Prognosis Of Bladder Cancer Research Articles

A novel focal adhesion-related risk model predicts prognosis of bladder cancer —— a bioinformatic study based on TCGA and GEO database

BackgroundBladder cancer (BLCA) is the ninth most common cancer globally, as well as the fourth most common cancer in men, with an incidence of 7%. However, few effective prognostic biomarkers or models of BLCA are available at present.MethodsThe prognostic genes of BLCA were screened from one cohort of The Cancer Genome Atlas (TCGA) database through univariate Cox regression analysis and functionally annotated by Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. The intersecting genes of the BLCA gene set and focal adhesion-related gene were obtained and subjected to the least absolute shrinkage and selection operator regression (LASSO) to construct a prognostic model. Gene set enrichment analysis (GSEA) of high- and low-risk patients was performed to explore further the biological process related to focal adhesion genes. Univariate and multivariate Cox analysis, receiver operating characteristic (ROC) curve analysis, and Kaplan–Meier survival analysis (KM) were used to evaluate the prognostic model. DNA methylation analysis was presented to explore the relationship between prognosis and gene methylation. Furthermore, immune cell infiltration was assessed by CIBERSORT, ESTIMATE, and TIMER. The model was verified in an external GSE32894 cohort of the Gene Expression Omnibus (GEO) database, and the Prognoscan database presented further validation of genes. The HPA database validated the related protein level, and functional experiments verified significant risk factors in the model.ResultsVCL, COL6A1, RAC3, PDGFD, JUN, LAMA2, and ITGB6 were used to construct a prognostic model in the TCGA-BLCA cohort and validated in the GSE32894 cohort. The 7-gene model successfully stratified the patients into both cohorts’ high- and low-risk groups. The higher risk score was associated with a worse prognosis.ConclusionsThe 7-gene prognostic model can classify BLCA patients into high- and low-risk groups based on the risk score and predict the overall survival, which may aid clinical decision-making.

Circulating tumor cells correlating with Ki-67 predicts the prognosis of bladder cancer patients

PurposeTo investigate the value of circulating tumor cells (CTCs) and Ki-67 in predicting the prognosis of bladder cancer. Here, we tested CTC counts and Ki-67 levels to assess patient prognosis.Methods84 patients with bladder cancer who underwent surgery were included in this study. Peripheral blood CTCs were detected by SE-iFISH technology before and after surgery, and Ki-67 levels were analyzed by immunohistochemistry. The association between CTCs and Ki-67 and the combination of the two was analyzed to predict the prognosis of patients.Results76 out of 84 patients (90.5%) were positive. ROC curve analysis showed that preoperative and postoperative CTC counts = 4 and 2 were the best thresholds for predicting patient recurrence or death. In multivariate analysis, high postoperative CTC count (≥ 2) (P < 0.001) and Ki-67 high expression (≥ 15%) (P < 0.001) were independent poor prognostic factors for PFS in bladder cancer patients. In addition, the study found that Ki-67 levels were positively correlated with high postoperative CTC counts, Bladder cancer patients with Ki-67 high expression and high postoperative CTC counts were associated with extremely poor progression-free survival.ConclusionKi-67 high expression is associated with high postoperative CTC counts, both of which predict poor prognosis in bladder cancer patients.

Ferroptosis: A new therapeutic target for bladder cancer.

Bladder cancer (BC) is the most frequent type of urinary system cancer. The prognosis of BC is poor due to high metastasis rates and multidrug resistance. Hence, development of novel therapies targeting BC cell death is urgently needed. As a novel cell death type with strong antitumor potential, ferroptosis has been investigated by many groups for its potential in BC treatment. As an iron-dependent cell death process, ferroptosis is characterized by excessive oxidative phospholipids. The molecular mechanisms of ferroptosis include iron overload and the system Xc-GSH-GPX4 signaling pathway. A recent study revealed that ferroptosis is involved in the metastasis, treatment, and prognosis of BC. Herein, in this review, we comprehensively summarize the mechanism of ferroptosis, address newly identified targets involved in ferroptosis, and discuss the potential of new clinical therapies targeting ferroptosis in BC.

