Genes In Bladder Cancer Research Articles

MFAP3L predicts tumor microenvironment status, molecular subtypes and clinical benefit in patients with bladder cancer

Bladder cancer (BLCA), ranking as the tenth most prevalent malignancy globally, imposes a substantial public health and socio-economic challenge. Despite ongoing efforts by urologists to identify novel molecular subtypes and treatment paradigms, the intrinsic heterogeneity of BLCA continues to obstruct the efficacy of current diagnostic and therapeutic evaluations, leaving a gap in the comprehensive management of BLCA. This necessitates an in-depth investigation into the BLCA tumor microenvironment (TME) to identify pivotal molecules like MFAP3L. Our research concentrated on MFAP3L, commencing with a pan-cancer analysis of its immune profile. We discovered that MFAP3L exhibits a significant negative correlation with numerous immune components and markers in BLCA, a trend not observed in other cancer types. Within the TCGA-BLCA cohort, patients were classified into High-MFAP3L and Low-MFAP3L groups according to their MFAP3L transcript levels. Our exploration into the BLCA TME delved into immune infiltration, molecular subtype patterns, and treatment preferences within these MFAP3L groups. High MFAP3L expression was linked to favorable prognoses, luminal subtypes, and low immune infiltration, inversely associated with various immune molecules and characteristics. Additionally, high MFAP3L expressors exhibited diminished immune checkpoint levels, suggesting enhanced immunotherapy tolerance and sensitivity to oncogenic pathway targeting. Conversely, low MFAP3L expression correlated with poor outcomes, basal subtypes, increased immune infiltration, and heightened gene mutation rates, alongside sensitivity to radiotherapy, EGFR-targeted treatments, and immunotherapy. Hence, MFAP3L emerges as a critical yet underexplored gene in BLCA, offering insights into immune status within the TME and aiding in molecular subtyping and therapeutic decision-making.

Genetic Alterations in Chromatin Regulatory Genes in Upper Tract Urothelial Carcinoma and Urothelial Bladder Cancer.

Upper tract urothelial carcinoma (UTUC) and urothelial carcinoma of the bladder (UCB) share histomorphological and therapeutic features but distinct epidemiologic and clinicopathologic characteristics. We examined alterations of chromatin regulatory genes in molecular subtypes, clonal relatedness, and T-cell receptor (TCR) diversity in UTUC and UCB. Targeted next-generation sequencing or whole-exome DNA sequencing and TCR sequencing were conducted with 34 UTUC and 49 UCB specimens from 63 patients. Tumors were subtyped based on the expression of CK5 and GATA3. Results of tissue microarray of 78 muscle-invasive bladder cancer (MIBC) samples were used as prognostic factors of different subtypes of MIBC. Chromatin regulatory genes were frequently mutated in both UTUC and UCB. Rapid relapse and progression of non-MIBC are correlated with alterations of KMT2C and EP300. Frequency of alterations in chromatin regulatory genes is higher in UTUC patients with SBS22 and SBS2 signatures and lower in UCB patients with SBS2 and SBS6 signatures. GATA3 and CK5 double-positive patients with higher frequencies of SMARCA4, ARID1A, and EP300 mutations have better prognoses than patients with basal subtypes. Although UTUC and UCB in the same patient can be either clonally related or developed independently, mutated genes in chromatin pathway were enriched in the related clones. Compared to UTUC, UCB had more deleterious mutations in DNA damage repair (DDR) genes, higher levels of tumor mutation burden (TMB) and copy number variations (CNVs), as well as higher TCR clonality and lower TCR diversity. Since genetic alterations of the chromatin pathway genes are important in both UTUC and UCB, they could serve as potential biomarkers for predicting disease progression and therapeutic targets. Differences in mutation frequencies of DDR pathway, TMB, CNV, and TCR might be the contributing factors for the distinct responses to immune checkpoint inhibitor (ICI) between UTUC and UCB.

