Bladder cancer recurrence surveillance by urine metabolomics analysis

New Perspectives on the Role of Liquid Biopsy in Bladder Cancer: Applicability to Precision Medicine

Bladder cancer (BC) is one of the most common tumors in the world. Cystoscopy and tissue biopsy are the standard methods in screening and early diagnosis of suspicious bladder lesions. However, they are invasive procedures that may cause pain and infectious complications. Considering the limitations of both procedures, and the recurrence and resistance to BC treatment, it is necessary to develop a new non-invasive methodology for early diagnosis and multiple evaluations in patients under follow-up for bladder cancer. In recent years, liquid biopsy has proven to be a very useful diagnostic tool for the detection of tumor biomarkers. This non-invasive technique makes it possible to analyze single tumor components released into the peripheral circulation and to monitor tumor progression. Numerous biomarkers are being studied and interesting clinical applications for these in BC are being presented, with promising results in early diagnosis, detection of microscopic disease, and prediction of recurrence and response to treatment.

Metabolomic profiling of human bladder tissue extracts

INTRODUCTION

Bladder cancer is a common malignancy affecting the urinary tract and effective biomarkers and for which monitoring therapeutic interventions have yet to be identified.

OBJECTIVES

Major aim of this work was to perform metabolomic profiling of human bladder cancer and adjacent normal tissue and to evaluate cancer biomarkers.

METHODS

This study utilized nuclear magnetic resonance (NMR) and high-resolution nanoparticle-based laser desorption/ionization mass spectrometry (LDI-MS) methods to investigate polar metabolite profiles in tissue samples from 99 bladder cancer patients.

RESULTS

Through NMR spectroscopy, six tissue metabolites were identified and quantified as potential indicators of bladder cancer, while LDI-MS allowed detection of 34 compounds which distinguished cancer tissue samples from adjacent normal tissue. Thirteen characteristic tissue metabolites were also found to differentiate bladder cancer tumor grades and thirteen metabolites were correlated with tumor stages. Receiver-operating characteristics analysis showed high predictive power for all three types of metabolomics data, with area under the curve (AUC) values greater than 0.853.

CONCLUSION

To date, this is the first study in which bladder human normal tissues adjacent to cancerous tissues are analyzed using both NMR and MS method. These findings suggest that the metabolite markers identified in this study may be useful for the detection and monitoring of bladder cancer stages and grades.

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.

Diagnostic value of the combination of DAPK methylation in urinary sediment and B ultrasound for recurrent urinary bladder cancer

BACKGROUND

Urinary bladder cancer (UBC) is the most common malignancy affecting the urinary system. This study aimed to investigate the diagnostic value of combining DAPK methylation in urinary sediment and B ultrasound in the detection of recurrent UBC.

METHODS

A total of 1021 cases with primary UBC who underwent electrocision of bladder tumor through urethra were included in this study and followed up. Various parameters including B ultrasound, DAPK methylation in urinary sediment, examination of exfoliated cells in the urine, and cystoscopy were performed. The data collected was analyzed using the Kappa test, and receiver operating characteristic (ROC) curve was constructed to assess the diagnostic role in recurrent UBC.

RESULTS

Among the 1021 patients, 115 patients experienced recurrence confirmed by cystoscopy and biopsy within two years and were excluded from the study, resulting in an effective sample size of 906 primary UBC cases. The results of cystoscopy showed agreement with B ultrasound (Kappa = 0.785, P < 0.05), as well as with DAPK methylation in urinary sediment, and the combination of B ultrasound and DAPK methylation (Kappa = 0.517, P < 0.05, Kappa = 0.593, P < 0.05). The combination of B ultrasound with DAPK methylation yielded an area under the curve of 0.922, with a sensitivity of 92.86%, specificity of 91.63%, and a negative predictive value of 99.4%, suggesting that a negative result indicates a low risk of recurrence.

CONCLUSION

The combination of DAPK methylation in urinary sediment with B ultrasound demonstrates high diagnostic performance for recurrent UBC.

Statistical methods and resources for biomarker discovery using metabolomics

Metabolomics is a dynamic tool for elucidating biochemical changes in human health and disease. Metabolic profiles provide a close insight into physiological states and are highly volatile to genetic and environmental perturbations. Variation in metabolic profiles can inform mechanisms of pathology, providing potential biomarkers for diagnosis and assessment of the risk of contracting a disease. With the advancement of high-throughput technologies, large-scale metabolomics data sources have become abundant. As such, careful statistical analysis of intricate metabolomics data is essential for deriving relevant and robust results that can be deployed in real-life clinical settings. Multiple tools have been developed for both data analysis and interpretations. In this review, we survey statistical approaches and corresponding statistical tools that are available for discovery of biomarkers using metabolomics.

