity. Given that abnormal glutamine metabolism has been identified as a key factor driving the progression of bladder cancer, it is necessary to assess the prognosis and therapeutic efficacy of bladder cancer treatments based on an analysis of glutamine metabolism-related genes. We used bladder cancer sample data downloaded from The Cancer Genome Atlas to identify glutamine metabolism-related genes as prognostic markers, and established a novel Glutamine Metabolism Immunity Index (GMII) based on univariate and multivariate COX regression analyses. On the basis of GMII values, bladder cancer patients were divided into high- and low-risk groups, and systematic analysis was conducted for clinical features, somatic mutations, immune cell infiltration, chemotherapeutic response, and immunotherapeutic efficacy. Candidate small-molecule drugs targeting the GMII core target proteins were identified based on molecular docking analysis. The GMII consisting of eight independent prognostic genes was established to be an excellent tool for predicting the survival in patients with bladder cancer and was validated using multiple datasets. Compared with patients in the high-risk group, those in the low-risk group had significantly better responses to gemcitabine and immune checkpoint blockade. In addition, we predicted 12 potential small-molecule drugs that could bind to three of the GMII core target proteins. The GMII can be used to accurately predict the prognosis and immunotherapeutic response of bladder cancer patients, as well as candidate small-molecule drugs. Furthermore, the novel "Glutamine Metabolism-related Gene"-guided strategy for predicting survival and chemo-immunotherapeutic efficacy may also be applicable for cancers other than bladder cancer.

A Comprehensive Analysis of Immune Response in Patients with Non-Muscle-Invasive Bladder Cancer

Bladder carcinoma has elevated morbimortality due to its high recurrence and progression in localized disease. A better understanding of the role of the tumor microenvironment in carcinogenesis and response to treatment is needed. Peripheral blood and samples of urothelial bladder cancer and adjacent healthy urothelial tissue were collected from 41 patients and stratified in low- and high-grade urothelial bladder cancer, excluding muscular infiltration or carcinoma in situ. Mononuclear cells were isolated and labeled for flow cytometry analysis with antibodies aimed at identifying specific subpopulations within T lymphocytes, myeloid cells and NK cells. In peripheral blood and tumor samples, we detected different percentages of CD4+ and CD8+ lymphocytes, monocyte and myeloid-derived suppressor cells, as well as differential expression of activation- and exhaustion-related markers. Conversely, only a significant increase in bladder total monocytes was found when comparing bladder and tumor samples. Interestingly, we identified specific markers differentially expressed in the peripheral blood of patients with different outcomes. The analysis of host immune response in patients with NMIBC may help to identify specific markers that allow optimizing therapy and patient follow-up. Further investigation is needed to establish a strong predictive model.

CCNB2 as a potential biomarker of bladder cancer via the high throughput technology.

Bladder cancer and oral squamous cell carcinoma (OSCC) seriously affect people's health. However, the relationship between bladder cancer and OSCC remains unclear. Got GSE138206, GSE146483, GSE184616, and bladder cancer datasets GSE65635, GSE100926 from Gene Expression Omnibus database. Weighted gene co-expression network analysis was used to identify the significant module. Functional enrichment analysis was performed via the Gene Ontology analysis and Kyoto Encyclopedia of Genes and Genomes. Furthermore, the Gene Set Enrichment Analysis was also used to complete the enrichment analysis. Comparative Toxicogenomics Database found most relevant diseases to core genes. TargetScan is used to forecast analysis of microRNA and target genes. In Gene Ontology analysis, differentially expressed genes were mostly concentrated in cell differentiation, extrallular region, structural molecule activity, and actin binding. In Kyoto Encyclopedia of Genes and Genomes analysis, the differentially expressed genes were mainly enriched in PI3K-Akt signaling pathway, pathway in cancer, and extracellular matrix-receptor interaction. Seven hub genes (cyclin B2 [CCNB2], TK1, CDC20, PCNA, CKS1B, CDCA5, MCM4) were obtained. Hub genes (CCNB2, CDC20) are highly expressed in OSCC and bladder cancer samples. CCNB2 was one common oncogene of bladder cancer and OSCC.

