Role and efficacy of current biomarkers in bladder cancer

Biomarkers for predicting bladder cancer therapy response

The advent of precision medicine has underscored the importance of biomarkers in predicting therapy response for bladder cancer, a malignancy marked by considerable heterogeneity. This review critically examines the current landscape of biomarkers to forecast treatment outcomes in bladder cancer patients. We explore a range of biomarkers, including genetic, epigenetic, proteomic, and transcriptomic indicators, from multiple sample sources, including urine, tumor tissue and blood, assessing their efficacy in predicting responses to chemotherapy, immunotherapy, and targeted therapies. Despite promising developments, the translation of these biomarkers into clinical practice faces significant challenges, such as variability in biomarker performance, the necessity for large-scale validation studies, and the integration of biomarker testing into routine clinical workflows. We also highlight the need for standardized methodologies and robust assays to ensure consistency and reliability. Future directions point towards longitudinal studies and the development of combination biomarker panels to enhance predictive accuracy. This review emphasizes the transformative potential of predictive biomarkers in improving patient outcomes and advocates for continued collaborative efforts to overcome existing barriers in this rapidly evolving field.

Combined expression of JHDM1D/KDM7A gene and long non-coding RNA RP11-363E7.4 as a biomarker for urothelial cancer prognosis

Bladder cancer is the tenth most frequently diagnosed cancer globally. Classification of high- or low-grade tumors is based on cytological differentiation and is an important prognostic factor. LncRNAs regulate gene expression and play critical roles in the occurrence and development of cancer, however, there are few reports on their diagnostic value and co-expression levels with genes, which may be useful as specific biomarkers for prognosis and therapy in bladder cancer. Thus, we performed a marker lesion study to investigate whether gene/lncRNA expression in urothelial carcinoma tissues may be useful in differentiating low-grade and high-grade tumors. RT-qPCR was used to evaluate the expression of the JHDM1D gene and the lncRNAs CTD-2132N18.2, SBF2-AS1, RP11-977B10.2, CTD-2510F5.4, and RP11-363E7.4 in 20 histologically diagnosed high-grade and 10 low-grade tumors. A protein-to-protein interaction network between genes associated with JHDM1D gene was constructed using STRING website. The results showed a moderate (positive) correlation between CTD-2510F5.4 and CTD2132N18.2. ROC curve analyses showed that combined JHDM1D and RP11-363E7.4 predicted tumor grade with an AUC of 0.826, showing excellent accuracy. In conclusion, the results indicated that the combined expression of JHDM1D and RP11-363E7.4 may be a prognostic biomarker and a promising target for urothelial tumor therapy.

Identification and validation of prognostic signature genes of bladder cancer by integrating methylation and transcriptomic analysis

Being a frequent malignant tumor of the genitourinary system, Bladder Urothelial Carcinoma (BLCA) has a poor prognosis. This study focused on identifying and validating prognostic biomarkers utilizing methylation, transcriptomics, and clinical data from The Cancer Genome Atlas Bladder Urothelial Carcinoma (TCGA BLCA) cohort. The impact of altered differentially methylated hallmark pathway genes was subjected to clustering analysis to observe changes in the transcriptional landscape on BLCA patients and identify two subtypes of patients from the TCGA BLCA population where Subtype 2 was associated with the worst prognosis with a p-value of 0.00032. Differential expression and enrichment analysis showed that subtype 2 was enriched in immune-responsive and cancer-progressive pathways, whereas subtype 1 was enriched in biosynthetic pathways. Following, regression and network analyses revealed Epidermal Growth Factor Receptor (EGFR), Fos-related antigen 1 (FOSL1), Nuclear Factor Erythroid 2 (NFE2), ADP-ribosylation factor-like protein 4D (ARL4D), SH3 domain containing ring finger 2 (SH3RF2), and Cadherin 3 (CDH3) genes to be the most significant prognostic gene markers. These genes were used to construct a risk model that separated the BLCA patients into high and low-risk groups. The risk model was also validated in an external dataset by performing survival analysis between high and low-risk groups with a p-value < 0.001 and the result showed the high group was significantly associated with poor prognosis compared to the low group. Single-cell analyses revealed the elevated level of these genes in the tumor microenvironment and associated with immune response. High-grade patients also tend to have a high expression of these genes compared to low-grade patients. In conclusion, this research developed a six-gene signature that is pertinent to the prediction of overall survival (OS) and might contribute to the advancement of precision medicine in the management of bladder cancer.