Identification of immuno-infiltrating MAP1A as a prognosis-related biomarker for bladder cancer and its ceRNA network construction.

Approximately 75% of bladder cancer occurrences are of the non-muscle-invasive type. The estimated five-year survival rate is 26%-55%. Currently, there is no reliable biomarker available for early diagnosis and prognosis of bladder cancer. The present study aims to identify a biomarker using bioinformatic approaches to provide a new insight in clinical research for early diagnosis and prognosis of bladder cancer. Clinical data and a transcriptome of bladder cancer were obtained from TCGA, GEO, GETx, and UCSC Xena. The differential expressed gene (DEG) analysis, weighted gene co-expression network analysis (WGCNA), and survival analysis using the Kaplan-Meier and Cox proportional-hazards models were used to identify the Microtubule-associated Proteins 1A (MAP1A). on overall survival (OS) and disease-free survival (DFS) was analyzed using GEPIA and GETx databases. The TIMER 2.0 database predicted the correlation between MAP1A and immunocytes and immune checkpoints. Target prediction of the regulated competing endogenous RNAs (ceRNAs) network of MAP1A was performed using starBase and TargetScan. Cystoscope v3.7.2 software was used to visualize the ceRNA coexpression network. The R programming language v4.0.2 was applied as an analytic tool. Gene expression of MAP1A verified by RT-qPCR. The low expression of MAP1A was verified in bladder cancer tissues and bladder cancer cell lines SW780 and 5637.P < 0.001 were obtained by Kaplan-Meier survival analysis and Cox proportional hazards model, with a hazard ratio (HR) of 1.4. Significant correlations between MAP1A and OS (P < 0.001, HR = 1.9) as well as DFS (P < 0.05, HR = 1.7) in bladder cancer were identified through gene expression profiling interactive analysis (GEPIA), indicating MAP1A may be a high-risk factor. Significant correlation in single copy-number variation of MAP1A gene with CD8+ T cells, and myeloid dendritic cells (MDCs) (P < 0.05) was noted. MAP1A expression was shown to be significantly correlated with the amount of CD4+ T cells and CD8+ T cells, MDCs, macrophages, and neutrophils in a statistically significant positive manner (P < 0.001). However, the MAP1A expression demonstrated a strong negative connection with B cells (P < 0.001). Except for macrophage M1 genes IRF5 and PTGS2, MAP1A expression was significantly correlated with the gene levels in immunocytes such as CD4+ T cells, CD8+ T cells, B cells, dendritic cells (DCs), macrophages, and neutrophils (Cor > 0.2, P < 0.001), as well as immune checkpoint related genes including cytotoxic t-lymphocyte-associated protein 4 (CTLA-4), programmed death 1 (PD-1), programmed death ligand 1 (PD-L1) (P < 0.001). Finally, we predicted that the MAP1A-interacting miRNA was miR-34a-5p, and the MAP1A endogenous competing RNAs were LNC00667, circ_MAP1B, and circ_MYLK, respectively. These findings support the need for further studies on the mechanism underlying the pathogenesis of this disease. MAP1A is considered as a prospective biomarker for early diagnosis, therapeutic observation, and prognosis analysis in bladder cancer.

O3 - Prognosis of primary papillary Ta-G3 bladder cancer in the non-muscle invasive spectrum

O3 - Prognosis of primary papillary Ta-G3 bladder cancer in the non-muscle invasive spectrum

N6-methyladenosine-related lncRNAs in combination with computational histopathology and radiomics predict the prognosis of bladder cancer