Targeted and untargeted urinary metabolic profiling of bladder cancer

Bladder cancer (BC) is frequent cancer affecting the urinary tract and is one of the most prevalent malignancies worldwide. No biomarkers that can be used for effective monitoring of therapeutic interventions for this cancer have been identified to date. This study investigated polar metabolite profiles in urine samples from 100 BC patients and 100 normal controls (NCs) using nuclear magnetic resonance (NMR) and two methods of high-resolution nanoparticle-based laser desorption/ionization mass spectrometry (LDI-MS). Five urine metabolites were identified and quantified using NMR spectroscopy to be potential indicators of bladder cancer. Twenty-five LDI-MS-detected compounds, predominantly peptides and lipids, distinguished urine samples from BC and NCs individuals. Level changes of three characteristic urine metabolites enabled BC tumor grades to be distinguished, and ten metabolites were reported to correlate with tumor stages. Receiver-Operating Characteristics analysis showed high predictive power for all three types of metabolomics data, with the area under the curve (AUC) values greater than 0.87. These findings suggest that metabolite markers identified in this study may be useful for the non-invasive detection and monitoring of bladder cancer stages and grades.

Urinary microbiota and metabolic signatures associated with inorganic arsenic-induced early bladder lesions

Inorganic arsenic (iAs) contamination in drinking water is a global public health problem, and exposure to iAs is a known risk factor for bladder cancer. Perturbation of urinary microbiome and metabolome induced by iAs exposure may have a more direct effect on the development of bladder cancer. The aim of this study was to determine the impact of iAs exposure on urinary microbiome and metabolome, and to identify microbiota and metabolic signatures that are associated with iAs-induced bladder lesions. We evaluated and quantified the pathological changes of bladder, and performed 16S rDNA sequencing and mass spectrometry-based metabolomics profiling on urine samples from rats exposed to low (30 mg/L NaAsO₂) or high (100 mg/L NaAsO₂) iAs from early life (in utero and childhood) to puberty. Our results showed that iAs induced pathological bladder lesions, and more severe effects were noticed in the high-iAs group and male rats. Furthermore, six and seven featured urinary bacteria genera were identified in female and male offspring rats, respectively. Several characteristic urinary metabolites, including Menadione, Pilocarpine, N-Acetylornithine, Prostaglandin B1, Deoxyinosine, Biopterin, and 1-Methyluric acid, were identified significantly higher in the high-iAs groups. In addition, the correlation analysis demonstrated that the differential bacteria genera were highly correlated with the featured urinary metabolites. Collectively, these results suggest that exposure to iAs in early life not only causes bladder lesions, but also perturbs urinary microbiome composition and associated metabolic profiles, which shows a strong correlation. Those differential urinary genera and metabolites may contribute to bladder lesions, suggesting a potential for development of urinary biomarkers for iAs-induced bladder cancer.

LC-MS based urine untargeted metabolomic analyses to identify and subdivide urothelial cancer

Introduction

Urine metabolomics has been a promising technique in the liquid biopsy of urothelial cancer (UC). The comparison of upper tract urothelial cancer (UTUC), lower tract urothelial cancer (BCa), and healthy controls (HCs) need to be performed to find related biomarkers.

Methods

In our investigation, urine samples from 35 UTUCs, 44 BCas, and 53 gender- and age-matched HCs were analyzed using liquid chromatography-high resolution mass spectrometry (LC-HRMS). In different groups, the differential metabolites and the disturbed metabolism pathways were explored. Transcriptomics and urine metabolomics are combined to identify the probably disturbed gene in BCa.

Results

With an area under the curve (AUC) of 0.815, the panel consisting of prostaglandin I2, 5-methyldeoxycytidine, 2,6-dimethylheptanoyl carnitine, and deoxyinosine was able to discriminate UC from HCs. With an AUC of 0.845, the validation group also demonstrated strong predictive ability. UTUC and BCa without hematuria could be distinguished using the panel of 5'-methylthioadenosine, L-beta-aspartyl-L-serine, dehydroepiandrosterone sulfate, and N'-formylkynurenine (AUC=0.858). The metabolite panel comprising aspartyl-methionine, 7-methylinosine, and alpha-CEHC glucuronide could discriminate UTUC from BCa with hematuria with an AUC of 0.83. Fatty acid biosynthesis, purine metabolism, tryptophan metabolism, pentose and glucuronate interconversions, and arachidonic acid metabolism were dysregulated when comparing UC with HCs. PTGIS and BCHE, the genes related to the metabolism of prostaglandin I2 and myristic acid respectively, were significantly associated with the survival of BCa.

Discussion

Not only could LC-HRMS urine metabolomic investigations distinguish UC from HCs, but they could also identify UTUC from BCa. Additionally, urine metabolomics combined with transcriptomics can find out the potential aberrant genes in the metabolism.

Postoperative Metabolic Phenoreversion in Clear Cell Renal Cell Carcinoma

The ultimate goal of surgical treatment in cancer is to remove the tumor mass for restoring a healthy state. A 16-lipid panel that discriminated healthy controls from clear cell renal cell carcinoma (ccRCC) patients in a prior study was evaluated in the present work in paired-serum samples collected from patients (n = 41) before and after nephrectomy. Changes in the lipid and metabolite fingerprints from ccRCC patients were investigated and compared with fingerprints from healthy individuals obtained by means of ultra-performance liquid chromatography-high-resolution mass spectrometry. The lipid panel differentiated phenotypes associated with metabolic restoration after surgery, representing a serum signature of phenoreversion to a healthy metabolic state. In particular, PC 16:0/0:0, PC 18:2/18:2, and linoleic acid allowed discriminating serum samples from ccRCC patients with poor prognosis from those with an improved outcome during the follow-up period. Ratios of PC 16:0/0:0 and PC 18:2/18:2 with linoleic acid levels may contribute as prognostic tools to support decision-making during the patient follow-up care. The preliminary character of these results should be validated with larger cohorts, including subjects with different ethnicities, life style, and diets. MetaboLights study references: MTBLS1839, MTBLS3838, and MTBLS4629.