HNRNPL induced circFAM13B increased bladder cancer immunotherapy sensitivity via inhibiting glycolysis through IGF2BP1/PKM2 pathway

BackgroundThe response rate to immunotherapy in patients with bladder cancer (BCa) remains relatively low. Considering the stable existence and important functions in tumour metabolism, the role of circRNAs in regulating immune escape and immunotherapy sensitivity is receiving increasing attention.MethodsCircular RNA (circRNA) sequencing was performed on five pairs of BCa samples, and circFAM13B (hsa_circ_0001535) was screened out because of its remarkably low expression in BCa. Further mRNA sequencing was conducted, and the association of circFAM13B with glycolysis process and CD8+ T cell activation was confirmed. The functions of circFAM13B were verified by proliferation assays, glycolysis assays, BCa cells-CD8+ T cell co-culture assays and tumorigenesis experiment among human immune reconstitution NOG mice. Bioinformatic analysis, RNA–protein pull down, mass spectrometry, RNA immunoprecipitation, luciferase reporter assay and fluorescence in situ hybridization were performed to validate the HNRNPL/circFAM13B/IGF2BP1/PKM2 cascade.ResultsLow expression of circFAM13B was observed in BCa, and it was positively associated with lower tumour stage and better prognosis among patients with BCa. The function of CD8+ T cells was promoted by circFAM13B, and it could attenuate the glycolysis of BCa cells and reverse the acidic tumour microenvironment (TME). The production of granzyme B and IFN-γ was improved, and the immunotherapy (PD-1 antibodies) sensitivity was facilitated by the inhibition of acidic TME. Mechanistically, circFAM13B was competitively bound to the KH3-4 domains of IGF2BP1 and subsequently reduced the binding of IGF2BP1 and PKM2 3’UTR. Thus, the stability of the PKM2 mRNA decreased, and glycolysis-induced acidic TME was inhibited. The generation of circFAM13B was explored by confirming whether heterogeneous nuclear ribonucleoprotein L (HNRNPL) could promote circFAM13B formation via pre-mRNA back-splicing.ConclusionsHNRNPL-induced circFAM13B could repress immune evasion and enhance immunotherapy sensitivity by inhibiting glycolysis and acidic TME in BCa through the novel circFAM13B/IGF2BP1/PKM2 cascade. Therefore, circFAM13B can be used as a biomarker for guiding the immunotherapy among patients with BCa.

IGF2BP3 overexpression predicts poor prognosis and correlates with immune infiltration in bladder cancer

BackgroundIGF2BP3 expression is associated with poor prognosis in cancers of multiple tissue origins. However, the precise mechanism of its co-carcinogenic action in bladder cancer is unknown.MethodsWe aimed to demonstrate the relationship between IGF2BP3 expression and pan-cancer using The Cancer Genome Atlas (TCGA) database. We next validated IGF2BP3 expression in the Gene Expression Omnibus (GEO) database (GSE3167). Receiver operating characteristic (ROC) curve analysis was used to evaluate the diagnostic values of IGF2BP3. Cox and logistic regression were used to explore the factors affecting the prognosis. Protein–protein interactions (PPIs) network was constructed by STRING. Enrichment analyses were performed to infer involved pathways and functional categories of IGF2BP3 using the cluster Profiler package. We applied single-sample gene set enrichment analysis (ssGSEA) algorithm and TIMER database to evaluate the expression level of immune genes.ResultsPan-cancer analyses reveal that IGF2BP3 was higher in most cancer types, including bladder cancer, and the same results were found in GSE3167. The area under the ROC curve of IGF2BP3 was 0.736, which indicated that IGF2BP3 may be a potential diagnostic biomarker. High IGF2BP3 expression was associated with poorer overall survival (OS) (P = 0.015). For validation, we collected 95 bladder cancer samples and found that IGF2BP3 expression was higher in bladder cancer tissues than that in non-tumor bladder tissues by immunohistochemistry staining. We found a positive correlation between the expression level of IGF2BP3 and the clinical stage of bladder cancer. Immunocyte infiltration analysis showed that high IGF2BP3 expression was correlated with regulating the infiltration level of immune cell, including neutrophil cells and macrophages. IGF2BP3 promotes migration and invasion of bladder cancer cells, while IGF2BP3 inhibition had the opposite effects. Higher IGF2BP3 expression was closely associated with advanced TNM stage.ConclusionIGF2BP3 overexpression was related to disease progression and poor prognosis, as well as infiltration of immune cells in bladder cancer. IGF2BP3 can be a promising independent prognostic biomarker and potential treatment target for bladder cancer.