A modified model of PANoptosisto identify prognosis and immunotherapy response in bladder cancer

BackgroundCell death, including apoptosis and necrosis, collectively known as widespread apoptosis. The present study aims to investigate the mechanism of action in widespread apoptosis-related modification patterns in bladder cancer. MethodsUsing a clinical genomics database, we obtained transcriptomic data and related clinical information of bladder cancer patients. By employing the least absolute shrinkage analysis, we were able to construct a risk model and single-cell sequencing analysis of differential genes in bladder cancer. ResultsFive differentially expressed genes (TMPRSS4, TPST1, FOXD1, ELOVL4, EMP1) associated with widespread apoptosis were identified as features for predicting the prognosis of bladder cancer patients. Survival curve analysis revealed significant differences in prognosis (P<0.05). Additionally, multivariate Cox regression analysis determined the independent risk factor for bladder cancer prognosis as the risk score (P<0.001), with high confidence in the scoring model validated internally (P<0.001). Single-cell sequencing reveals high expression of CDKN2A, ERBB2, and TMPRSS4 in B cells, while HRAS is significantly expressed in fibroblasts. ConclusionPANscore, as a potential prognostic and immunotherapeutic biomarker, will provide more precise and rational basis for personalized treatment strategies

Construction and Validation of a Prognostic Model Based on Pyroptosis-related Genes in Bladder Cancer.

Bladder cancer (BCa) is a highly prevalent disease with a poor prognosis. There is no better forecasting method for it yet. Current studies demonstrate that pyroptosis is involved in the development and progression of various cancers. This study employed bioinformatics techniques to analyze the data of BCa patients obtained from the TCGA and GEO databases in order to construct a prognostic risk model. The TCGA dataset was used for the training set, and the multiple external datasets (including GSE13507, GSE31684, GSE48075, IMvigor210, and GSE32894) were applied as the validation sets. Prognostic-associated pyroptosis genes screened by univariate Cox regression analysis were utilized to construct the lasso Cox regression model. GO and KEGG analysis results identified the selected genes that are primarily involved in the inflammation and cell death processes. The related patients were grouped into low- and high-risk groups. Kaplan-Meier survival analysis was performed to compare survival differences between the risk groups. The accuracy of this risk prediction model was assessed by ROC. We also applied the Human Protein Atlas (HPA) to detect the protein expression of these genes. Subsequently, qRT-PCR was performed to verify the expression of these model genes. There are 29 pyroptosis-related genes with significant expression differences between BCa and corresponding adjacent tissues, and 11 genes (SH2D2A, CHMP4C, MRFAP1L1, GBP2, EHBP1, RAD9A, ANXA1, TMEM109, HEYL, APOL2, ORMDL1) were picked by univariate and LASSO Cox regression analysis. Immunological cell infiltration and ssGSEA results further indicated that the low and high-risk groups were substantially correlated with the immune status of BCa patients. According to TCGA and multiple external datasets, Kaplan-Meier survival curves showed the overall survival rate of the high-risk group to be decreased. ROC curves showed the model established to be accurate and reliable. Moreover, the HPA database also demonstrated the verification of the modeled genes' expression in BCa and normal bladder tissue using the HPA database. qRT-PCR results also suggested the up-regulated EHBP1 and down-regulated RAD9A mRNA expression levels to be confirmed in 15 pairs of BCa and corresponding adjacent tissues. This study presents the development and validation of a novel gene signature associated with pyroptosis, which holds the potential for predicting patient outcomes in BCa and providing insights into the immune microenvironment of BCa.

The role of autophagy dysregulation in low and high-grade nonmuscle invasive bladder cancer: A survival analysis and clinicopathological association

IntroductionBladder cancer disproportionately affects men and often presents as nonmuscle-invasive bladder cancer (NMIBC). Despite initial treatments, the recurrence and progression of NMIBC are linked to autophagy. This study investigates the expression of autophagy genes (mTOR, ULK1, Beclin1, and LC3) in low and high-grade NMIBC, providing insights into potential prognostic markers and therapeutic targets. Material and methodsA total of 115 tissue samples (n = 85 NMIBC (pTa, pT1, and CIS) and n = 30 control from BPH patients) were collected. The expression level of autophagy genes (mTOR, ULK1, Beclin1, and LC3) and their proteins were assessed in low and high-grade NMIBC, along with control tissue samples using quantitative real-time polymerase chain reaction and western blotting. Association with clinicopathological characteristics and autophagy gene expression was analyzed by multivariate and univariate survival analysis using SPSS. ResultIn high-grade NMIBC, ULK1, P = 0.0150, Beclin1, P = 0.0041, and LC3, P = 0.0014, were substantially downregulated, whereas mTOR, P = 0.0006, was significantly upregulated. The KM plots show significant survival outcomes with autophagy genes. The clinicopathological characters, high grade (P = 0.019), tumor stage (CIS P = 0.039, pT1 P = 0.018, P = 0.045), male (P = 0.010), lymphovascular invasion (P = 0.028) and autophagy genes (ULK1 P = 0.002, beclin1 (P = 0.010, P = 0.022) were associated as risk factors for survival outcome in NMIBC patients. ConclusionThe upregulated mTOR, downregulated ULK1, and beclin1 expression is linked to a high-grade, CIS and pT1 stage, resulting in poor recurrence-free survival and progression-free survival and highlights the prognostic significance of autophagy gene in nonmuscle-invasive bladder cancer.

