Microsatellite Instability Analysis (MSA) for Bladder Cancer: Past History and Future Directions

Clinical features and oncological outcomes of bladder cancer microsatellite instability

OBJECTIVES

Excellent anticancer effect for solid tumors with microsatellite instability (MSI)-high by anti-PD-1 antibody has been reported. In this study, we investigated the clinical impact of MSI status in bladder cancer.

METHODS

This study included 205 Japanese patients who underwent transurethral resection for bladder cancer between 2005 and 2021. The prevalence rates of microsatellite stable (MSS), MSI-low (MSI-L), and MSI-high (MSI-H) were determined using molecular testing. We examined the association of MSI status (MSS versus MSI-L/H) with clinicopathological characteristics and oncological outcomes.

RESULTS

MSI-L/H tumors were associated with higher T-category in non-muscle invasive bladder cancer (NMIBC). Additionally, MSI-L/H tumors were associated with a higher risk of intravesical recurrence in NMIBC patients treated with intravesical bacillus Calmette-Guérin (BCG) but not with non-BCG therapy.

CONCLUSIONS

This study suggested that the MSI status might serve as a predictive marker for intravesical recurrence after BCG intravesical therapy in NMIBC and highlighted an unmet need for an alternative treatment in patients with MSI-L/H tumors.

Potential molecular biomarkers for the diagnosis and prognosis of bladder cancer

Bladder cancer (BC) is a common malignant tumor of urinary system, which can be divided into muscle-invasive BC (MIBC) and nonmuscle-invasive BC (NMIBC). The number of BC patients has been gradually increasing currently. At present, bladder tumours are diagnosed and followed-up using a combination of cystoscopic examination, cytology and histology. However, the detection of early grade tumors, which is much easier to treat effectively than advanced stage disease, is still insufficient. It frequently recurs and can progress when not expeditiously diagnosed and monitored following initial therapy for NMIBC. Treatment strategies are totally different for different stage diseases. Therefore, it is of great practical significance to study new biomarkers for diagnosis and prognosis. In this review, we summarize the current state of biomarker development in BC diagnosis and prognosis prediction. We retrospectively analyse eight diagnostic biomarkers and eight prognostic biomarkers, in which CK, P53, PPARγ, PTEN and ncRNA are emphasized for discussion. Eight molecular subtype systems are also identified. Clinical translation of biomarkers for diagnosis, prognosis, monitoring and treatment will hopefully improve outcomes for patients. These potential biomarkers provide an opportunity to diagnose tumors earlier and with greater accuracy, and help identify those patients most at risk of disease recurrence.

Results Obtained from a Pivotal Validation Trial of a Microsatellite Analysis (MSA) Assay for Bladder Cancer Detection through a Statistical Approach Using a Four-Stage Pipeline of Modern Machine Learning Techniques

Several studies have shown that microsatellite changes can be profiled in urine for the detection of bladder cancer. The use of microsatellite analysis (MSA) for bladder cancer detection requires a comprehensive analysis of as many as 15 to 20 markers, based on the amplification and interpretations of many individual MSA markers, and it can be technically challenging. Here, to develop fast, more efficient, standardized, and less costly MSA for the detection of bladder cancer, we developed three multiplex-polymerase-chain-reaction-(PCR)-based MSA assays, all of which were analyzed via a genetic analyzer. First, we selected 16 MSA markers based on 9 selected publications. Based on samples from Johns Hopkins University (the JHU sample, the first set sample), we developed an MSA based on triplet, three-tube-based multiplex PCR (a Triplet MSA assay). The discovery, validation, and translation of biomarkers for the early detection of cancer are the primary focuses of the Early Detection Research Network (EDRN), an initiative of the National Cancer Institute (NCI). A prospective study sponsored by the EDRN was undertaken to determine the efficacy of a novel set of MSA markers for the early detection of bladder cancer. This work and data analysis were performed through a collaboration between academics and industry partners. In the current study, we undertook a re-analysis of the primary data from the Compass study to enhance the predictive power of the dataset in bladder cancer diagnosis. Using a four-stage pipeline of modern machine learning techniques, including outlier removal with a nonlinear model, correcting for majority/minority class imbalance, feature engineering, and the use of a model-derived variable importance measure to select predictors, we were able to increase the utility of the original dataset to predict the occurrence of bladder cancer. The results of this analysis showed an increase in accuracy (85%), sensitivity (82%), and specificity (83%) compared to the original analysis. The re-analysis of the EDRN study results using machine learning statistical analysis proved to achieve an appropriate level of accuracy, sensitivity, and specificity to support the use of the MSA for bladder cancer detection and monitoring. This assay can be a significant addition to the tools urologists use to both detect primary bladder cancers and monitor recurrent bladder cancer.

Qualification of the Microsatellite Instability Analysis (MSA) for Bladder Cancer Detection: The Technical Challenges of Concordance Analysis

Bladder cancer (here we refer to transitional carcinoma of bladder) is a major cause of morbidity and mortality in the Western world, and recent understanding of its etiology, the molecular characteristics associated with its progression, renders bladder cancer an ideal candidate for screening. Cystoscopy is invasive and sometimes carries unwanted complications, but it is the gold standard for the detection of bladder cancer. Urine cytology, while the most commonly used test as an initial screening tool, is of limited value due to its low sensitivity, particularly for low-grade tumors. Several new "molecular assays" for the diagnosis of urothelial cancer have been developed over the last two decades. Here, we have established our new bladder cancer test based on an assay established for the Early Detection Research Network (EDRN) study. As a part of the study, a quality control CLIA/College of American Pathology (CAP) accredited laboratory, (QA Lab), University of Maryland Baltimore Biomarker Reference Laboratory (UMB-BRL), performed quality assurance analysis. Quality assurance measures included a concordance study between the testing laboratory (AIBioTech), also CLIA/CAP accredited, and the QA lab to ensure that the assay was performed and the results were analyzed in a consistent manner. Therefore, following the technical transfer and training of the microsatellite analysis assay to the UMB-BRL and prior to the initiation of analysis of the clinical samples by the testing lab, a series of qualification studies were performed. This report details the steps taken to ensure qualification of the assay and illustrates the technical challenges facing biomarker validation of this kind.