Metabolomic and elemental profiling of blood serum in bladder cancer

Bladder cancer (BC) is one of the most frequently diagnosed types of urinary cancer. Despite advances in treatment methods, no specific biomarkers are currently in use. Targeted and untargeted profiling of metabolites and elements of human blood serum from 100 BC patients and the same number of normal controls (NCs), with external validation, was attempted using three analytical methods, i.e., nuclear magnetic resonance, gold and silver-109 nanoparticle-based laser desorption/ionization mass spectrometry (LDI-MS), and inductively coupled plasma optical emission spectrometry (ICP-OES). All results were subjected to multivariate statistical analysis. Four potential serum biomarkers of BC, namely, isobutyrate, pyroglutamate, choline, and acetate, were quantified with proton nuclear magnetic resonance, which had excellent predictive ability as judged by the area under the curve (AUC) value of 0.999. Two elements, Li and Fe, were also found to distinguish between cancer and control samples, as judged from ICP-OES data and AUC of 0.807 (in validation set). Twenty-five putatively identified compounds, mostly related to glycans and lipids, differentiated BC from NCs, as detected using LDI-MS. Five serum metabolites were found to discriminate between tumor grades and nine metabolites between tumor stages. The results from three different analytical platforms demonstrate that the identified distinct serum metabolites and metal elements have potential to be used for noninvasive detection, staging, and grading of BC.

LC-MS metabolomics of urine reveals distinct profiles for non-muscle-invasive and muscle-invasive bladder cancer

PURPOSE

Bladder cancer (BC) is among the most frequent malignancies worldwide. Novel non-invasive markers are needed to diagnose and stage BC with more accuracy than invasive procedures like cystoscopy. To date, no study has identified urine metabolites characteristic of all BC stages. To discover novel urine metabolomic profiles to diagnose and stage non-muscle-invasive (NMIBC) and muscle-invasive (MIBC) patients using mass spectrometry-based metabolomics.

METHODS

We prospectively recruited 198 BC patients and 98 age- and sex-matched healthy volunteers without evidence of renal or bladder condition confirmed by ultrasound, from whom we collected a first morning urine sample (before surgery in patients). In a discovery stage, an untargeted metabolomic analysis was conducted in urine samples of a selection of 64 BC patients (19 TaG1, 11 TaG3, 20 T1G3, 12 T2G3, 1 T2G2, 1 T3G3) and 20 controls to identify dysregulated metabolites. Next, after exhaustive multivariate analysis, confirmed dysregulated metabolites were validated in an independent cohort of 134 BC patients (19 TaG1, 62 TaG2, 9 TaG3, 15 T1G2, 16 T1G3, 4 T2G2, 9 T2G3) and 78 controls.

RESULTS

We validated p-cresol glucuronide as potential diagnostic biomarker for BC patients compared to controls (AUC = 0.79). For NMIBC, p-cresol glucuronide was valuable as staging biomarker (AUC = 0.803). And among NMIBCs, p-coumaric acid may be a potential specific staging biomarker for the TaG1 NMIBC; however, future validation experiments should be conducted once the precise version of the standard is commercially available. Remarkably, for MIBC we validated spermine as potential specific staging biomarker (AUC = 0.882).

CONCLUSION

Ours is the first metabolomics study conducted in urine of a thoroughly characterized cohort comprising all stages of NMIBC, MIBC and healthy controls in which we identified non-invasive diagnostic and staging biomarkers. These may improve BC management, thus reducing the use of current harmful diagnostic techniques.

New bladder cancer non-invasive surveillance method based on voltammetric electronic tongue measurement of urine

Bladder cancer (BC) is the sixth leading cause of death by cancer. Depending on the invasiveness of tumors, patients with BC will undergo surgery and surveillance lifelong, owing the high rate of recurrence and progression. In this context, the development of strategies to support non-invasive BC diagnosis is focusing attention. Voltammetric electronic tongue (VET) has been demonstrated to be of use in the analysis of biofluids. Here, we present the implementation of a VET to study 207 urines to discriminate BC and non-BC for diagnosis and surveillance to detect recurrences. Special attention has been paid to the experimental setup to improve reproducibility in the measurements. PLSDA analysis together with variable selection provided a model with high sensitivity, specificity, and area under the ROC curve AUC (0.844, 0.882, and 0.917, respectively). These results pave the way for the development of non-invasive low-cost and easy-to-use strategies to support BC diagnosis and follow-up.