2020TiP SOGUG-NEOWIN: A phase II, open-label, multi-centre trial evaluating the efficacy and safety of erdafitinib (ERDA) monotherapy and ERDA and cetrelimab (CET) as neoadjuvant treatment in cisplatin-ineligible patients with muscle-invasive bladder cancer (MIBC) and FGFR gene alterations

2020TiP SOGUG-NEOWIN: A phase II, open-label, multi-centre trial evaluating the efficacy and safety of erdafitinib (ERDA) monotherapy and ERDA and cetrelimab (CET) as neoadjuvant treatment in cisplatin-ineligible patients with muscle-invasive bladder cancer (MIBC) and FGFR gene alterations

Sex bias in FGFR3 somatic mutations in bladder cancer

Abstract Background Strong sex disparities have been observed among patients with bladder cancer (BCa). FGFR3 is one of the most frequently mutated genes in bladder cancer, and there are inconsistencies in its frequency in male and female patients. Methods Here, we conducted a meta-analysis comparing the FGFR3 somatic mutation frequency in men and women among 7351 patients with BCa from 18 cohorts. Results We showed that female patients had a 1.32 times higher risk of having FGFR3 somatic mutations than males. This difference was attributed to mutations occurring at the 2 most frequently mutated sites, S249 and Y375. Additionally, nonsense mutations were more likely to be found in women, whereas indel/frameshift mutations were almost exclusively found in men; however, no difference was noted for missense mutations. Conclusions A female sex bias in FGFR3 somatic mutations was observed in BCa. Well-powered individual participant data analyses addressing the possible confounding effects of other factors (eg, age, ethnicity, smoking status, muscle invasiveness, and molecular subtype), as well as analyses integrating omics and functional investigations, are warranted to further validate and explain the mechanisms of the current findings.

Exploring prognostic DNA methylation genes in bladder cancer: a comprehensive analysis

The current study aimed to investigate the status of genes with prognostic DNA methylation sites in bladder cancer (BLCA). We obtained bulk transcriptome sequencing data, methylation data, and single-cell sequencing data of BLCA from public databases. Initially, Cox survival analysis was conducted for each methylation site, and genes with more than 10 methylation sites demonstrating prognostic significance were identified to form the BLCA prognostic methylation gene set. Subsequently, the intersection of marker genes associated with epithelial cells in single-cell sequencing analysis was obtained to acquire epithelial cell prognostic methylation genes. Utilizing ten machine learning algorithms for multiple combinations, we selected key genes (METRNL, SYT8, COL18A1, TAP1, MEST, AHNAK, RPP21, AKAP13, RNH1) based on the C-index from multiple validation sets. Single-factor and multi-factor Cox analyses were conducted incorporating clinical characteristics and model genes to identify independent prognostic factors (AHNAK, RNH1, TAP1, Age, and Stage) for constructing a Nomogram model, which was validated for its good diagnostic efficacy, prognostic prediction ability, and clinical decision-making benefits. Expression patterns of model genes varied among different clinical features. Seven immune cell infiltration prediction algorithms were used to assess the correlation between immune cell scores and Nomogram scores. Finally, drug sensitivity analysis of Nomogram model genes was conducted based on the CMap database, followed by molecular docking experiments. Our research offers a reference and theoretical basis for prognostic evaluation, drug selection, and understanding the impact of DNA methylation changes on the prognosis of BLCA.

The Prognostic Hub Gene POLE2 Promotes BLCA Cell Growth via the PI3K/AKT Signaling Pathway.