ObjectivesIdentification of m6A- related lncRNAs associated with BC diagnosis and prognosis. MethodsFrom the TCGA database, we obtained transcriptome data and corresponding clinical information (including histopathological and CT imaging data) for 408 patients. And bioinformatics, computational histopathology, and radiomics were used to identify and analyze diagnostic and prognostic biomarkers of m6A-related lncRNAs in BC. Results3 significantly high-expressed m6A-related lncRNAs were significantly associated with the prognosis of BC. The BC samples were divided into two subgroups based on the expression of the 3 lncRNAs. The overall survival of patients in cluster 2 was significantly lower than that in cluster 1. The immune landscape results showed that the expression of PD-L1, T cells follicular helper, NK cells resting, and mast cells activated in cluster 2 were significantly higher, and naive B cells, plasma cells, T cells regulatory (Tregs), and mast cells resting were significantly lower. Computational histopathology results showed a significantly higher percentage of tumor-infiltrating lymphocytes (TILs) in cluster 2. The radiomics results show that the 3 eigenvalues of diagnostics image-original minimum, diagnostics image-original maximum, and original GLCM inverse variance are significantly higher in cluster 2. High expression of 2 bridge genes in the PPI network of 30 key immune genes predicts poorer disease-free survival, while immunohistochemistry showed that their expression levels were significantly higher in high-grade BC than in low-grade BC and normal tissue. ConclusionBased on the results of immune landscape, computational histopathology, and radiomics, these 3 m6A-related lncRNAs may be diagnostic and prognostic biomarkers for BC.

M6A-immune-related lncRNA prognostic signature for predicting immune landscape and prognosis of bladder cancer

BackgroundN6-methyladenosine (m6A) related long noncoding RNAs (lncRNAs) may have prognostic value in bladder cancer for their key role in tumorigenesis and innate immunity.MethodsBladder cancer transcriptome data and the corresponding clinical data were acquired from the Cancer Genome Atlas (TCGA) database. The m6A-immune-related lncRNAs were identified using univariate Cox regression analysis and Pearson correlation analysis. A risk model was established using least absolute shrinkage and selection operator (LASSO) Cox regression analyses, and analyzed using nomogram, time-dependent receiver operating characteristics (ROC) and Kaplan–Meier survival analysis. The differences in infiltration scores, clinical features, and sensitivity to Talazoparib of various immune cells between low- and high-risk groups were investigated.ResultsTotally 618 m6A-immune-related lncRNAs and 490 immune-related lncRNAs were identified from TCGA, and 47 lncRNAs of their intersection demonstrated prognostic values. A risk model with 11 lncRNAs was established by Lasso Cox regression, and can predict the prognosis of bladder cancer patients as demonstrated by time-dependent ROC and Kaplan–Meier analysis. Significant correlations were determined between risk score and tumor malignancy or immune cell infiltration. Meanwhile, significant differences were observed in tumor mutation burden and stemness-score between the low-risk group and high-risk group. Moreover, high-risk group patients were more responsive to Talazoparib.ConclusionsAn m6A-immune-related lncRNA risk model was established in this study, which can be applied to predict prognosis, immune landscape and chemotherapeutic response in bladder cancer.

The Urothelial Transcriptomic Response to Interferon Gamma: Implications for Bladder Cancer Prognosis and Immunotherapy.

Interferon gamma (IFNγ) is central to the inflammatory immune response, such as that entrained by BCG immunotherapy for bladder cancer. However, immune-mediated tumour cell killing is subject to modulation by immunoinhibitory "checkpoint" receptors such as PD-L1. We investigated the effects of IFNγ on barrier-forming in vitro-differentiated normal human urothelium using mRNA-sequencing, and showed canonical upregulation of MHC class I/II and de novo expression of the T cell tropic CXCL9-11 chemokines. Normal urothelium constitutively expressed immunoinhibitory B7 family member VSIR (VISTA), while CD274 (PD-L1) expression was induced/upregulated by IFNγ. We generated a urothelial IFNγ response gene signature. When applied to the unsupervised clustering of non-muscle-invasive bladder cancers, the IFNγ-signature predicted longer recurrence-free survival. In muscle-invasive cancers, the IFNγ-signature split the basal/squamous consensus subtype, with significantly worse overall survival when weak or absent. This study offers novel insights into strategies to enhance immunotherapy via the IFNγ and VISTA/PD-L1 nexus.

Immunogenic cell death mediation patterns reveal novel paradigm for characterizing the immune microenvironment and immunotherapeutic responses in bladder cancer.