A transcriptome study of p53-pathway related prognostic gene signature set in bladder cancer

p53 pathway is important in tumorigenesis. However, no study has been performed to specifically investigate the role of p53 pathway genes in bladder cancer (BLCA). In this study, transcriptomics data of muscle invasive bladder cancer patients (n = 411) from The Cancer Genome Atlas (TCGA) were investigated. Using the hallmark p53 pathway gene set, the Non-Negative Matrix factorization (NMF) analysis identified two subtypes (C1 and C2). Clinical, survival, and immunological analysis were done to validate distinct characteristics of the subtypes. Pathway enrichment analysis showed the subtype C1 with poor prognosis having enrichment in genes of the immunity related pathways, where C2 subtype with better prognosis being enriched in genes of the steroid synthesis and drug metabolism pathways. A signature gene set consisting of MDGA2, GNLY, GGT2, UGT2B4, DLX1, and DSC1 was created followed by a risk model. Their expressions were analyzed in RNA extracted from the blood and matched tumor tissues of BLCA patients (n = 10). DSC1 had significant difference of expression (p = 0.005) between the blood and tumor tissues in our BLCA samples. Contrary to the usual normal bladder tissue to blood ratio, DLX1 expression was lower (p = 0.02734) in tumor tissues than in blood. Being the first research of p53 pathway related signature gene set in bladder cancer, this study potentially has a substantial impact on the development of biomarkers for BLCA.

Diagnostic Performance of Biomarkers for Bladder Cancer Detection Suitable for Community and Primary Care Settings: A Systematic Review and Meta-Analysis

Evidence on the use of biomarkers to detect bladder cancer in the general population is scarce. This study aimed to systematically review evidence on the diagnostic performance of biomarkers which might be suitable for use in community and primary care settings [PROSPERO Registration: CRD42021258754]. Database searches on MEDLINE and EMBASE from January 2000 to May 2022 resulted in 4914 unique citations, 44 of which met inclusion criteria. Included studies reported on 112 biomarkers and combinations. Heterogeneity of designs, populations and outcomes allowed for the meta-analysis of three biomarkers identified in at least five studies (NMP-22, UroVysion, uCyt+). These three biomarkers showed similar discriminative ability (adjusted AUC estimates ranging from 0.650 to 0.707), although for NMP-22 and UroVysion there was significant unexplained heterogeneity between included studies. Narrative synthesis revealed the potential of these biomarkers for use in the general population based on their reported clinical utility, including effects on clinicians, patients, and the healthcare system. Finally, we identified some promising novel biomarkers and biomarker combinations (N < 3 studies for each biomarker/combination) with negative predictive values of ≥90%. These biomarkers have potential for use as a triage tool in community and primary care settings for reducing unnecessary specialist referrals. Despite promising emerging evidence, further validation studies in the general population are required at different stages within the diagnostic pathway.

Evaluation of DNA methylation in promoter regions of hTERT, TWIST1, VIM and NID2 genes in Moroccan bladder cancer patients

