Recent development of urinary biomarkers for bladder cancer diagnosis and monitoring

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.

Mapping the chromothripsis landscape in urothelial carcinoma unravels great intratumoral and intertumoral heterogeneity

Chromothripsis, a hallmark of cancer, is characterized by extensive and localized DNA rearrangements involving one or a few chromosomes. However, its genome-wide frequency and characteristics in urothelial carcinoma (UC) remain largely unknown. Here, by analyzing single-regional and multi-regional whole-genome sequencing (WGS), we present the chromothripsis blueprint in 488 UC patients. Chromothripsis events exhibit significant intertumoral heterogeneity, being detected in 41% of UC patients, with an increase from 30% in non-muscle-invasive disease (Ta/1) to 53% in muscle-invasive disease (T2-4). The presence of chromothripsis correlates with an unstable cancer genome and poor clinical outcomes. Analysis of multi-regional WGS data from 52 patients revealed pronounced intratumoral heterogeneity with chromothripsis events detectable only in specific tumor regions rather than uniformly across all areas. Chromothripsis events evolve under positive selection and contribute to tumor dissemination. This study presents a comprehensive genome-wide chromothripsis landscape in UC, highlighting the significance of chromothripsis in UC development.

Hydrogel-Based Microdroplet Ensembles Encapsulating Multiplexed EXPAR Assays for Trichromic Digital Profiling of MicroRNAs and in-Depth Classification of Primary Urethral Cancers

The primary challenge in microarray-based biological analysis lies in achieving the sensitive and specific detection of single-molecule targets while ensuring high reproducibility. A user-friendly digital imaging platform has been developed for the encoded trichromic profiling of circulating microRNAs (miRNAs). This platform replaces the traditional exponential polymerase amplification reaction (EXPAR) conducted on the microliter scale with a system that confines the amplification process within thousands of femtoliter-sized microdroplet reactors, cross-linked from tetra-armed poly(ethylene glycol) acrylate (Tetra-PEGA) and poly(ethylene glycol) dithiol (HS-PEG-SH), thus offering significant advantages, including minimal sample input, enhanced reactivity, and simplified analytical procedures. The quantitative analysis relies on digital counting of fluorescently positive microdroplets, each containing an individual miRNA sequence. This approach significantly reduces nonspecific amplification and improves sensitivity by over 2 orders of magnitude. The system has shown great potential in differentiating between subtypes of primary urethral carcinoma, suggesting its practical application in routine cancer diagnostics through simple urinalysis.

Over-expression of KRT17 and MDK genes at mRNA levels in urine-exfoliated cells is associated with early non-invasive diagnosis of non-muscle-invasive bladder cancer

INTRODUCTION

Current diagnostic approaches for bladder cancer (BLCA) are often invasive or lack the required sensitivity and specificity. This underscores the need for an early non-invasive diagnostic test for BLCA. This work aimed to explore the potential of molecular markers in urine-exfoliated cells for the diagnosis of non-muscle-invasive bladder cancer (NMIBC).

MATERIALS AND METHODS

Urine specimens (n = 140) were collected from NMIBC patients (n = 68) and control subjects (31 healthy volunteers and 41 non-cancer patients with common urological diseases [CUD]. Total RNA was extracted from the cells isolated from urine specimens. mRNA expression of selected genes: CDC20, KRT15, FOXM1, CXCR2, UPK1B, MDK, KRT20, and KRT17 was determined using RT-qPCR. The receiver operating characteristic (ROC) curve was then plotted to obtain the area under the curve (AUC), specificity, and sensitivity of the urinary mRNA markers.

RESULTS

The expression of CDC20, MDK, UPK1B, FOXM1, KRT17, and KRT20 was up-regulated in samples obtained from low- and high-grade pathological grades of NMIBC compared to that measured in healthy subjects. Notably, MDK and KRT17 mRNA levels in the low- and high-grade cases were substantially higher than in normal and CUD groups. The AUC of the KRT17 and MDK combination in diagnosing NMIBC was 0.92, surpassing that of single genes. The sensitivity and specificity of the KRT17 and MDK combination were 74% and 94%, respectively. In diagnosing low-grade from healthy and CUD groups, analysis of the KRT17 and MDK combination yielded AUCs of 0.94 and 0.95, respectively, with sensitivities of 85% and 97%, and specificities of 93% and 85%.

CONCLUSION

The findings of this study revealed that KRT17 and MDK together are potential urine-based biomarkers for early diagnosis of NMIBC.

Contemporary Molecular Markers for Predicting Systemic Treatment Response in Urothelial Bladder Cancer: A Narrative Review

The search for dependable molecular biomarkers to enhance routine clinical practice is a compelling challenge across all oncology fields. Urothelial bladder carcinoma, known for its significant heterogeneity, presents difficulties in predicting responses to systemic therapies and outcomes post-radical cystectomy. Recent advancements in molecular cancer biology offer promising avenues to understand the disease's biology and identify emerging predictive biomarkers. Stratifying patients based on their recurrence risk post-curative treatment or predicting the efficacy of conventional and targeted therapies could catalyze personalized treatment selection and disease surveillance. Despite progress, reliable molecular biomarkers to forecast responses to systemic agents, in neoadjuvant, adjuvant, or palliative treatment settings, are still lacking, underscoring an urgent unmet need. This review aims to delve into the utilization of current and emerging molecular signatures across various stages of urothelial bladder carcinoma to predict responses to systemic therapy.

