Integrated bioinformatics investigation of adenylyl cyclase family co-expression network in bladder cancer followed by preliminary validation of member 2 (ADCY2) in tumorigenesis and prognosis.

Background: The adenylyl cyclase (ADCY) gene family encodes enzymes responsible for the synthesis of cyclic adenosine monophosphate (cAMP) from adenosine triphosphate (ATP), which comprises nine transmembrane isoforms (ADCYs 1-9). Although ADCYs correlate with intracellular signalling and tumorigenesis in different malignancies, their roles in bladder cancer remain unclear. Methods: Utilizing the bladder urothelial carcinoma (BLCA) dataset from The Cancer Genome Atlas (TCGA), we employed the R package 'limma' to identify differential genes. Subsequent correlation analysis with corresponding clinical data was conducted. Prognostic significance of ADCY family genes was assessed through survival analysis. Univariate and multivariate Cox regression determined ADCY2 as a potential independent risk factor for BLCA. Validation was performed using immunohistochemistry results from independent cohorts. Additionally, we delved into the mechanism of genetic variations, methylation modifications, and signalling pathways of ADCY family genes. Evaluation of their role in the immune microenvironment was achieved through R packages single-sample gene set enrichment analysis (ssGSEA), CIBERPORT, and ESTIMATE. Results: Cases of bladder cancer were retrieved from TCGA, and the transcriptionally differentially expressed members of ADCY were identified (members 2, 4, and 5). Genomic alteration, epigenomic modification, clinicopathological characteristics and clinical survival were systematically investigated. A co-expression network was established based on the intersection of correlated genes, which was centred around ADCY2, ADCY4, and ADCY5. Enrichment analysis revealed that correlated genes were involved in epithelial-mesenchymal transition (EMT). The ADCY2 was selected as the most representative biomarker for prognosis in bladder cancer. Bladder tumour with higher ADCY2 expression had higher prognostic risk and worse survival outcomes. Moreover, ADCY2 was correlated with classic immune checkpoints, and a better responsiveness to immunotherapy was exhibited in high-expression subsets. To ameliorate universality of the conclusion, our study also included several real-world cohorts into the preliminary validation, using datasets from the Gene Expression Omnibus (GEO; GSE13507), tissue microarray (TMA) with 80 bladder cancer inclusion and clinical trial IMvigor210, which were associated with immunotherapy sensitivity, prognosis, and common biomarker presentation. Conclusions: Our study reveals that ADCY family has prognostic value in patients with bladder cancer; the ADCY2 is a prominent prognostic biomarker. The bioinformatics analyses and validation provide direction for further functional and mechanistic studies on the screened members of ADCY family.

Identification and Development of Inflammatory Response-Related Genes Signature Associated With Prognosis Evaluation and Immune Status of Bladder Cancer.

Background: Bladder urothelial carcinoma (BLCA) is one of the most common malignant tumors with high morbidity and recurrence rate. The study aims to establish a prediction model to elaborate the relation between inflammatory response and prognosis of BLCA and thus to evaluate the potential prognostic value of inflammatory response-related genes (IRGs) in therapeutic choices. Methods: The study utilized the gene expression profiles from the The Cancer Genome Atlas and Gene Expression Omnibus (GSE32894) datasets. Differentially expressed IRGs between normal and tumor tissues were identified, and 10 of them were correlated with overall survival (OS) (p < 0.05). Then, the LASSO-Cox regression analysis was applied to optimize the signature. RNA sequencing data of patients with BLCA from GSE32894 were applied as a validation set. Cox regression analyses of the seven-gene signature were performed to examine the efficiency of signature in predicting prognosis. Receiver operating characteristic curve analysis was applied to measure the predictive performance of the risk score for OS. Analysis of independent prognostic factors, downstream functional enrichment, drug sensitivity, and immune features were included in this study. Results: The IRG signature (LDLR, ROS1, MMP14, TNFAIP6, MYC, PTGER4, and RIPK2) was used to divide patients into high- and low-risk groups. Cox regression analyses revealed that the risk score was an independent predictive factor. Functional enrichment analysis revealed that genes were enriched in prognosis-related molecular functions and immune-related biological processes. Drug sensitivity and tumor microenvironment correlation analysis indicated that the signature was related to immunotherapy effect. Conclusion: The study defined a new prognostic signature consisting of seven IRGs, which could effectively predict the prognosis of patients with BLCA and reveal relationship of immune features in BLCA with different risk scores. The study also provided a possible indicator for targeted therapy.