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Bladder cancer (BC) and control urines were studied by voltammetric electronic tongue

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A PLSDA model was obtained with high sensitivity, specificity, and accuracy (84/88/86)

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103/122 BC urines and 7⅝5 control urines were predicted correctly

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The electronic tongue has the potential for non-invasive BC diagnostics and follow-up

The Effect of Narrative Nursing Intervention on Shame in Elderly Patients with Bladder Cancer after Ileal Bladder Replacement: A Cohort Study

Background

The standard treatment for bladder cancer (BC) is transurethral resection (TURBt), intravesical chemotherapy, and regular follow-up cystoscopy after surgery. However, some patients experience relapse or progression. Narrative care refers to a nursing model in which nurses put themselves into the patient's position through communication and listening, thereby alleviating the patient's negative emotions. This study analyzed narrative nursing interventions in elderly patients with BC after vesicoileal replacement.

Objective

To explore the positive stimulating effect of narrative nursing intervention on the sense of shame in elderly patients with bladder cancer (BC) after ileal bladder replacement.

Methods

A total of 60 elderly patients with BC who went through ileal replacement of the bladder from February 2019 to April 2021 in our hospital were enrolled. The patients were divided into the control group and the study group by the arbitrary number table method. The former group received routine care, and the latter group received a narrative nursing intervention model. The nursing satisfaction, stigma score, self-care ability score, SAS score, SDS score, and quality of life score were compared.

Results

First, we compared the nursing satisfaction. In the research group, 23 cases were very satisfied, 6 cases were satisfied, and 1 case was normal, and the satisfaction rate was 100.00%. In the control group, 13 cases were very satisfied, 8 cases were satisfied, 4 cases were general, and 5 cases were dissatisfied, with a satisfaction rate of 83.33%. The nursing satisfaction of the research group was significantly higher compared to that of the control group (P < 0.05). Secondly, we compared the stigma scores. The stigma scores of the study group at the time of discharge, 1 month, 3 months, and 6 months after discharge were lower compared to those of the control group (P < 0.05). In terms of the scores of self-care ability, the total scores of self-concept, self-care responsibility, self-care knowledge, self-care skills, and self-care ability of the research group were higher compared to those of the control group (P < 0.05). With regard to SAS scores, before nursing, there was no significant difference exhibited (P > 0.05). After nursing, the patient's SAS score decreased. Compared with the two groups, the SAS scores of the study group at discharge, 1 month, 3 months, and 6 months after discharge were all lower (P < 0.05). In terms of SDS score, there was no significant difference before nursing (P > 0.05). After nursing, the SDS scores of patients decreased. Compared between the two groups, the SDS scores of the study group at the time of discharge, 1 month, 3 months, and 6 months after discharge were lower (P < 0.05). Finally, we compared the life quality scores. Before nursing, there was no significant difference exhibited (P > 0.05). After nursing, the scores of life quality of patients improved. Compared with the two groups, the physical function, psychological function, social function, and healthy self-cognition scores of the research group were all lower compared to those of the control group (P < 0.05).

Conclusion

Narrative nursing can reduce anxiety and depression in elderly patients with BC after ileal replacement of the bladder, enhance the quality of life, reduce the patient's stigma, and play a positive motivating role. This nursing model is worthy of promotion in clinic.

Metabolomics of Esophageal Squamous Cell Carcinoma Tissues: Potential Biomarkers for Diagnosis and Promising Targets for Therapy

Background

The incidence of esophageal squamous cell carcinoma in China ranks first in the world. The early diagnosis technology is underdeveloped, and the prognosis is poor, which seriously threatens the quality of life of the Chinese people. Epidemiological findings are related to factors such as diet, living habits, and age. The specific mechanism is not clear yet. Metabolomics is a kind of omics that simultaneously and quantitatively analyzes the comprehensive profile of metabolites in living systems. It has unique advantages in the study of the diagnosis and pathogenesis of tumor-related diseases, especially in the search for biomarkers. Therefore, it is desirable to perform metabolic profiling analysis of cancer tissues through metabolomics to find potential biomarkers for the diagnosis and treatment of esophageal squamous cell carcinoma.

Methods

HPLC-TOF-MS/MS technology and Illumina Hiseq Xten Sequencing was used for the analysis of 210 pairs of matched esophageal squamous cell carcinoma tissues and normal tissues in Zhenjiang City, Jiangsu Province, a high-incidence area of esophageal cancer in China. Bioinformatics analysis was also performed.

Results

Through metabolomic and transcriptomic analysis, this study found that a total of 269 differential metabolites were obtained in esophageal squamous cell carcinoma and normal tissues, and 48 differential metabolic pathways were obtained through KEGG enrichment analysis. After further screening and identification, 12 metabolites with potential biomarkers to differentiate esophageal squamous cell carcinoma from normal tissues were obtained.

Conclusions

From the metabolomic data, 4 unknown compounds were found to be abnormally expressed in esophageal squamous cell carcinoma for the first time, such as 9,10-epoxy-12,15-octadecadienoate; 3 metabolites were found in multiple abnormal expression in another tumor, but upregulation or downregulation was found for the first time in esophageal cancer, such as oleoyl glycine; at the same time, it was further confirmed that five metabolites were abnormally expressed in esophageal squamous cell carcinoma, which was similar to the results of other studies, such as PE.