BLCA is a common urothelial malignancy characterized by a high recurrence rate. Despite its prevalence, the molecular mechanisms underlying its development remain unclear. This study aimed to explore new prognostic biomarkers and investigate the underlying mechanism of bladder cancer (BLCA). The objective of this study is to identify key prognostic biomarkers for BLCA and to elucidate their roles in the disease. We first collected the overlapping DEGs from GSE42089 and TCGA-BLCA samples for the subsequent weighted gene co-expression network analysis (WGCNA) to find a key module. Then, key module genes were analyzed by the MCODE algorithm, prognostic risk model, expression and immunohistochemical staining to identify the prognostic hub gene. Finally, the hub gene was subjected to clinical feature analysis, as well as cellular function assays. In WGCNA on 1037 overlapping genes, the blue module was the key module. After a series of bioinformatics analyses, POLE2 was identified as a prognostic hub gene in BLCA from potential genes (TROAP, POLE2, ANLN, and E2F8). POLE2 level was increased in BLCA and related to different clinical features of BLCA patients. Cellular assays showed that si-POLE2 inhibited BLCA proliferation, and si-POLE2+ 740Y-P in BLCA cells up-regulated the PI3K and AKT protein levels. In conclusion, POLE2 was identified to be a promising prognostic biomarker as an oncogene in BLCA. It was also found that POLE2 exerts a promoting function by the PI3K/AKT signaling pathway in BLCA.

Identification and Validation of Prognostic Model for Tumor Microenvironment-Associated Genes in Bladder Cancer Based on Single-Cell RNA Sequencing Data Sets.

The purpose of this study was to elucidate the relationship between the tumor microenvironment (TME) and cellular diversity in bladder cancer (BLCA) progression, leveraging single-cell RNA sequencing (scRNA-seq) data to identify potential prognostic biomarkers and construct a prognostic model for BLCA. We analyzed scRNA-seq data of normal and tumor bladder cells from the Gene Expression Omnibus (GEO) database to uncover crucial markers within the bladder TME. The study compared gene expression in normal versus tumor bladder cells, identifying differentially expressed genes. These genes were subsequently assessed for their prognostic significance using patient follow-up data from The Cancer Genome Atlas. Prognostic models were constructed using Least Absolute Shrinkage and Selection Operator and multivariate Cox regression analyses, focusing on eight genes of interest. The predictive performance of the model was also tested against additional GEO data sets (GSE31684, GSE13507, and GSE32894). The prognostic model demonstrated reliable prediction of patient outcomes. Validation through gene set enrichment analysis and immune cell infiltration assessment supported the model's efficacy. The results from both the univariate and multivariate analyses suggest that the risk score is an independent prognostic factor with a hazard ratio of 2.97 (95% CI, 2.28 to 3.9, P < .001). In the validation cohort, the AUC at 1, 2, and 3 years is 0.74, 0.74, and 0.72, respectively. Our findings proposed biomarkers with prognostic potential, laying the groundwork for future in vitro validation and therapeutic exploration. This contributes to a deeper understanding of the genes associated with bladder TME and may improve prognostic precision in BLCA management.

Identification of tumor-specific T cell signature predicting cancer immunotherapy response in bladder cancer by multi-omics analysis and experimental verification

BackgroundNumerous gene signatures predicting the prognosis of bladder cancer have been identified. However, a tumor-specific T cell signature related to immunotherapy response in bladder cancer remains under investigation.MethodsSingle-cell RNA and TCR sequencing from the Gene expression omnibus (GEO) database were used to identify tumor-specific T cell-related genes in bladder cancer. Subsequently, we constructed a tumor-specific T cell signature (TstcSig) and validated its clinical relevance for predicting immunotherapy response in multiple immunotherapy cohorts. Further analyses explored the immune characteristics of TstcSig in bladder cancer patients from other cohorts in the TCGA and GEO databases. Western blot (WB), multicolor immunofluorescence (MIF), qRT-PCR and flow cytometry assays were performed to validate the results of bioinformatics analysis.ResultsThe established TstcSig, based on five tumor-specific T cell-related genes, could predict outcomes in a bladder cancer immunotherapy cohort. This was verified using two additional immunotherapy cohorts and showed better predictive performance compared to 109 published T cell signatures. TstcSig was strongly correlated with immune characteristics such as immune checkpoint gene expression, tumor mutation burden, and T cell infiltration, as validated by single-cell and spatial transcriptomics datasets. Notably, the positive correlation between TstcSig and T cell infiltration was confirmed in the TCGA cohort. Furthermore, pan-cancer analysis demonstrated the heterogeneity of the prognostic value of TstcSig. Tumor-specific T cells highly expressed CD27, IFNG, GZMB and CXCL13 and secreted more effector cytokines for tumor cell killing, as validated experimentally.ConclusionWe developed a five-gene signature (including VAMP5, TIGIT, LCK, CD27 and CACYBP) based on tumor-specific T cell-related genes to predict the immunotherapy response in bladder cancer patients.