Background: Immunogenic cell death (ICD) plays an important role in several malignancies. However, the role of ICD-mediated patterns in bladder cancer (BCA) remains unknown. Methods: For assessing the ICD-mediated patterns based on the expression of IRGs, 4 large BCA cohorts were obtained. The ICD-mediated patterns of individual samples were quantified as an ICD score by principal component analysis. The correlations of the ICD-mediated patterns with the tumor immune microenvironment (TIME) and responses to immunotherapy were comprehensively evaluated. The IRGs with predictive prognostic values were further validated by in vitro loss of function assays. Results: Two distinct ICD-mediated patterns were established, showing distinct clinical features and immune microenvironment features. Although ICD cluster A was associated with a poor prognosis with a high ICD score, it showed an immune activation state with a more favorable response to immunotherapy and treatment that induced ICD. The ICD-related gene, CALR, was significantly upregulated in the T24 BCA cell line relative to the control SV-HUC-1 cells. Knocking down CALR suppressed T24 cell viability and caused ER stress. Conclusion: We identified the existence of distinct ICD-mediated patterns in BCA closely associated with the remodeling of the TIME. Further in-depth examination of ICD-related features is warranted to obtain a broader prospect for therapeutic innovations and improved prognosis of BCA.

Both radiographical and pathological lymph node statuses are independent predictors for survival following neoadjuvant chemotherapy and radical cystectomy for cT3/4 or cN+ bladder cancer

IntroductionUrothelial bladder cancer (UBC) with clinical suspicion of locally advanced growth or pelvic lymphogenic spread has a high risk of progression and death.Patients and methodsBladder cancer patients with locally advanced (cT3/4) tumor growth or suspected pelvic lymphogenic spread (cN+) were treated with preoperative cisplatin-containing chemotherapy and consolidative cystectomy with pelvic lymphadenectomy. We aimed to identify prognostic factors and describe the patients’ oncological outcome.ResultsA complete dataset including follow-up data was available for 96 patients. In a univariate analysis, we identified cN stage (cN+ vs cN-, HR 2.7, 95% CI 1.3–6.0), response to chemotherapy (HR 0.2, 95% CI 0.1–0.5), ypT stage (ypT0/is/1 vs ypT2-4, HR 3.1, 95% CI 1.4–6.8), ypN stage (ypN + vs ypN-, HR 7.9, 95% CI 3.7–17.0), resection status (HR 4.4, 95% CI HR 1.5–13.0) as significantly associated with cancer-specific survival. In a multivariate regression analysis, both cN and ypN statuses were validated as independent prognostic factors for cancer-specific survival (cN: HR 2.6, 95% CI 1.1–6.1; ypN: HR 5.5, 95% CI 2.0–15.1).DiscussionLymph node status was identified as a prognostic marker in a high-risk cohort of UBC patients treated with inductive chemotherapy and cystectomy. Establishing cN status as a prognosticator underlines the necessity to aggressively treat these patients despite reported impreciseness of imaging procedures in UCB. Patients with histologically positive lymph nodes following preoperative chemotherapy have a very poor prognosis, and thus, the need for adjuvant systemic treatment is emphasized.ConclusionBoth clinically and pathologically affected lymph nodes convey a poor prognosis in bladder cancer and necessitate aggressive treatment.

Neutrophil-related genes predict prognosis and response to immune checkpoint inhibitors in bladder cancer.

Neutrophils play a key role in the occurrence and development of cancer. However, the relationship between neutrophils and cancer prognosis remains unclear due to their great plasticity and diversity. To explore the effects of neutrophils on the clinical outcome of bladder cancer, we acquired and analyzed gene expression data and clinical information of bladder cancer patients from IMvigor210 cohort and The Cancer Genome Atlas dataset (TCGA) database. We established a neutrophil-based prognostic model incorporating five neutrophil-related genes (EMR3, VNN1, FCGRT, HIST1H2BC, and MX1) and the predictive value of the model was validated in both an internal and an external validation cohort. Multivariate Cox regression analysis further proved that the model remained an independent prognostic factor for overall survival and a nomogram was constructed for clinical practice. Additionally, FCGRT was identified as the key neutrophil-related gene linked to an adverse prognosis of bladder cancer. Up-regulation of FCGRT indicated activated cancer metabolism, immunosuppressive tumor environment, and dysregulated functional status of immune cells. FCGRT overexpression was also correlated with decreased expression of PD-L1 and low levels of tumor mutation burden (TMB). FCGRT predicted a poor response to immunotherapy and had a close correlation with chemotherapy sensitivity. Taken together, a novel prognostic model was developed based on the expression level of neutrophil-related genes. FCGRT served as a promising candidate biomarker for anti-cancer drug response, which may contribute to individualized prognostic prediction and may contribute to clinical decision-making.