Construction and validation of a bladder cancer risk model based on autophagy-related genes.

Autophagy has an important association with tumorigenesis, progression, and prognosis. However, the mechanism of autophagy-regulated genes on the risk prognosis of bladder cancer (BC) patients has not been fully elucidated yet. In this study, we created a prognostic model of BC risk based on autophagy-related genes, which further illustrates the value of genes associated with autophagy in the treatment of BC. We first downloaded human autophagy-associated genes and BC datasets from Human Autophagy Database and The Cancer Genome Atlas (TCGA) database, and finally obtained differential prognosis-associated genes for autophagy by univariate regression analysis and differential analysis of cancer versus normal tissues. Subsequently, we downloaded two datasets from Gene Expression Omnibus (GEO), GSE31684 and GSE15307, to expand the total number of samples. Based on these genes, we distinguished the molecular subtypes (C1, C2) and gene classes (A, B) of BC by consistent clustering analysis. Using the genes merged from TCGA and the two GEO datasets, we conducted least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analysis to obtain risk genes and construct autophagy-related risk prediction models. The accuracy of this risk prediction model was assessed by receiver operating characteristic (ROC) and calibration curves, and then nomograms were constructed to predict the survival of bladder cancer patients at 1, 3, and 5years, respectively. According to the median value of the risk score, we divided BC samples into the high- and low-risk groups. Kaplan-Meier (K-M) survival analysis was performed to compare survival differences between subgroups. Then, we used single sample gene set enrichment analysis (ssGSEA) for immune cell infiltration abundance, immune checkpoint genes, immunotherapy response, gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis, and tumor mutation burden (TMB) analysis for different subgroups. We also applied quantitative real-time polymerase chain reaction (PCR) and immunohistochemistry (IHC) techniques to verify the expression of these six genes in the model. Finally, we chose the IMvigor210 dataset for external validation. Six risk genes associated with autophagy (SPOCD1, FKBP10, NAT8B, LDLR, STMN3, and ANXA2) were finally screened by LASSO regression algorithm and multivariate Cox regression analysis. ROC and calibration curves showed that the model established was accurate and reliable. Univariate and multivariate regression analyses were used to verify that the risk model was an independent predictor. K-M survival analysis indicated that patients in the high-risk group had significantly worse overall survival than those in the low-risk group. Analysis by algorithms such as correlation analysis, gene set variation analysis (GSVA), and ssGSEA showed that differences in immune microenvironment, enrichment of multiple biologically active pathways, TMB, immune checkpoint genes, and human leukocyte antigens (HLAs) were observed in the different risk groups. Then, we constructed nomograms that predicted the 1-, 3-, and 5-year survival rates of different BC patients. In addition, we screened nine sensitive chemotherapeutic drugs using the correlation between the obtained expression status of risk genes and drug sensitivity results. Finally, the external dataset IMvigor210 verified that the model is reliable and efficient. We established an autophagy-related risk prognostic model that is accurate and reliable, which lays the foundation for future personalized treatment of bladder cancer.