Prognostic analysis of anoikis-related genes in bladder cancer: An observational study.

Anoikis is proved to play a crucial role in the development of cancers. However, the impact of anoikis on the prognosis of bladder cancer (BLCA) is currently unknown. Thus, this study aimed to find potential effect of anoikis in BLCA. The Cancer Genome Atlas (TCGA)-BLCA and GSE13507 cohorts were downloaded from TCGA and the Gene Expression Omnibus (GEO) databases, respectively. Differentially expressed genes (DEGs) were screened between BLCA and normal groups, which intersected with anoikis-related genes to yield anoikis-related DEGs (AR DEGs). Univariate COX, rbsurv, and multivariate COX analyses were adopted in order to build a prognostic risk model. The differences of risk score in the different clinical subgroups and the relevance between survival rate and clinical characteristics were explored as well. Finally, chemotherapy drug sensitivity in different risk groups was analyzed. In total, 78 AR DEGs were acquired and a prognostic signature was build based on the 6 characteristic genes (CALR, FASN, CSPG4, HGF, INHBB, SATB1), where the patients of low-risk group had longer survival time. The survival rate of BLCA patients was significantly differential in different groups of age, stage, smoking history, pathologic-T, and pathologic-N. The IC50 of 56 drugs showed significant differences between 2 risk groups, such as imatinib, docetaxel, and dasatinib. At last, the results of real time quantitative-polymerase chain reaction (RT-qPCR) demonstrated that the expression trend of CALR, HGF, and INHBB was consistent with the result obtained previously based on public databases. Taken together, this study identified 6 anoikis-related characteristic genes (CALR, FASN, CSPG4, HGF, INHBB, SATB1) for the prognosis of BLCA patients, providing a scientific reference for further research on BLCA.

Developing and experimental validating a B cell exhaustion-related gene signature to assess prognosis and immunotherapeutic response in bladder cancer

BackgroundB cell exhaustion (BEX) refers to the impairment of normal B cell functions and decreased proliferation capability. However, the prognostic value of BEX-related genes in bladder cancer (BLCA) remains unclear. MethodsBLCA cases from TCGA were used for training, while GSE5287, GSE13507, GSE31684, and GSE32894 cohorts from GEO were used for external validation. BEX-related genes were identified through literature retrieval, unsupervised clustering, and genomic difference detection. Gene pairing, LASSO, random forest, and Cox regression were employed to construct a predictive model. B cell samples from scRNAseqDB, GSE111636, and IMvigor210 were utilized to explore immunoprofiles and the predictive ability of the model in immunotherapeutic response. Additionally, 21 pairs of BLCA and paracarcinoma samples from Nanfang Hospital were used to re-confirm our findings through RT-qPCR, immunofluorescence, and flow cytometry. Results39 BEX-related genes were identified. A 4-gene-pair signature was constructed and served as a reliable prognostic predictor across multiple datasets (pooled HR = 2.32; 95 % CI = 1.81–2.98). The signature reflected the BEX statuses of B cells (FDR < 0.05) and showed promise in evaluating immunotherapeutic sensitivity (P < 0.001). In the local cohort, CD52, TUBB6, and CAV1 were down-regulated in BLCA tissues, while TGFBI, UBE2L6, TINAGL1, and IL32 were up-regulated (all P < 0.05). Furthermore, the infiltration levels of CD19 + CD52 + and CD19 + TUBB6 + B cells in paracarcinoma samples were higher than those in BLCA samples (all P < 0.05). ConclusionA BEX-related gene signature was developed to predict prognosis and immunotherapeutic sensitivity in BLCA, providing valuable guidance for personalized treatment.

Transcriptomic profiling and risk assessment in bladder cancer: Insights from copper death-related genes

BackgroundThe study aimed to investigate the role of copper death-related genes (CRGs) in bladder cancer (BC) for improved prognosis assessment. MethodsMulti-omics techniques were utilized to analyze CRG expression in BC tissues from TCGA and GEO databases. Consensus clustering categorized patients into molecular subtypes based on clinical characteristics and immune cell infiltration. ResultsAn innovative risk assessment model identified eight critical genes associated with BC risk. In vitro and in vivo experiments validated LIPT1's significant impact on copper-induced cell death, proliferation, migration, and invasion in BC. ConclusionThis multi-omics analysis elucidates the pivotal role of CRGs in BC progression, suggesting enhanced risk assessment through molecular subtype categorization and identification of key genes like LIPT1. Insights into these mechanisms offer the potential for improved diagnosis and treatment strategies for BC patients.