Fibroblast Common Serum Response Signature-Related Classification Affects the Tumour Microenvironment and Predicts Prognosis in Bladder Cancer.

Abnormal oncogenic signatures provide important clues regarding cancer prognosis and treatment. We analysed the variations in 189 oncogenic signature gene sets between normal and tumourous tissues from The Cancer Genome Atlas (TCGA) and found that the “CSR_LATE_UP” signature was the most upregulated oncogenic signature gene set in bladder cancer. Next, we developed a common serum response (CSR) risk score (CRS) model based on fibroblast CSR genes and systematically analysed the correlations of these genes or the CRSs with survival, previously reported molecular subtypes, clinicopathological features, cancer signalling pathways, chemotherapeutic responses, and the tumour microenvironment using TCGA and validation cohorts. The CRS could predict the malignant phenotype, chemotherapeutic efficacy, immune invasion, and disease prognosis. Inflammatory signalling pathways (e.g., inflammatory response, TNFA signalling via NFƘB, IFNα response, and IL2-STAT5 signalling) were markedly upregulated in patients with high CRS. Notably, the CSR-related gene ANLN was positively correlated with CD8+ immune cell infiltration, PD-L1 expression, and sensitivity to PD-L1 inhibitors and could thus provide guidance for clinical immunotherapy. This study highlights the crucial role of the CSR signature in bladder cancer and provides a CRS model for accurate predictions of the disease prognosis and chemotherapy and immunotherapy responses.

Metabolic-associated signature and hub genes associated with immune microenvironment and prognosis in bladder cancer.

The relationship between metabolism and immune microenvironment remains to be studied in bladder cancer (BCa). We aimed to construct a metabolic-associated signature for prognostic prediction and investigate its relationship with the immune microenvironment in BCa. The RNA expression of metabolism associated genes was obtained from a combined data set including The Cancer Genome Atlas, GSE48075, and GSE13507 to divide BCa patients into different clusters. A metabolic-associated signature was constructed using the differentially expressed genes between clusters in the combined data set and validated in the IMvigor210 trial and our center. The composition of tumor-infiltrating immune cells (TIICs) was evaluated using the single-sample Gene Set Variation Analysis. BCa patients in Cluster A or high-risk level were associated with advanced clinicopathological features and poor survival outcomes. The percentage of high-risk patients was significantly lower in patients responding to anti-PD-L1 treatment. Compared with low-risk patients, the IC50 values of cisplatin and gemcitabine were significantly lower in high-risk patients. Thiosulfate transferase (TST) and S100A16 were significantly associated with clinicopathological features and prognosis. Downregulation of TST promoted BCa cell invasion, migration, and epithelial-to-mesenchymal transition, which are inhibited by downregulation of S100A16. CD8 + T cells, neutrophils, and dendritic cells had higher infiltration in the TST low-level and the S100A16 high-level. Furthermore, loss of function TST and S100A16 significantly affected the expression of PD-L1 and CD47. The metabolic-associated signature can stratify BCa patients into distinct risk levels with different immunotherapeutic susceptibility and survival outcomes. Metabolism disorder promoted the dysregulation of immune microenvironment, thus contributing to immunosuppression.

Editorial: Molecular biomarkers and imaging markers in the prediction, diagnosis, and prognosis of bladder cancer.