AIM2 inflammasome activation benefits the therapeutic effect of BCG in bladder carcinoma.

A large proportion of bladder cancer (BLCA) patients suffer from malignant progression to life-threatening muscle-invasive bladder cancer (MIBC). Inflammation is a critical event in cancer development, but little is known about the role of inflammation in BLCA. In this study, the expression of the innate immune sensor AIM2 is much lower in high-grade BLCA and positively correlates with the survival rates of the BLCA patients. A novel AIM2 overexpressed BLCA model is proposed to investigate the impact of AIM2 on BLCA development. Mice inoculated with AIM2-overexpressed cells show tumor growth delay and prolonged survival compared to the control group. Meanwhile, CD11b+ cells significantly infiltrate AIM2-overexpressed tumors, and AIM2-overexpression in 5637 cells enhanced the inflammasome activation. In addition, oligodeoxynucleotide (ODN) TTAGGG (A151), an AIM2 inflammasome inhibitor, could abolish the elevation of AIM2-induced cleavage of inflammatory cytokines and pyroptosis. Orthotopic BLCA by AIM2-overexpressed cells exhibits a better response to Bacillus Calmette-Guérin (BCG) immunotherapy. Overall, AIM2 inflammasome activation can inhibit the BLCA tumorigenesis and enhance the therapeutic effect of BCG in BLCA. This study provides new insights into the anti-tumor effect of AIM2 inflammasome activation in BLCA and the immunotherapeutic strategy of BLCA development.

Recognition of Glycometabolism-Associated lncRNAs as Prognosis Markers for Bladder Cancer by an Innovative Prediction Model.

The alteration of glycometabolism is a characteristic of cancer cells. Long non-coding RNAs (lncRNAs) have been documented to occupy a considerable position in glycometabolism regulation. This research aims to construct an effective prediction model for the prognosis of bladder cancer (BC) based on glycometabolism-associated lncRNAs (glyco-lncRNAs). Pearson correlation analysis was applied to get glyco-lncRNAs, and then, univariate cox regression analysis was employed to further filtrate survival time-associated glyco-lncRNAs. Multivariate cox regression analysis was utilized to construct the prediction model to divide bladder cancer (BC) patients into high- and low-risk groups. The overall survival (OS) rates of these two groups were analyzed using the Kaplan-Meier method. Next, gene set enrichment analysis and Cibersortx were used to explore the enrichment and the difference in immune cell infiltration, respectively. pRRophetic algorithm was applied to explore the relation between chemotherapy sensitivity and the prediction model. Furthermore, reverse transcriptase quantitative polymerase chain reaction was adopted to detect the lncRNAs constituting the prediction signature in tissues and urine exosomal samples of BC patients. A powerful model including 6 glyco-lncRNAs was proposed, capable of suggesting a risk score for each BC patient to predict prognosis. Patients with high-risk scores demonstrated a shorter survival time both in the training cohort and testing cohort, and the risk score could predict the prognosis without depending on the traditional clinical traits. The area under the receiver operating characteristic curve of the risk score was higher than that of other clinical traits (0.755 > 0.640, 0.485, 0.644, or 0.568). The high- and low-risk groups demonstrated very distinct immune cells infiltration conditions and gene set enriched terms. Besides, the high-risk group was more sensitive to cisplatin, docetaxel, and sunitinib. The expression of lncRNA AL354919.2 featured with an increase in low-grade patients and a decrease in T3-4 and Stage III-IV patients. Based on the experiment results, lncRNA AL355353.1, AC011468.1, and AL354919.2 were significantly upregulated in tumor tissues. This research furnishes a novel reference for predicting the prognosis of BC patients, assisting clinicians with help in the choice of treatment.