Metabolomic Approaches for Detection and Identification of Biomarkers and Altered Pathways in Bladder Cancer

Metabolomic analysis has proven to be a useful tool in biomarker discovery and the molecular classification of cancers. In order to find new biomarkers, and to better understand its pathological behavior, bladder cancer also has been studied using a metabolomics approach. In this article, we review the literature on metabolomic studies of bladder cancer, focusing on the different available samples (urine, blood, tissue samples) used to perform the studies and their relative findings. Moreover, the multi-omic approach in bladder cancer research has found novel insights into its metabolic behavior, providing excellent start-points for new diagnostic and therapeutic strategies. Metabolomics data analysis can lead to the discovery of a “signature pathway” associated with the progression of bladder cancer; this aspect could be potentially valuable in predictions of clinical outcomes and the introduction of new treatments. However, further studies are needed to give stronger evidence and to make these tools feasible for use in clinical practice.

Untargeted Metabolomics Identify a Panel of Urinary Biomarkers for the Diagnosis of Urothelial Carcinoma of the Bladder, as Compared to Urolithiasis with or without Urinary Tract Infection in Dogs

Urothelial carcinoma (UC), the most common urologic cancer in dogs, is often diagnosed late because the clinical signs are shared by other non-malignant lower urinary tract disorders (LUTD). The urine-based BRAFV595E test for UC is highly effective only in certain breeds; hence additional non-invasive biomarkers of UC are needed. Here, urine from dogs with UC (n = 27), urolithiasis (n = 8), or urolithiasis with urinary tract infection (UTI) (n = 8) were subjected to untargeted metabolomics analyses, using GC-TOF-MS for primary metabolites, QTOF-MS for complex lipids, and HILIC-QTOF MS for secondary and charged metabolites. After adjusting for age and sex, we identified 1123 known metabolites that were differentially expressed between UC and LUTD. Twenty-seven metabolites were significant (1.5 ≤ log2FC ≤ −1.5, adjusted p-value < 0.05); however, 10 of these could be attributed to treatment-related changes. Of the remaining 17, 6 (hippuric acid, N-Acetylphenylalanine, sarcosine, octanoylcarnitine, N-alpha-methylhistamine, glycerol-3-galactoside) discriminated between UC and LUTD (area under the ROC curve > 0.85). Of the 6 metabolites, only hippuric acid and N-alpha-methylhistamine were discriminatory in both male (n = 20) and female (n = 23) dogs, while sarcosine was an effective discriminator in several breeds, but only in females. Further investigation of these metabolites is warranted for potential use as non-invasive diagnostic biomarkers of dogs with UC that present with LUTD-related clinical signs.

OUP accepted manuscript

Circulating biomarkers have emerged as valuable surrogates for evaluating disease states in solid malignancies. Their relative ease of access and rapid turnover has bolstered clinical applications in monitoring treatment efficacy and cancer progression. In this review, the roles of various circulating biomarkers in monitoring treatment response are described. Non-specific markers of disease burden, tumor markers (eg CA 125, CEA, PSA, etc.), circulating tumor cells, nucleic acids, exosomes, and metabolomic arrays are highlighted. Specifically, the discovery of each of these markers is reviewed, with examples illustrating their use in influencing treatment decisions, and barriers to their application noted where these exist. Finally, opportunities for future work using these circulating biomarkers are discussed.

The effect of amino acids on the bladder cycle: a concise review

The human bladder maintains a cycle of filling, storing, and micturating throughout an individual's lifespan. The cycle relies on the ability of the bladder to expand without increasing the intravesical pressure, which is only possible with the controlled relaxation of well-complaint muscles and the congruously organized construction of the bladder wall. A competent bladder outlet, which functions in a synchronous fashion with the bladder, is also necessary for this cycle to be completed successfully without deterioration. In this paper, we aimed to review the contemporary physiological findings on bladder physiology and examine the effects of amino acids on clinical conditions affecting the bladder, with special emphasis on the available therapeutic evidence and possible future roles of the amino acids in the treatment of the bladder-related disorders.

Urinary Metabolic Markers of Bladder Cancer: A Reflection of the Tumor or the Response of the Body?

This work will review the metabolic information that various studies have obtained in recent years on bladder cancer, with particular attention to discovering biomarkers in urine for the diagnosis and prognosis of this disease. In principle, they would be capable of complementing cystoscopy, an invasive but nowadays irreplaceable technique or, in the best case, of replacing it. We will evaluate the degree of reproducibility that the different experiments have shown in the indication of biomarkers, and a synthesis will be attempted to obtain a consensus list that is more likely to become a guideline for clinical practice. In further analysis, we will inquire into the origin of these dysregulated metabolites in patients with bladder cancer. For this purpose, it will be helpful to compare the imbalances measured in urine with those known inside tumor cells or tissues. Although the urine analysis is sometimes considered a liquid biopsy because of its direct contact with the tumor in the bladder wall, it contains metabolites from all organs and tissues of the body, and the tumor is separated from urine by the most impermeable barrier found in mammals. The distinction between the specific and systemic responses can help understand the disease and its consequences in more depth.