Bladder cancer (BLCA) is a common malignant tumor in the urinary system. BLCA is divided into muscle-invasive bladder cancer (MIBC) and non-muscle-invasive bladder cancer (NMIBC) 1 . Approximately 70% of BLCA patients are initially diagnosed with NMIBC, but 50-70% of patients relapse after treatment, and 10-20% of patients progress to MIBC. The 5-year survival rate for patients with MIBC is about 50% 2,3 . Nowadays there is still a lack of public recognized, universally applicable diagnosis and prognostic markers for BLCA.In this Research Topic, we compiled seventeen research articles and one review that summarized new advances about molecular biomarkers and imaging markers in the prediction, diagnosis, and prognosis of BLCA. In conclusion, the collections of research articles and reviews under this Research Topic present novel insights on the prediction, diagnosis, and prognosis of bladder cancer. It will hopefully encourage us to explore molecular targets from various perspectives and ultimately promote the diagnosis and treatment of BLCA.

Identification of adenylate cyclase 2 methylation in bladder cancer with implications for prognosis and immunosuppressive microenvironment.

BackgroundThe incidence and mortality of bladder cancer (BCa) are increasing, while the existing diagnostic methods have limitations. Therefore, for early detection and response prediction, it is crucial to improve the prognosis and treatment strategies. However, with existing diagnostic methods, detecting BCa in the early stage is challenging. Hence, novel biomarkers are urgently needed to improve early diagnosis and treatment efficiency.MethodsThe gene expression profile and gene methylation profile dataset were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs), differentially methylated genes (DMGs), and methylation-regulated differentially expressed genes (MeDEGs) were gradually identified. A cancer genome map was obtained using online gene expression profile interaction analysis, and survival implications were produced using Kaplan-Meier survival analysis. GSEA was employed to predict the marker pathways where DEGs were significantly involved. The study used bisulfite PCR amplification combined with bisulfite amplicon sequencing (BSAS) to screen for methylation analysis of multiple candidate regions of the adenylate cyclase 2 (ADCY2) based on the sequence design of specific gene regions and CpG islands.ResultsIn this study, DEGs and DMGs with significantly up- or down-regulated expression were selected. The intersection method was used to screen the MeDEGs. The interaction network group in STRING was then visualized using Cytoscape, and the PPI network was constructed to identify the key genes. The key genes were then analyzed using functional enrichment. To compare the relationship between key genes and the prognosis of BCa patients, we further investigated ADCY2 and found that ADCY2 can be a potential clinical biomarker in BCa prognosis and immunotherapy response prediction. In human BCa 5637 and MGH1 cells, we developed and verified the effectiveness of ADCY2 primers using BSAS technology. The findings revealed that the expression of ADCY2 is highly regulated by the methylation of the promoter regions.ConclusionThis study revealed that increased expression of ADCY2 was significantly correlated with increased tumor heterogeneity, predicting worse survival and immunotherapy response in BCa patients.

An immune‐related gene signature for the prognosis of human bladder cancer based on WGCNA

The innovation of immunotherapy was a milestone in the treatment of bladder cancer (BLCA). However, the treatment benefits varied by individual thus promoting the investigation of the biomarker of the patients. Unfortunately, there were not many effective predictive models, which were desired by clinicians, for BLCA that can predict the prognosis and benefit of immunotherapy. We constructed a three genes prognosis prediction model termed RiskScore based on the result of weighted correlation network analysis (WGCNA) from The Cancer Genome Atlas (TCGA) cohort (n = 406). We then validated the prediction accuracy with three validation cohort(GSE13507 (n = 165), GSE48075(n = 73), GSE32894(n = 224)). We compared the differences in gene expression, immune relate function, and immune infiltration between two groups divided by RiskScore. We further discovered the potential drug target and suitable compounds for high-risk groups. Our results suggested that the low-risk group may be more potential for immunotherapy for they have higher B cell infiltration, higher expression of immune checkpoints(PDCD1, CTLA4), and much more active immune-related pathways(B cell and T cell receptor signaling pathway). The RiskScore showed a well predictive accuracy for the prognosis of BLCA. After Spearman analysis, we found the suitable drug target and compounds for the patients in the high-risk group. The model we constructed is able to predict the prognosis of BLCA patients with ease and accuracy. PLK1 and gefitinib may be utilized for further treatment of BLCA patients.

A Novel Risk Model for lncRNAs Associated with Oxidative Stress Predicts Prognosis of Bladder Cancer.