Extrachromosomal circular DNA landscape of breast cancer with lymph node metastasis

Breast cancer (BC) is a complex disease with diverse manifestations, often resulting in lymph node metastasis (LNM) and impacting patient prognosis. Extrachromosomal circular DNA (eccDNA) has emerged as a key player in tumorigenesis, yet its contribution to BC LNM remains elusive. Here, we examined primary tumors and matched LNM tissues from 19 BC patients using the Circle-Seq method. We identified a median count of 44,682 eccDNA in primary tumor tissues and 38,057 in their paired LNM tissues. Furthermore, a ladder-like size distribution is observed in both primary tumor and LNM tissues. Meanwhile, similar repeat sequence distribution and GC content are identified from both primary tissue and LNM tissues. Finally, we found that eccDNA from both groups are flanked with palindromic trinucleotide motifs. These observations indicate that eccDNA of primary tumor and LNM tissues are from similar chromosomal origins. However, a subset of miRNA-associated eccDNA displayed selective enrichment in metastatic lesions, such as miR-6730 and miR-548AA1 genes. This observation implicates the function of miRNA-related eccDNA in the metastatic cascade. Our study uncovers the potential significance of these unique eccDNA molecules, shedding light on their role in cancer metastasis.

Active Surveillance in Non-Muscle Invasive Bladder Cancer, the Potential Role of Biomarkers: A Systematic Review

Bladder cancer (BC) is the tenth most common cause of cancer worldwide and is the thirteenth leading cause of cancer mortality. The non-muscle invasive (NMI) variant represents 75% of cases and has a mortality rate of less than 1%; however, it has a high recurrence rate. The gold standard of management is transurethral resection in the case of new lesions. However, this is associated with significant morbidity and costs, so the reduction of these procedures would contribute to reducing complications, morbidity, and the burden to the health system associated with therapy. In this clinical scenario, strategies such as active surveillance have emerged that propose to manage low-risk BC with follow-up; however, due to the low evidence available, this is a strategy that is underutilized by clinicians. On the other hand, in the era of biomarkers, it is increasingly known how to use them as a tool in BC. Therefore, the aim of this review is to provide to clinical practitioners the evidence available to date on AS and the potential role of biomarkers in this therapeutic strategy in patients with low-grade/risk NMIBC. This is the first review linking use of biomarkers and active surveillance, including 29 articles.

The Role of miRNAs to Detect Progression, Stratify, and Predict Relevant Clinical Outcomes in Bladder Cancer

Bladder cancer (BC) is one of the most common types of cancer worldwide, with significant differences in survival depending on the degree of muscle and surrounding tissue invasion. For this reason, the timely detection and monitoring of the disease are important. Surveillance cystoscopy is an invasive, costly, and uncomfortable procedure to monitor BC, raising the need for new, less invasive alternatives. In this scenario, microRNAs (miRNAs) represent attractive prognostic tools given their role as gene regulators in different biological processes, tissue expression, and their ease of evaluation in liquid samples. In cancer, miRNA expression is dynamically modified depending on the tumor type and cancer staging, making them potential biomarkers. This review describes the most recent studies in the last five years exploring the utility of miRNA-based strategies to monitor progression, stratify, and predict relevant clinical outcomes of bladder cancer. Several studies have shown that multimarker miRNA models can better predict overall survival, recurrence, and progression in BC patients than traditional strategies, especially when combining miRNA expression with clinicopathological variables. Future studies should focus on validating their use in different cohorts and liquid samples.

3D Printing for Cancer Diagnosis: What Unique Advantages Are Gained?

Cancer is a complex disease with global significance, necessitating continuous advancements in diagnostics and treatment. 3D printing technology has emerged as a revolutionary tool in cancer diagnostics, offering immense potential in detection and monitoring. Traditional diagnostic methods have limitations in providing molecular and genetic tumor information that is crucial for personalized treatment decisions. Biomarkers have become invaluable in cancer diagnostics, but their detection often requires specialized facilities and resources. 3D printing technology enables the fabrication of customized sensor arrays, enhancing the detection of multiple biomarkers specific to different types of cancer. These 3D-printed arrays offer improved sensitivity, allowing the detection of low levels of biomarkers, even in complex samples. Moreover, their specificity can be fine-tuned, reducing false-positive and false-negative results. The streamlined and cost-effective fabrication process of 3D printing makes these sensor arrays accessible, potentially improving cancer diagnostics on a global scale. By harnessing 3D printing, researchers and clinicians can enhance early detection, monitor treatment response, and improve patient outcomes. The integration of 3D printing in cancer diagnostics holds significant promise for the future of personalized cancer care.