Promoter hypermethylation have been reported to play a key role in bladder cancer development and progression. The aim of this study is to evaluate the methylation status of hTERT, TWIST1, VIM and NID2 genes in bladder cancer. The methylation status was evaluated using the Methylation-Specific PCR (MSP) approach on 70 tumour biopsies from Moroccan bladder cancer patients. Overall, methylation frequencies of hTERT, TWIST1, VIM and NID2 genes, were 90%, 85.71%, 67.14% and 67.14%, respectively. Hypermethylation of all studied genes was found in all pathological grades and stages of bladder cancer. Nevertheless, statistical analysis showed no significant association between promoter methylation of hTERT, TWIST1, VIM and NID2 genes and tumours stage/grade (p value >0.05). Moreover, we have investigated the association between the methylation pattern of selected genes and the treatment outcome in a sub-group of non-muscle-invasive bladder cancer cases (52/70). Hypermethylation of hTERT, TWIST1, VIM and NID2 was detected in 83.34%; 66.67%; 83.34% and 58.34% of recurrent cases, respectively, and in 80%; 80%; 80% and 60% of progressive cases, respectively. Statistical analysis highlighted a significant association between TWIST1 hypermethylation and tumour recurrence (p = 0.041<0.05). Our results indicate that hypermethylation of hTERT, TWIST1, VIM and NID2 genes is a frequent epigenetic event in bladder cancer and could be a promising therapeutic target to prevent bladder cancer progression and metastasis.

Preparation, characterization and evaluation of [125I]-pirarubicin: A new therapeutic agent for urinary bladder cancer with potential for use as theranostic agent

Improving urinary bladder cancer diagnosis, follow-up, and therapy tools to overcome existing limitations and increase survival rates is a highly desirable goal. In the current investigation, pirarubicin, a new generation antineoplastic anthracycline, was labeled with [¹²⁵I] via an electrophilic substitution reaction. The reaction parameters were studied to optimize the iodination process. The labeled compound showed high radiochemical yield (98.5 ± 2.1%) and consistently remained above 90% for more than 20 h at room temperature and in the presence of serum at 37 °C. The binding of [¹²⁵I]-pirarubicin to its target DNA-human topoisomerase II complex was assessed in-silico. The in-vitro tracer uptake by cancer cells was high and reached saturation (88.4 ± 2.3%) after 3 h with nuclei to cells ratio of 40 ± 1.2%. The labeled compound antiproliferative effect was much stronger than the unlabelled pirarubicin, as cleared by the growth inhibition test. Radiotoxicity improved cancer cells drug cytotoxicity. The in-vivo evaluation results showed that the [¹²⁵I]-pirarubicin tends to preferentially accumulate in urinary bladder cancerous tissues.

Identification of a Prognostic Signature Associated With the Homeobox Gene Family for Bladder Cancer

Background: Bladder cancer (BLCA) is a common malignant tumor of the genitourinary system, and there is a lack of specific, reliable, and non-invasive tumor biomarker tests for diagnosis and prognosis evaluation. Homeobox genes play a vital role in BLCA tumorigenesis and development, but few studies have focused on the prognostic value of homeobox genes in BLCA. In this study, we aim to develop a prognostic signature associated with the homeobox gene family for BLCA. Methods: The RNA sequencing data, clinical data, and probe annotation files of BLCA patients were downloaded from the Gene Expression Omnibus database and the University of California, Santa Cruz (UCSC), Xena Browser. First, differentially expressed homeobox gene screening between tumor and normal samples was performed using the "limma" and robust rank aggregation (RRA) methods. The mutation data were obtained with the "TCGAmutation" package and visualized with the "maftools" package. Kaplan-Meier curves were plotted with the "survminer" package. Then, a signature was constructed by logistic regression analysis. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed using "clusterProfiler." Furthermore, the infiltration level of each immune cell type was estimated using the single-sample gene set enrichment analysis (ssGSEA) algorithm. Finally, the performance of the signature was evaluated by receiver-operating characteristic (ROC) curve and calibration curve analyses. Results: Six genes were selected to construct this prognostic model: TSHZ3, ZFHX4, ZEB2, MEIS1, ISL1, and HOXC4. We divided the BLCA cohort into high- and low-risk groups based on the median risk score calculated with the novel signature. The overall survival (OS) rate of the high-risk group was significantly lower than that of the low-risk group. The infiltration levels of almost all immune cells were significantly higher in the high-risk group than in the low-risk group. The average risk score for the group that responded to immunotherapy was significantly lower than that of the group that did not. Conclusion: We constructed a risk prediction signature with six homeobox genes, which showed good accuracy and consistency in predicting the patient's prognosis and response to immunotherapy. Therefore, this signature can be a potential biomarker and treatment target for BLCA patients.