Background Oxidative stress (OS) reactions are closely related to the development and progression of bladder cancer (BCa). This project aimed to identify new potential biomarkers to predict the prognosis of BCa and improve immunotherapy. Methods We downloaded transcriptomic information and clinical data on BCa from The Cancer Genome Atlas (TCGA). Screening for OS genes was statistically different between tumor and adjacent normal tissue. A coexpression analysis between lncRNAs and differentially expressed OS genes was performed to identify OS-related lncRNAs. Then, differentially expressed oxidative stress lncRNAs (DEOSlncRNAs) between tumors and normal tissues were identified. Univariate/multivariate Cox regression analysis was performed to select the lncRNAs for risk assessment. LASSO analysis was conducted to establish a prognostic model. The prognostic risk model could accurately predict BCa patient prognosis and reveal a close correlation with clinicopathological features. We analyzed the principal component analysis (PCA), immune microenvironment, and half-maximal inhibitory concentration (IC50) in the risk groups. Results We constructed a model containing eight DEOSlncRNAs (AC021321.1, AC068196.1, AC008750.1, SETBP1-DT, AL590617.2, THUMPD3-AS1, AC112721.1, and NR4A1AS). The prognostic risk model showed better results in predicting the prognosis of BCa patients and was strongly correlated with clinicopathological characteristics. We found great agreement between the calibration plots and prognostic predictions in this model. The areas under the receiver operating characteristic (ROC) curve (AUCs) at 1, 3, and 5 years were 0.792, 0.804, and 0.843, respectively. This model also showed good predictive ability regarding the tumor microenvironment and tumor mutation burden. In addition, the high-risk group was more sensitive to eight therapeutic agents, and the low-risk group was more responsive to five therapeutic agents. Sixteen immune checkpoints were significantly different between the two risk groups. Conclusion Our eight DEOSlncRNA risk models provide new insights into predicting prognosis and clinical progression in BCa patients.

Identification of a dysregulated CircRNA-associated gene signature for predicting prognosis, immune landscape, and drug candidates in bladder cancer.

Increasing evidences have demonstrated that circular RNA (circRNAs) plays a an essential regulatory role in initiation, progression and immunotherapy resistance of various cancers. However, circRNAs have rarely been studied in bladder cancer (BCa). The purpose of this research is to explore new circRNAs and their potential mechanisms in BCa. A novel ceRNA-regulated network, including 87 differentially expressed circRNAs (DE-circRNAs), 126 DE-miRNAs, and 217 DE-mRNAs was constructed to better understanding the biological processes using Cytoscape 3.7.1 based on our previously high-throughput circRNA sequencing and five GEO datasets. Subsequently, five randomly selected circRNAs (upregulated circ_0001681; downregulated circ_0000643, circ_0001798, circ_0006117 and circ_0067900) in 20 pairs of BCa and paracancerous tissues were confirmed using qRT-PCR. Functional analysis results determined that 772 GO functions and 32 KEGG pathways were enriched in the ceRNA network. Ten genes (PFKFB4, EDNRA, GSN, GAS1, PAPPA, DTL, TGFBI, PRSS8, RGS1 and TCF4) were selected for signature construction among the ceRNA network. The Human Protein Atlas (HPA) expression of these genes were consistent with the above sequencing data. Notably, the model was validated in multiple external datasets (GSE13507, GSE31684, GSE48075, IMvigor210 and GSE32894). The immune-infiltration was evaluated by 7 published algorithms (i.e., TIMER, CIBERSORT, CIBERSORT-ABS, QUANTISEQ, MCPCOUNTER, XCELL and EPIC). Next, Correlations between riskscore or risk groups and clinicopathological data, overall survival, recognized immunoregulatory cells or common chemotherapeutic agents of BCa patients were performed using wilcox rank test, chi-square test, cox regression and spearman’s correlation analysis; and, these results are significant. According to R package “GSVA” and “clusterProfiler”, the most significantly enriched HALLMARK and KEGG pathway was separately the ‘Epithelial Mesenchymal Transition’ and ‘Ecm Receptor Interaction’ in the high- vs. low-risk group. Additionally, the functional experiments in vitro also revealed that the overexpression of has_circ_0067900 significantly impaired the proliferation, migration, and invasion capacities of BCa cells. Collectively, the results of the current study provide a novel landscape of circRNA-associated ceRNA-regulated network in BCa. The ceRNA-associated gene model which was constructed presented a high predictive performance for the prognosis, immunotherapeutic responsiveness, and chemotherapeutic sensitivity of BCa. And, has_circ_0067900 was originally proposed as tumor suppressor for patients with BCa.