Single-cell analysis reveals the COL11A1+ fibroblasts are cancer-specific fibroblasts that promote tumor progression.

Background: Cancer-associated fibroblasts (CAFs) promote tumor progression through extracellular matrix (ECM) remodeling and extensive communication with other cells in tumor microenvironment. However, most CAF-targeting strategies failed in clinical trials due to the heterogeneity of CAFs. Hence, we aimed to identify the cluster of tumor-promoting CAFs, elucidate their function and determine their specific membrane markers to ensure precise targeting. Methods: We integrated multiple single-cell RNA sequencing (scRNA-seq) datasets across different tumors and adjacent normal tissues to identify the tumor-promoting CAF cluster. We analyzed the origin of these CAFs by pseudotime analysis, and tried to elucidate the function of these CAFs by gene regulatory network analysis and cell-cell communication analysis. We also performed cell-type deconvolution analysis to examine the association between the proportion of these CAFs and patients' prognosis in TCGA cancer cohorts, and validated that through IHC staining in clinical tumor tissues. In addition, we analyzed the membrane molecules in different fibroblast clusters, trying to identify the membrane molecules that were specifically expressed on these CAFs. Results: We found that COL11A1+ fibroblasts specifically exist in tumor tissues but not in normal tissues and named them cancer-specific fibroblasts (CSFs). We revealed that these CSFs were transformed from normal fibroblasts. CSFs represented a more activated CAF cluster and may promote tumor progression through the regulation on ECM remodeling and antitumor immune responses. High CSF proportion was associated with poor prognosis in bladder cancer (BCa) and lung adenocarcinoma (LUAD), and IHC staining of COL11A1 confirmed their specific expression in tumor stroma in clinical BCa samples. We also identified that CSFs specifically express the membrane molecules LRRC15, ITGA11, SPHK1 and FAP, which could distinguish CSFs from other fibroblasts. Conclusion: We identified that CSFs is a tumor specific cluster of fibroblasts, which are in active state, may promote tumor progression through the regulation on ECM remodeling and antitumor immune responses. Membrane molecules LRRC15, ITGA11, SPHK1 and FAP could be used as therapeutic targets for CSF-targeting cancer treatment.

An IFN-γ-related signature predicts prognosis and immunotherapy response in bladder cancer: Results from real-world cohorts.

Bladder cancer (BLCA) is featured with high incidence and mortality. Whether the IFN-γ signaling could be used as an immunotherapy determinant for BLCA has not been fully confirmed. In this study, the transcriptome data and clinical information of BLCA samples were collected from The Cancer Genome Atlas (TCGA). Besides, four immunotherapy cohorts including IMvigor210 cohort, Gide cohort, Van Allen cohort, and Lauss cohort were collected. The Xiangya real-world cohort was used for independent validation. An IFN-γ-related signature was developed and validated in BLCA for predicting prognosis, mutation, tumor microenvironment status, and immunotherapy response. This is the first study focusing on the comprehensive evaluation of predictive values on the IFN-γ-related signature in BLCA. The potential clinical application of the IFN-γ-related signature was expected to be further validated with more prospective clinical cohorts.

Identification of Potential Key Genes Linked to Gender Differences in Bladder Cancer Based on Gene Expression Omnibus (GEO) Database.

Growing evidence strongly indicates pivotal roles of gender differences in the occurrence and survival rate of patients with bladder cancer, with a higher incidence in males and poorer prognosis in females. Nevertheless, the molecular basis underlying gender-specific differences in bladder cancer remains unknown. The current study has tried to detect key genes contributing to gender differences in bladder cancer patients. The gene expression profile of GSE13507 was firstly obtained from the Gene Expression Omnibus (GEO) database. Further, differentially expressed genes (DEGs) were screened between males and females using R software. Protein-protein interactive (PPI) network analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO), and Kaplan-Meier survival analyses were also performed. We detected six hub genes contributing to gender differences in bladder cancer patients, containing IGF2, CCL5, ASPM, CDC20, BUB1B, and CCNB1. Our analyses demonstrated that CCNB1 and BUB1B were upregulated in tumor tissues of female subjects with bladder cancer. Other genes, such as IGF2 and CCL5, were associated with a poor outcome in male patients with bladder cancer. Additionally, three signaling pathways (focal adhesion, rheumatoid arthritis, and human T-cell leukemia virus infection) were identified to be differentially downregulated in bladder cancer versus normal samples in both genders. Our findings suggested that gender differences may modulate the expression of key genes that contributed to bladder cancer occurrence and prognosis.