Abstract A013: Functional and clinical consequences of hotspot non-coding mutations upstream of the LEPROTL1 gene in bladder cancer

Abstract Recent whole-genome sequencing studies have unveiled intriguing hotspot mutations within non-coding genomic regions, yet their implications in cancer remain unknown. Here, we characterized the role of twin hotspot non-coding mutations upstream of the LEPROTL1 gene in bladder cancer: chr8: 29,952,919 G&amp;gt;A and chr8: 29,952,919 C&amp;gt;T. Either mutation is found in ~20% of bladder tumors, and the mutations do not typically co-occur. Through a comprehensive analysis integrating ChiP-seq, ATAC-seq, and Hi-C data from bladder cancer cell lines, we observed that these mutations co-localize with enhancer elements that interact with multiple nearby genes. In vitro dual luciferase reporter assays showed that both mutations are functional and likely affect gene expression in a genomic context. CRISPR-Cas9-mediated knocking out of the putative enhancer region identified LEPROTL1, DCTN6, and SARAF as target genes that are likely co-regulated, which was further supported by strong positive correlations of their mRNA expression in TCGA data. Isogenic cell clones generated by CRISPR-mediated base-editing showed that the mutations result in simultaneous upregulation of the three target genes, which were also expressed at higher levels in TCGA tumors harboring the non-coding mutations. Little is known about the function of LEPROTL1, DCTN6, and SARAF. Utilizing siRNA knockdown models complemented by live-cell imaging, viability assays, and cell cycle analysis, we found that they promote cell proliferation and cell cycle progression. Furthermore, our base-edited isogenic cell lines showed more rapid proliferation and cell cycle progression, as well as resistance to cisplatin. The mutations were also associated with shorter disease-specific survival in a TCGA cohort, and DCTN6 showed a negative association with overall survival. These results underscore the clinical significance of the non-coding mutations. Currently, we are assessing the effect of these mutations on tumor growth and cisplatin response in vivo using xenograft mouse models and evaluating the mechanisms by which LEPROTL1, DCTN6, and SARAF modulate cell cycle progression. Taken together, our data suggest that non-coding enhancer mutations near LEPROTL1 contribute to bladder carcinogenesis by increasing the expression of three co-regulated novel oncogenes, all of which were previously uncharacterized in bladder cancer. Since we found the mutations to be clinically significant, our study also raises the possibility of using the non-coding mutations and their target genes as clinical biomarkers and potential therapeutic drug targets. Citation Format: Kelly Butler, Bilal Lone, Alexandra Dobbins, Arup Chakraborty, Salah Boudajadi, Andrea Apolo, Rouf Banday. Functional and clinical consequences of hotspot non-coding mutations upstream of the LEPROTL1 gene in bladder cancer [abstract]. In: Proceedings of the AACR Special Conference on Bladder Cancer: Transforming the Field; 2024 May 17-20; Charlotte, NC. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(10_Suppl):Abstract nr A013.

Single-cell and bulk RNA-sequence identified fibroblasts signature and CD8 + T-cell - fibroblast subtype predicting prognosis and immune therapeutic response of bladder cancer, based on machine learning: bioinformatics multi-omics study.

Cancer-associated fibroblasts (CAFs) are found in primary and advanced tumours. They are primarily involved in tumour progression through complex mechanisms with other types of cells in the tumour microenvironment. However, essential fibroblasts-related genes (FRG) in bladder cancer still need to be explored, and there is a shortage of an ideal predictive model or molecular subtype for the progression and immune therapeutic assessment for bladder cancer, especially muscular-invasive bladder cancer based on the FRG. CAF-related genes of bladder cancer were identified by analysing single-cell RNA sequence datasets, and bulk transcriptome datasets and gene signatures were used to characterize them. Then, 10 types of machine learning algorithms were utilised to determine the hallmark FRG and construct the FRG index (FRGI) and subtypes. Further molecular subtypes combined with CD8+ T-cells were established to predict the prognosis and immune therapy response. Fifty-four BLCA-related FRG were screened by large-scale scRNA-sequence datasets. The machine learning algorithm established a 3-genes FRGI. High FRGI represented a worse outcome. Then, FRGI combined clinical variables to construct a nomogram, which shows high predictive performance for the prognosis of bladder cancer. Furthermore, the BLCA datasets were separated into two subtypes - fibroblast hot and cold types. In five independent BLCA cohorts, the fibroblast hot type showed worse outcomes than the cold type. Multiple cancer-related hallmark pathways are distinctively enriched in these two types. In addition, high FRGI or fibroblast hot type shows a worse immune therapeutic response. Then, four subtypes called CD8-FRG subtypes were established under the combination of FRG signature and activity of CD8+ T-cells, which turned out to be effective in predicting the prognosis and immune therapeutic response of bladder cancer in multiple independent datasets. Pathway enrichment analysis, multiple gene signatures, and epigenetic alteration characterize the CD8-FRG subtypes and provide a potential combination strategy method against bladder cancer. In summary, the authors established a novel FRGI and CD8-FRG subtype by large-scale datasets and organised analyses, which could accurately predict clinical outcomes and immune therapeutic response of BLCA after surgery.