Predictive model for recurrence of renal cell carcinoma by comparing pre- and postoperative urinary metabolite concentrations

To improve treatment outcomes in real practice, useful biomarkers are desired when predicting postoperative recurrence for renal cell carcinoma (RCC). We collected data from patients who underwent definitive surgery for RCC and for benign urological tumor at our department between November 2016 and December 2019. We evaluated the differences in pre‐ and postoperative urinary metabolites with our precise quantitative method and identified predictive factors for RCC recurrence. Additionally, to clarify the significance of metabolites, we measured the intracellular metabolite concentration of three RCC cell lines. Among the 56 patients with RCC, nine had a recurrence (16.0%). When comparing 27 patients with T1a RCC and 10 with benign tumor, a significant difference was observed between pre‐ and postoperative concentrations among 10 urinary metabolites. In these 10 metabolites, multiple logistic regression analysis identified five metabolites (lactic acid, glycine, 2‐hydroxyglutarate, succinic acid, and kynurenic acid) as factors to build our recurrence prediction model. The values of area under the receiver operating characteristic curve, sensitivity, and specificity in this predictive model were 0.894%, 88.9%, and 88.0%, respectively. When stratified into low and high risk groups of recurrence based on this model, we found a significant drop of recurrence‐free survival rates among the high risk group. In in vitro studies, intracellular metabolite concentrations of metastatic tumor cell lines were much higher than those of primary tumor cell lines. By using our quantitative evaluation of urinary metabolites, we could predict postoperative recurrence with high sensitivity and specificity. Urinary metabolites could be noninvasive biomarkers to improve patient outcome.

Multiple Chromatographic Analysis of Urine in the Detection of Bladder Cancer

Bladder cancer (BC) is the most common type of carcinoma of the urological system. Recently, there has been an increasing interest in non-invasive diagnostic tumor markers due to the invasive attribute of cystoscopy, which is still considered the gold standard diagnostic method. However, markers published in the literature so far do not meet expectations for replacing cystoscopy due to their low specificity and excessively high false-positive results, which can be mainly caused by frequently occurring hematuria also in benign cases. No reliable non-invasive method has yet been identified that can distinguish patients with bladder cancer and non-malignant hematuria patients. Our work examined the possibilities of non-targeted biomarkers of urine to distinguish patients with malignant and non-malignant diseases of the bladder using 3D HPLC in combination with computer processing of multiple datasets. Urine samples from 47 patients, 23 patients with bladder cancer (BC) and 24 patients with non-malignant hematuria (NMHU), were enrolled in clinical trials. For the separation and subsequent analysis of a large number of urine components, 3D HPLC (high-performance liquid chromatography) with an absorption and fluorescence detector was used. The obtained dataset was further subjected to various uni- and multi-dimensional statistical analyses and mathematical modeling. We found 334 chromatographic peaks, of which 18 peaks were identified as significantly different for BC and NMHU patients. Using receiver operating characteristic (ROC) analysis, we assessed the informative ability of significant chromatographic peaks (90% sensitivity and 74% specificity). By logistic regression, we identified the optimal and simplified set of seven chromatographic peaks (5 absorptions plus 2 fluorescence) with strong classification power (100% sensitivity and 100% specificity) for distinguishing patients with bladder cancer and those with non-malignant hematuria. Partial least square discriminant analysis (PLS-DA) model and orthogonal projection to latent structure discriminant analysis (OPLS-DA) with 100% sensitivity and 96% specificity were used to distinguish BC and NMHU patients. Multivariate statistical analysis of urinary metabolomic profiles of patients revealed that BC patients can be discriminated from NMHU patients and the results can likely contribute to an early and non-invasive diagnosis of BC.

Integrative Transcriptomic, Lipidomic, and Metabolomic Analysis Reveals Potential Biomarkers of Basal and Luminal Muscle Invasive Bladder Cancer Subtypes

Muscle invasive bladder cancer (MIBC) is a heterogeneous disease with a high recurrence rate and poor clinical outcomes. Molecular subtype provides a new framework for the study of MIBC heterogeneity. Clinically, MIBC can be classified as basal and luminal subtypes; they display different clinical and pathological characteristics, but the molecular mechanism is still unclear. Lipidomic and metabolomic molecules have recently been considered to play an important role in the genesis and development of tumors, especially as potential biomarkers. Their different expression profiles in basal and luminal subtypes provide clues for the molecular mechanism of basal and luminal subtypes and the discovery of new biomarkers. Herein, we stratified MIBC patients into basal and luminal subtypes using a MIBC classifier based on transcriptome expression profiles. We qualitatively and quantitatively analyzed the lipids and metabolites of basal and luminal MIBC subtypes and identified their differential lipid and metabolite profiles. Our results suggest that free fatty acids (FFAs) and sulfatides (SLs), which are closely associated with immune and stromal cell types, can contribute to the diagnosis of basal and luminal subtypes of MIBC. Moreover, we showed that glycerophosphocholine (GCP)/imidazoles and nucleosides/imidazoles ratios can accurately distinguish the basal and luminal tumors. Overall, by integrating transcriptomic, lipidomic, and metabolomic data, our study reveals specific biomarkers to differentially diagnose basal and luminal MIBC subtypes and may provide a basis for precision therapy of MIBC.