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.

A prognostic risk prediction model based on ferroptosis-related long non-coding RNAs in bladder cancer: A bulk RNA-seq research and scRNA-seq validation

To construct a prognostic risk model of bladder cancer (BC) from the perspective of long non-coding RNAs (lncRNAs) and ferroptosis, in order to guide clinical prognosis and identify potential therapeutic targets. In-hours BC samples were collected from 4 patients diagnosed with BC, who underwent radical cystectomy. Single cell transcriptome sequencing was performed and Seurat package were used for quality control and secondary analysis. LncRNAs expression profiles of BC samples were extracted from The Cancer Genome Atlas database. And sex, age, tumor, node, metastasis stage and other clinical data was downloaded at the same time. Ferroptosis-related lncRNAs were identified by co-expression analysis. We constructed a risk model by Cox regression and least absolute shrinkage and selection operator regression analyses. The predictive strength of the risk model for overall survival (OS) of patients with BC was evaluated by the log-rank test and Kaplan-Meier method. Finally, the enrichment analysis was performed and visualized. We identified and included 15 prognostic ferroptosis-related lncRNAs (AL356740.1, FOXC2AS1, ZNF528AS1, LINC02535, PSMB8AS1, AL590428.1, AP000347.2, OCIAD1-AS1, AP001347.1, AC104986.2, AC018926.2, LINC00867, AC099518.4, USP30-AS1, and ARHGAP5-AS1), to build our ferroptosis-related lncRNAs risk model. Using this risk model, BC patients were divided into high and low-risk groups, and their respective survival lengths were calculated. The results showed that the OS of the low-risk group was significantly longer than that of the high-risk group. A nomogram was utilized to predict the survival rate of BC patients. As indicated in the nomogram, risk score was the most important indicator of OS in patients with BC. The ferroptosis-related lncRNAs risk model is an independent tool for prognostic risk assessment in patients with BC. Single cell transcriptome sequencing suggests that ferroptosis-related lncRNAs express specifically in BC tumor microenvironment. AL356740.1, LINC02535 and LINC00867 were mainly expressed in tumor cells. The risk model based on the ferroptosis-related lncRNAs and the genomic clinico-pathological nomogram could be used to accurately predict the prognosis of patients with BC. The lncRNAs used to build this model might become potential therapeutic targets in the future.

Expression pattern of the histone lysine demethylase family and its potential role in bladder cancer: a multi-omics analysis