Comprehensive analysis and prognostic assessment of senescence-associated genes in bladder cancer

BackgroundThe prevalence and mortality of bladder cancer (BLCA) present a significant medical challenge. While the function of senescence-related genes in tumor development is recognized, their prognostic significance in BLCA has not been thoroughly explored.MethodsBLCA transcriptome datasets were sourced from the TCGA and GEO repositories. Gene groupings were determined through differential gene expression and non-negative matrix factorization (NMF) methodologies. Key senescence-linked genes were isolated using singular and multivariate Cox regression analyses, combined with lasso regression. Validation was undertaken with GEO database information. Predictive models, or nomograms, were developed by merging risk metrics with clinical records, and their efficacy was gauged using ROC curve methodologies. The immune response’s dependency on the risk metric was assessed through the immune phenomenon score (IPS). Additionally, we estimated IC50 metrics for potential chemotherapeutic agents.ResultsReviewing 406 neoplastic and 19 standard tissue specimens from the TCGA repository facilitated the bifurcation of subjects into two unique clusters (C1 and C2) according to senescence-related gene expression. After a stringent statistical evaluation, a set of ten pivotal genes was discerned and applied for risk stratification. Validity tests for the devised nomograms in forecasting 1, 3, and 5-year survival probabilities for BLCA patients were executed via ROC and calibration plots. IC50 estimations highlighted a heightened responsiveness in the low-risk category to agents like cisplatin, cyclopamine, and sorafenib.ConclusionsIn summation, our research emphasizes the prospective utility of risk assessments rooted in senescence-related gene signatures for enhancing BLCA clinical oversight.

ALYREF m5C RNA methylation reader predicts bladder cancer prognosis by regulating the tumor immune microenvironment.

5-Methylcytidine (m5C) methylation is a recently emerging epigenetic modification that is closely related to tumor proliferation, occurrence, and metastasis. This study aimed to investigate the clinicopathological characteristics and prognostic value of m5C regulators in bladder cancer (BLCA), and their correlation with the tumor immune microenvironment. Thirteen m5C RNA methylation regulators were analyzed using RNA-sequencing and corresponding clinical information obtained from the TCGA database. The Cluster Profiler package was used to analyze the gene ontology function of potential targets and enriched the Kyoto Encyclopedia of Genes and Genomes pathway. Kaplan-Meier survival analysis was used to compare survival differences using the log-rank test and univariate Cox proportional hazards regression. The correlation between signature prognostic m5C regulators and various immune cells was analyzed. Univariate and multivariate Cox regression analyses identified independence of the ALYREF gene signature. Nine out of the 13 m5C RNA methylation regulators were differentially expressed in BLCA and normal samples and were co-expressed. These 9 regulators were associated with clinicopathological tumor characteristics, particularly high or low tumor risk, pT or pTNM stage, and migration. Consensus clustering analysis divides the BLCA samples into 4 clusters. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment annotation and gene ontology function analysis identified 273 upregulated and 594 downregulated genes in BLCA. Notably, only ALYREF was significantly correlated with OS (P < .05). ALYREF exhibited significant infiltration levels in macrophage cells. Therefore, we constructed a nomogram for ALYREF as an independent prognostic factor. Additionally, we observed that both the mRNA and protein levels of ALYREF were upregulated, and immunofluorescence showed that ALYREF was mainly distributed in nuclear speckles. ALYREF overexpression was significantly associated with poor OS. Our findings demonstrated the potential of ALYREF to predict clinical prognostic risks in BLCA patients and regulate the tumor immune microenvironment. As such, ALYREF may serve as a novel prognostic indicator in BLCA patients.