Mass spectrometry imaging of L-[ring-13C6]-labeled phenylalanine and tyrosine kinetics in non-small cell lung carcinoma

BACKGROUND

Metabolic reprogramming is a common phenomenon in tumorigenesis and tumor progression. Amino acids are important mediators in cancer metabolism, and their kinetics in tumor tissue are far from being understood completely. Mass spectrometry imaging is capable to spatiotemporally trace important endogenous metabolites in biological tissue specimens. In this research, we studied L-[ring-¹³C₆]-labeled phenylalanine and tyrosine kinetics in a human non-small cell lung carcinoma (NSCLC) xenografted mouse model using matrix-assisted laser desorption/ionization Fourier-transform ion cyclotron resonance mass spectrometry imaging (MALDI-FTICR-MSI).

METHODS

We investigated the L-[ring-¹³C₆]-Phenylalanine (¹³C₆-Phe) and L-[ring-¹³C₆]-Tyrosine (¹³C₆-Tyr) kinetics at 10 min (n = 4), 30 min (n = 3), and 60 min (n = 4) after tracer injection and sham-treated group (n = 3) at 10 min in mouse-xenograft lung tumor tissues by MALDI-FTICR-MSI.

RESULTS

The dynamic changes in the spatial distributions of 19 out of 20 standard amino acids are observed in the tumor tissue. The highest abundance of ¹³C₆-Phe was detected in tumor tissue at 10 min after tracer injection and decreased progressively over time. The overall enrichment of ¹³C₆-Tyr showed a delayed temporal trend compared to ¹³C₆-Phe in tumor caused by the Phe-to-Tyr conversion process. Specifically, ¹³C₆-Phe and ¹³C₆-Tyr showed higher abundances in viable tumor regions compared to non-viable regions.

CONCLUSIONS

We demonstrated the spatiotemporal intra-tumoral distribution of the essential aromatic amino acid ¹³C₆-Phe and its de-novo synthesized metabolite ¹³C₆-Tyr by MALDI-FTICR-MSI. Our results explore for the first time local phenylalanine metabolism in the context of cancer tissue morphology. This opens a new way to understand amino acid metabolism within the tumor and its microenvironment.

Epigenomic and Metabolomic Integration Reveals Dynamic Metabolic Regulation in Bladder Cancer

Bladder cancer (BC) represents a clinical, social, and economic challenge due to tumor-intrinsic characteristics, limitations of diagnostic techniques and a lack of personalized treatments. In the last decade, the use of liquid biopsy has grown as a non-invasive approach to characterize tumors. Moreover, the emergence of omics has increased our knowledge of cancer biology and identified critical BC biomarkers. The rewiring between epigenetics and metabolism has been closely linked to tumor phenotype. Chromatin remodelers interact with each other to control gene silencing in BC, but also with stress-inducible factors or oncogenic signaling cascades to regulate metabolic reprogramming towards glycolysis, the pentose phosphate pathway, and lipogenesis. Concurrently, one-carbon metabolism supplies methyl groups to histone and DNA methyltransferases, leading to the hypermethylation and silencing of suppressor genes in BC. Conversely, α-KG and acetyl-CoA enhance the activity of histone demethylases and acetyl transferases, increasing gene expression, while succinate and fumarate have an inhibitory role. This review is the first to analyze the interplay between epigenome, metabolome and cell signaling pathways in BC, and shows how their regulation contributes to tumor development and progression. Moreover, it summarizes non-invasive biomarkers that could be applied in clinical practice to improve diagnosis, monitoring, prognosis and the therapeutic options in BC.

Tumoral markers in bladder cancer (Review)

Bladder tumors are frequently diagnosed urologic malignant diseases with an extremely high recurrence rate compared to other neoplastic tumors. Urothelial bladder carcinomas are mostly identified in their incipient form, as non-muscle invasive, but despite that, a third of them develop into aggressive recurrent disease. The diagnosis of bladder carcinoma at this moment is established using cytology and cystoscopy and is a great challenge for clinicians due to the lack of sensitivity. Urinary biomarkers could improve and enhance the diagnosis and screening techniques and determine a more accurate recurrence rate. However, bladder cancer is a heterogeneous disease and the existence of a single marker test with reduced cost is unlikely; thus, until then, the use of a panel of markers to obtain valuable information is inevitable even though suboptimal for use. To improve this deadlock, new biomarker panels should be identified and prepared to equalize the cost-efficiency balance. The present paper is a literature review concerning the most commonly used tumor markers in urinary bladder cancer as well as the most commonly encountered genetic modifications in such patients.