To investigate the expression patterns of 19 histone lysine demethylases (KDMs) and their role in bladder cancer. In this study, UALCAN and GSCALite were used to analyze the transcriptional expression, methylation level and somatic variation of KDMs in bladder cancer samples from TCGA. Kaplan Meier-Plotter and Assistant for clinical bioinformatics were used to investigate the effect of KDMs expression on the prognosis of BLCA samples. The immune infiltration and drug sensitivity of KDMs in bladder cancer were analyzed by Timer and GSCALite. The KDMs did not show consistent expressions patterns in bladder cancer, where the expressions of KDM1A/1B/2B/4A/4B/5B/5C were significantly upregulated while those of KDM3B/6B/7C were significantly downregulated. Methylation data analysis showed that methylation levels of KDM1A/3B/4A/4B/4C/5A/5B/5C/7B were significantly downregulated and that of KDM7C was upregulated. The transcription levels of 14 KDMs had significant negative correlations with their methylation levels, and among them KDM1A showed the strongest correlation. Mutation analysis revealed that KDM6A had the highest frequency of nonsynonymous mutations with the largest variety, and these mutations were complementary to nonsynonymous mutations of the other KDMs. Survival analysis showed that KDM3A/4C/5D/6A/7B were protective for OS while KDM3B/5B/5C adversely affected RFS of BLCA patients. Further comprehensive prognostic modeling confirmed that KDM4C/6A/7B were potential prognostic biomarkers of bladder cancer, and their expressions were positively correlated with immune infiltration in BLCA patients. KDM2B/3B/4B/4C/5A were negatively correlated with the sensitivity to most anticancer drugs, while KDM2B/4B were positively correlated with the sensitivity to 4 anticancer drugs. The expression patterns of the KDMs in bladder cancer highlight a high mutation complementarity and a negative correlation between over-expression and hypomethylation level closely related with the prognosis, immune infiltration and drug sensitivity.

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.

Identification of molecular subtypes based on liquid-liquid phase separation and cross-talk with immunological phenotype in bladder cancer.

Mounting evidence has demonstrated that an imbalance in liquid-liquid phase separation (LLPS) can induce alteration in the spatiotemporal coordination of biomolecular condensates, which plays a role in carcinogenesis and cachexia. However, the role of LLPS in the occurrence and progression of bladder cancer (BLCA) remains to be elucidated. Identifying the role of LLPS in carcinogenesis may aid in cancer therapeutics. A total of 1,351 BLCA samples from six cohorts were retrieved from publicly available databases like The Cancer Genome Atlas, Gene Expression Omnibus, and ArrayExpress. The samples were divided into three distinct clusters, and their multi-dimensional heterogeneities were explored. The LLPS patterns of all patients were determined based on the LLPS-related risk score (LLPSRS), and its multifaceted landscape was depicted and experimentally validated at the multi-omics level. Finally, a cytotoxicity-related and LLPSRS-based classifier was established to predict the patient's response to immune checkpoint blockade (ICB) treatment. Three LLPS-related subtypes were identified and validated. The differences in prognosis, tumor microenvironment (TME) features, cancer hallmarks, and certain signatures of the three LLPS-related subtypes were validated. LLPSRS was calculated, which could be used as a prognostic biomarker. A close correlation was observed between clinicopathological features, genomic variations, biological mechanisms, immune infiltration in TME, chemosensitivity, and LLPSRS. Furthermore, our classifier could effectively predict immunotherapy response in patients with BLCA. Our study identified a novel categorization of BLCA patients based on LLPS. The LLPSRS could predict the prognosis of patients and aid in designing personalized medicine. Further, our binary classifier could effectively predict patients' sensitivity to immunotherapy.

NEAT1 promotes the malignant development of bladder cancer by regulating the miR-101/VEGF-C pathway in vitro and in vivo

BackgroundNEAT1 has been shown to play an oncogenic role in many kinds of cancers. However, detailed roles of NEAT1 in bladder cancer are largely unknown.MethodsIn the present study, the expression of NEAT1, miR-101 and VEGF-C was detected in human bladder cancer samples. The relationship between NEAT1 and the prognosis of patients with bladder cancer was analysed. In vitro experiments explored the effects of NEAT1 on biological behaviours of bladder cancer T24 and 5637 cells. Bioinformatics prediction and luciferase assays were used to assay the regulatory mechanism of action of NEAT1 and miR-101. Loss and gain of the expression of miR-101 and VEGF-C were used to explore the effects of the NEAT1/miR-101/VEGF-C pathway on T24 and 5637 cells. The effect of NEAT1 on the growth of bladder cancer in vivo was explored using an orthotopic tumourigenesis model.ResultsNEAT1 and VEGF-C were significantly upregulated in bladder cancer samples, and miR-101 was significantly downregulated. NEAT1 upregulation was associated with poorer recurrence-free survival of patients with bladder cancer. Overexpression of NEAT1 promoted the proliferation, migration and invasion of bladder cancer cells. The results of the luciferase assay indicated that miR-101 was a target of NEAT1. The promoting effects of NEAT1 on bladder cancer cells were reversed by miR-101 upregulation, and inhibition of miR-101 enhanced the effects of NEAT1. Overexpression of VEGF-C had a clear synergistic effect with the action of NEAT1. Overexpression of NEAT1 increased tumour growth and induced the development of liver metastasis.ConclusionsIn conclusion, our data indicated that NEAT1 was expressed at high levels in bladder cancer patients and correlated with unfavourable prognosis. NEAT1 promoted malignant development of bladder cancer in vitro and in vivo by regulating the miR-101/VEGF-C pathway.