Abstract 1123: Genomic characterization of radiotherapy-associated bladder cancer

Abstract Background: Bladder cancer (BCa) is the 4th most common cancer diagnosed in men, with 82,290 new cases predicted in 2023. As BCa frequently occurs at an advanced patient age, its diagnosis may follow radiotherapy (RT) for the treatment of prostate cancer. Currently, data is limited regarding the influence of RT on the clinical course and genomic landscape of subsequent BCa, mainly due to a paucity of samples. From prior studies, pelvic radiation confers an increased risk of BCa, with resulting tumors that are largely genomically similar to non-RT tumors with the exception of an increase rate of genomic insertions. Our current study looks to expand on these findings by characterizing the genomes of the largest cohort of RT-associated bladder cancers to date. Methods: We identified BCa cases from patients with a prior history of pelvic radiation for prostate cancer, and tumor only targeted sequencing was performed using Foundation Medicine (FMI) on FFPE tissue (n=41). For control cases (CTRL), patients with no prior record of pelvic radiation and who had previously underwent standard of care FMI sequencing were included (n=41). Sequencing data were re-aligned to hg38 and mutation calling was performed on the newly aligned sequences. Results: CTRL and RT cohorts had similar distributions of patients based on race and smoking status. While cT stage was similar between the two cohorts, the CTRL cohort was biased toward higher cN and cM stages with no difference in overall survival (median OS: CTRL = 20m, RT = 23m), though the advanced stage of the CTRL cohort could mask a worse prognosis in the RT cohort. Latency specific analysis revealed short latency tumors (&amp;lt;10 years from RT) had a significantly shorter overall survival than long latency tumors (p&amp;lt;0.01, HR=5.59, CI=1.81-17.3), and a numerically, but not significantly, shorter survival than CTRL patients (p=0.17, HR=1.55, CI=0.82-2.94). Long latency tumor patients had a significantly longer overall survival than CTRL patients (p&amp;lt;0.01, HR = 0.22, CI=0.07-0.63). In line with prior studies, RT samples had increased numbers of insertions (p&amp;lt;0.01). In addition, we also detected an increase in SNVs in the RT samples (p&amp;lt;0.01). Of note, KDM6A alterations were enriched within the RT cohort (CTRL = 10/41, RT = 30/41, p&amp;lt;0.001), with series of splice site mutations exclusive to RT samples (p&amp;lt;0.001). Conclusion: Patients diagnosed with BCa within a short interval following pelvic radiation have a worse prognosis. Genomic analysis showed RT-associated tumors having an increased number of insertions, SNVs, and KDM6A splice site mutations compared to non-RT tumors. Overall, the spectrum of recurrent alterations within the cohorts were consistent with previous studies, with the exception of the KDM6A mutations. To our knowledge, this is the first report of a RT-associated alteration in a specific gene in bladder cancer and additional studies will be needed to validate and understand the consequences of this finding. Citation Format: N. Ari Wijetunga, Kathryn H. Gessner, Krishna Kanchi, Sara E. Wobker, David Corcoran, Matthew D. Galsky, Matthew I. Milowsky, William Y. Kim, Tracy L. Rose, Jeffrey S. Damrauer. Genomic characterization of radiotherapy-associated bladder cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1123.

The potential mechanism of ursolic acid in the treatment of bladder cancer based on network pharmacology and molecular docking.

This study explored the potential molecular mechanisms of ursolic acid (UA) in bladder cancer treatment using network pharmacology and molecular docking. The Traditional Chinese Medicine Systems Pharmacology and UniProt databases were used to screen potential targets of UA. Relevant bladder cancer target genes were extracted using the GeneCards database. All data were pooled and intercrossed to obtain common target genes of UA and bladder cancer. Gene Ontology functional annotation and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed. Molecular docking was conducted to verify the possible binding conformation between UA and bladder cancer cells. Then, in vitro experiments were performed to further validate the predicted results. UA exerts anti-tumor effects on bladder cancer through multiple targets and pathways. Molecular docking indicated that UA undergoes stable binding with the proteins encoded by the top six core genes (STAT3, VEGFA, CASP3, TP53, IL1B, and CCND1). The in vitro experiments verified that UA can induce bladder cancer cell apoptosis by regulating the PI3K/Akt signaling pathway. Our study illustrated the potential mechanism of UA in bladder cancer based on network pharmacology and molecular docking. The results will provide scientific references for follow-up studies and clinical treatment.