Development of Multiplex Polymerase Chain Reaction (PCR)-Based MSA Assay for Bladder Cancer Detection

Several studies have shown that microsatellite changes can be profiled in the urine to detect bladder cancer. Microsatellite analysis (MSA) of bladder cancer detection requires a comprehensive analysis of up to 15-20 markers based on amplifying and interpreting many individual MSA markers, which can be technically challenging. To develop fast, efficient, standardized, and less costly MSA to detect bladder cancer, we developed three multiplex polymerase chain reaction (PCR) based MSA assays, all of which were analyzed by a genetic analyzer. First, we selected 16 MSA markers based on nine publications. We developed MSA assays based on triplet or three-tube-based multiplex PCR (Triplet MSA assay) using samples from Johns Hopkins University (JHU Sample, first set of samples). In the second set of samples (samples from six cancer patients and fourteen healthy individuals), our Triplet Assay with 15 MSA markers correctly predicted all 6/6 cancer samples to be cancerous and 14/14 healthy samples to be healthy. Although we could improve our report with more clinical information from patient samples and an increased number of cancer patients, our overall results suggest that our Triplet MSA Assay combined with a genetic analyzer is a potentially time- and cost-effective genetic assay for bladder cancer detection and has potential use as a dependable assay in patient care.

Liquid biopsy in urothelial carcinoma: Detection techniques and clinical applications

The types of urothelial carcinoma (UC) include urothelial bladder cancer and upper tract urothelial carcinoma. Current diagnostic techniques cannot meet the needs of patients. Liquid biopsy is an accurate method of determining the molecular profile of UC and is a cutting-edge and popular technique that is expected to complement existing detection techniques and benefit patients with UC. Circulating tumor cells, cell-free DNA, cell-free RNA, extracellular vesicles, proteins, and metabolites can be found in the blood, urine, or other bodily fluids and are examined during liquid biopsies. This article focuses on the components of liquid biopsies and their clinical applications in UC. Liquid biopsies have tremendous potential in multiple aspects of precision oncology, from early diagnosis and treatment monitoring to predicting prognoses. They may therefore play an important role in the management of UC and precision medicine.

Apoptosis related genes mediated molecular subtypes depict the hallmarks of the tumor microenvironment and guide immunotherapy in bladder cancer

Apoptosis has been discovered as a mechanism of cell death. The purpose of this study is to identify the diagnostic signature factors related to bladder cancer (BLCA) through apoptosis related genes (ARGs). Clinicopathological parameters and transcriptomics data of 1,440 BLCA patients were obtained from 7 datasets (GSE13507, GSE31684, GSE32548, GSE32894, GSE48075, TCGA-BLCA, and IMvigor210). We first identified prognosis-related ARGs in BLCA and used them to construct two ARGs molecular subtypes by using consensus clustering algorithm. By using principal component analysis algorithms, a ARGscore was constructed to quantify the index of individualized patient. High ARGscore correlated with progressive malignancy and poor outcomes in BLCA patients. High ARGscore was associated with higher immune cell, higher estimate scores, higher stromal scores, higher immune scores, higher immune checkpoint, and lower tumor purity, which was consistent with the "immunity tidal model theory". Preclinically, BLCA immunotherapy cohorts confirmed patients with low ARGscore demonstrated significant therapeutic advantages and clinical benefits. These findings contribute to our understanding of ARGs and immunotherapy in BLCA. The ARGscore is a potentially useful tool to predict the prognosis and immunotherapy in BLCA.

CDKN3 Overcomes Bladder Cancer Cisplatin Resistance via LDHA-Dependent Glycolysis Reprogramming

Background

Aerobic glycolysis plays an important role in bladder cancer (BLCA) progression and chemoresistance. Cyclin-dependent kinase inhibitor-3 (CDKN3), a dual-specificity protein tyrosine phosphatase, has aberrant upregulation in multiple cancer types and is associated with tumorigenesis. However, the role of CDKN3 in BLCA progression and glycolysis has not been elucidated.

Purpose

In this study, we investigated the effect and underlying mechanisms of CDKN3 on bladder cancer chemoresistance.

Results

This study confirmed that CDKN3 was overexpressed in BLCA tissues and promoted proliferation and migration. Additionally, our results showed a CDKN3-dependent mechanism on chemoresistance; chemoresistance cells were transformed into chemosensitivity cells by CDKN3 knockdown. Additionally, we showed that CDKN3 knockdown decreased glycolysis by inhibiting LDHA expression in BLCA chemoresistance cells. The results also proved that LDHA was an important mediator of CDKN3-regulated BLCA resistance. LDHA overexpression reversed glycolysis inhibition and chemosensitivity induced by CDKN3 downregulation.

Conclusion

These data collectively identified a vital role of CDKN3 in glycolysis and chemoresistance by regulating LDHA expression in BLCA cells, providing a possible therapeutic strategy for treating BLCA.