Construction of cuproptosis-related gene signature to predict the prognosis and immunotherapy efficacy of patients with bladder cancer through bioinformatics analysis and experimental validation.

Background: A new form of cell death, copper-dependent cell death (termed cuproptosis), was illustrated in a recent scientific study. However, the biological function or prognostic value of cuproptosis regulators in bladder cancer (BLCA) remains unknown. Materials and Methods: Sequencing data obtained from BLCA samples in TCGA and GEO databases were preprocessed for analysis. Biological function and immune cell infiltration levels evaluated by gene set variation analysis (GSVA) were employed to calculate enrichment scores. Iteration least absolute shrinkage and selection operator (LASSO) and COX regression model were employed to select feature genes and construct a novel cuproptosis-related (CR) score signature. The genomics of drug sensitivity in cancer (GDSC) and tumor immune dysfunction and exclusion (TIDE) analysis were used to predict the chemotherapy and immunotherapy efficacy for BLCA patients. The relative expression of the genes involved in the signature was also verified by real-time quantitative PCR (qRT-PCR) in cell lines and tissues. Results: Expression abundance and the prognostic value of cuproptosis regulators proved that cuproptosis might play a vital part in the carcinogenesis of BLCA. GSVA revealed that cuproptosis regulators might be associated with metabolism and metastasis-related pathways such as TGF-β, protein secretion, oxidative Phosphorylation, MYC targets, MTORC1, and adipogenesis pathways. CR scores could predict the prognosis and evaluate the chemotherapy and immunotherapy efficacies of BLCA. CR scores were positively correlated with EMT, MYC, MTORC1, HEDGEHOG, and E2F signaling pathways; meanwhile, they were negatively correlated with several immune cell infiltration levels such as CD8+ T cells, γδT cells, and activated dendritic cells. Several GEO datasets were used to validate the power of prognostic prediction, and a nomogram was also established for clinical use. The expressions of DDX10, RBM34, and RPL17 were significantly higher in BLCA cell lines and tissues in comparison with those in the corresponding normal controls. Conclusion: Cuproptosis might play an essential role in the progression of BLCA. CR scores could be helpful in the investigation of prognostic prediction and therapeutic efficacy and could make contributions to further studies in BLCA.

Development and validation of a novel model for predicting the survival of bladder cancer based on ferroptosis-related genes.

The role of ferroptosis, a new form of cell death, in bladder cancer (BC) has not been sufficiently studied. This study aimed to establish a prognostic prediction model for BC patients based on the expression profile of ferroptosis-related genes (FRG). The expression profiles of BC samples with clinical information were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). A total of 80 differentially expressed genes (DEGs) related to FRG were identified among which 37 DEGs were found to have a prognostic value. Eleven genetic markers including SLC2A12, CDO1, JDP2, MAFG, CAPG, RRM2, SLC2A3, SLC3A2, VDAC2, GCH1, and ANGPTL7 were identified through the LASSO regression analysis. The ROC curve analysis showed that the AUC was 0.702, 0.664, and 0.655 for the 1-year, 3-year, and 5-year survival outcomes, respectively. The prediction performance was verified in the TCGA-testing set and external set GSE13507. Multivariate Cox proportional hazards analysis showed that the risk score was an independent prognostic predictor. Moreover, we found differences in gene mutation, gene expression, and immune cell infiltration between the high and low-risk groups of BC patients. Finally, a nomogram was constructed by integrating clinical features and FRG signatures to predict the survival outcomes of BC patients. In addition, the differential expression of FRG mRNA and protein was verified through PCR and HPA online site. The characteristics of 11 FRG genes were examined and a prognostic nomogram for predicting the overall survival of BC was established.