Revealing prognostic and tumor microenvironment characteristics of cuproptosis in bladder cancer by genomic analysis.

Objectives: Bladder cancer (BLCA) is the most common malignant tumor in the urinary system, while the prognosis of muscle-invasive bladder cancer (MIBC) is poor. Cuproptosis might be a promising therapeutic approach to trigger tumor cell death. This study aimed to figure out the role of cuproptosis in BLCA and constructed a new cuproptosis scoring system to guide clinical diagnosis and individualize treatments. Methods: Consensus clustering was used to classify 490 patients with BLCA from TCGA and GEO cohorts. Survival outcomes and functional enrichment analyses were performed between the different subtypes. The cuproptosis scoring system was constructed by LASSO-Cox analysis. ESTIMATE, CIBERSORT, and ssGSEA were used to investigate the tumor microenvironment (TME). Drug sensitivity was evaluated with pRRophetic. An immunotherapy cohort was used to investigate the treatment response. The cuproptosis scoring system was verified in our own cohort with quantitative real-time PCR. Results: An overview of 12 cuproptosis genes (CuGs) in the TCGA database was depicted. Based on the mRNA expression profiles of CuGs, patients were classified into two cuproptosis molecular patterns. Based on the differential genes between the two cuproptosis patterns, the patients were classified into two cuproptosis gene clusters. There were distinct survival outcomes, signaling pathways, and TME between the two subtypes. A 7-gene cuproptosis scoring system was constructed. Patients with high cuproptosis scores showed worse OS and more immunosuppressing TME than those with low cuproptosis scores. The two cuproptosis score groups had distinct mutation profiles. Patients with high cuproptosis scores tended to be sensitive to chemotherapy drugs, but insensitive to immune checkpoint inhibitors (ICIs) treatment. Conclusion: This study depicted the landscape of cuproptosis in BLCA. We constructed a cuproptosis scoring system to predict the prognosis of BLCA patients. There were significant differences in survival outcomes, TME, mutation profiles, and drug sensitivities in high and low cuproptosis score patients. The cuproptosis scoring system could help oncologists comprehensively understand the tumor characteristic of BLCA and make individualized treatment strategies.

Treatment decisions of bladder cancer in patients older than 85 years: a SEER-based analysis 2011-2015.

To compare the survival outcomes of patients over 85 years of age with bladder cancer. We used data collected from the Surveillance, Epidemiology, and End Results (SEER) database. Kaplan-Meier (KM) curves were generated for overall survival with 95% confidence intervals (CIs). Cox proportional hazard models were used to estimate the hazard ratios among cases in different groups. Of the 9,321 patients who met the inclusion criteria, 6,703 (71.9%) were men and 2,618 (28.1%) were women, with a mean (standard deviation) age of 88.68 (3.216) years. The median follow-up time of this cohort was 18 months. In the low-grade non-muscle-invasive bladder cancer (LG NMIBC) group, our analysis showed that no further treatment led to a better prognosis after the first transurethral bladder tumor resection (TURBT). In the high-grade NMIBC (HG NMIBC) cohort, major therapy was correlated with better OS in univariable and multivariable analyses [hazard ratio (HR) 0.450; 95% CI: 0.351-0.577]. Trimodal therapy gave a better prognosis in the muscle-invasive bladder cancer (MIBC) cohort (HR 1.395; 95% CI: 1.147-1.697). In addition, none of the county factors were risk factors for prognosis in multivariable analysis. Minor and major therapies do not have a better prognosis after TURBT in LG NMIBC. Major therapy has better oncological outcomes in LG NMIBC and MIBC than minor therapy. Trimodal therapy leads to longer OS in MIBC. In addition, none of the county factors were risk factors for prognosis.