The prognostic role of p53 and its correlation with CDK9 in urothelial carcinoma

PurposeThe mutation of p53 is considered a pivotal step in bladder cancer pathogenesis. Recently, distinct interactions between p53 and CDK9, a transcription regulator, have been described. In this work, we explored the prognostic role of p53 expression and evaluated its associations with CDK9 in urothelial carcinoma.Materials and methodsThe research group consisted of 67 bladder cancer samples and 32 normal urothelial mucosa samples. All specimens were analyzed using ImageJ and the IHC profiler plugin. To validate the results, 406 cases from The Cancer Genome Atlas database were analyzed.ResultsP53 and CDK9 are overexpressed in urothelial cancer tissues when compared to normal urothelial tissues (p < 0.05). High p53 expression was observed in metastatic tumors and tumors with high CDK9 expression (p < 0,05). High p53 expression was predictive for shorter survival in patients with non-muscle-invasive bladder cancer (HR = 0.107 [0.012–0.96]; p = 0.046) but did not correlate with prognosis in the muscle-invasive group. In high CDK9 cancers, high p53 expression correlated with the occurrence of high-grade and muscle-invasive tumors (p < 0.05).ConclusionHigh expression of p53 correlates with unfavorable clinical features of bladder cancer. CDK9 is associated with the expression of p53, possibly through interactions with p53 inhibitors. Since the blockade of CDK9 in other malignancies reactivates wild-p53 activity, confirming the crosstalk between p53 and CDK9 in bladder cancer may be another step to explain the mechanism of tumor progression in its early stages.

UCHL5 Promotes Proliferation and Migration of Bladder Cancer Cells by Activating c-Myc via AKT/mTOR Signaling.

Ubiquitin C-terminal hydrolase L5 (UCHL5) is a deubiquitinating enzyme (DUB) that removes ubiquitin from its substrates. Associations between UCHL5 and cancer have been reported in various tissues, but the effect of UCHL5 on bladder cancer has not been thoroughly investigated. This study investigates the expression and function of UCHL5 in bladder cancer. UCHL5 was shown to be abnormally expressed using IHC of tissue microarray and Western blotting. Several procedures were performed to assess the effect of UCHL5 overexpression or knockdown on bladder cancer, such as cell proliferation, colony formation, wound-healing, and Transwell assays. In addition, RNA-Seq and Western blotting experiments were used to verify the status of downstream signaling pathways. Finally, bladder cancers with knockdown or overexpression of UCHL5 were treated with either SC79 or LY294002 to examine the participation of the AKT/mTOR signaling pathway and the expression of downstream targets c-Myc, SLC25A19, and ICAM5. In contrast to adjacent tissue samples, we discovered that UCHL5 was substantially expressed in bladder cancer samples. We also found that UCHL5 downregulation significantly suppressed both tumor growth in vivo and cell proliferation and migration in vitro. According to RNA-Seq analyses and Western blotting experiments, the expression of c-Myc, SLC25A19, and ICAM5 was modified as a result of UCHL5 activating AKT/mTOR signaling in bladder cancer cells. All things considered, our findings show that increased UCHL5 expression stimulates AKT/mTOR signaling, subsequently triggering the expression of c-Myc, SLC25A19, and ICAM5, which in turn promotes carcinogenesis in bladder cancer. UCHL5 is therefore a potential target for therapy in bladder cancer patients.