Nanotechnology in Bladder Cancer: Diagnosis and Treatment

Bladder cancer (BC) is the second most common cancer of the urinary tract in men and the fourth most common cancer in women, and its incidence rises with age. There are many conventional methods for diagnosis and treatment of BC. There are some current biomarkers and clinical tests for the diagnosis and treatment of BC. For example, radiotherapy combined with chemotherapy and surgical, but residual tumor cells mostly cause tumor recurrence. In addition, chemotherapy after transurethral resection causes high side effects, and lack of selectivity, and low sensitivity in sensing. Therefore, it is essential to improve new procedures for the diagnosis and treatment of BC. Nanotechnology has recently sparked an interest in a variety of areas, including medicine, chemistry, physics, and biology. Nanoparticles (NP) have been used in tumor therapies as appropriate tools for enhancing drug delivery efficacy and enabling therapeutic performance. It is noteworthy, nanomaterial could be reduced the limitation of conventional cancer diagnosis and treatments. Since, the major disadvantages of therapeutic drugs are their insolubility in an aqueous solvent, for instance, paclitaxel (PTX) is one of the important therapeutic agents utilized to treating BC, due to its ability to prevent cancer cell growth. However, its major problem is the poor solubility, which has confirmed to be a challenge when improving stable formulations for BC treatment. In order to reduce this challenge, anti-cancer drugs can be loaded into NPs that can improve water solubility. In our review, we state several nanosystem, which can effective and useful for the diagnosis, treatment of BC. We investigate the function of metal NPs, polymeric NPs, liposomes, and exosomes accompanied therapeutic agents for BC Therapy, and then focused on the potential of nanotechnology to improve conventional approaches in sensing.

Metabolic Evaluation of Urine from Patients Diagnosed with High Grade (HG) Bladder Cancer by SPME-LC-MS Method

Bladder cancer (BC) is a common malignancy of the urinary system and a leading cause of death worldwide. In this work, untargeted metabolomic profiling of biological fluids is presented as a non-invasive tool for bladder cancer biomarker discovery as a first step towards developing superior methods for detection, treatment, and prevention well as to further our current understanding of this disease. In this study, urine samples from 24 healthy volunteers and 24 BC patients were subjected to metabolomic profiling using high throughput solid-phase microextraction (SPME) in thin-film format and reversed-phase high-performance liquid chromatography coupled with a Q Exactive Focus Orbitrap mass spectrometer. The chemometric analysis enabled the selection of metabolites contributing to the observed separation of BC patients from the control group. Relevant differences were demonstrated for phenylalanine metabolism compounds, i.e., benzoic acid, hippuric acid, and 4-hydroxycinnamic acid. Furthermore, compounds involved in the metabolism of histidine, beta-alanine, and glycerophospholipids were also identified. Thin-film SPME can be efficiently used as an alternative approach to other traditional urine sample preparation methods, demonstrating the SPME technique as a simple and efficient tool for urinary metabolomics research. Moreover, this study's results may support a better understanding of bladder cancer development and progression mechanisms.

Profiling and Targeting of Energy and Redox Metabolism in Grade 2 Bladder Cancer Cells with Different Invasiveness Properties

Bladder cancer is one of the most prevalent deadly diseases worldwide. Grade 2 tumors represent a good window of therapeutic intervention, whose optimization requires high resolution biomarker identification. Here we characterize energy metabolism and cellular properties associated with spreading and tumor progression of RT112 and 5637, two Grade 2 cancer cell lines derived from human bladder, representative of luminal-like and basal-like tumors, respectively. The two cell lines have similar proliferation rates, but only 5637 cells show efficient lateral migration. In contrast, RT112 cells are more prone to form spheroids. RT112 cells produce more ATP by glycolysis and OXPHOS, present overall higher metabolic plasticity and are less sensitive than 5637 to nutritional perturbation of cell proliferation and migration induced by treatment with 2-deoxyglucose and metformin. On the contrary, spheroid formation is less sensitive to metabolic perturbations in 5637 than RT112 cells. The ability of metformin to reduce, although with different efficiency, cell proliferation, sphere formation and migration in both cell lines, suggests that OXPHOS targeting could be an effective strategy to reduce the invasiveness of Grade 2 bladder cancer cells.

Identification of metabolism-associated genes and construction of a prognostic signature in bladder cancer

BACKGROUND

Bladder cancer (BC) is a commonly diagnosed malignant tumor in the urinary system, with a high morbidity and a high recurrence rate. Current studies indicated that metabolism-associated genes (MAGs) having critical roles in the etiology of BC. The present study aims to identify differentially expressed MAGs and construct a MAGs based prognostic risk signature for BC by using The Cancer Genome Atlas (TCGA) database and proteomics data.

METHODS

RNA-sequence data from the TCGA database and proteomics data from our BC samples were used to identify differentially expressed MAGs and construct a MAGs based prognostic signature in BC. Subsequently, survival analysis and nomogram were used to evaluate the prognostic and predictive value of the MAGs based signature in BC. RNA isolation and reverse transcription‑quantitative PCR (RT-qPCR) were further performed to investigate the expression levels of MAGs in BC cells and explore the relationship between MAGs and M2 tumor associated macrophages (TAMs) secreted transforming growth factor-β1 (TGF-β1) in BC cells.

RESULTS

A total of 23 differentially expressed MAGs were identified and five MAGs were finally used to construct a MAGs based signature. Survival analysis revealed that the MAGs based signature was closely correlated with the survival outcomes of patients with BC. A nomogram with the MAGs based signature risk score and clinical features was also constructed to facilitate the individualized prediction of BC patients. RT-qPCR showed that five MAGs were significantly differentially expressed and the expression levels of three MAGs were positively correlated with M2 TAMs secreted TGF-β1 in T24 cells.

CONCLUSIONS

Our study identified novel prognostic MAGs and constructed a MAGs based signature, which can be used as an independent factor in evaluating the prognosis of patients with BC. Furthermore, M2 TAMs may promote the expression of MAGs via the TGF-β1 signaling pathway in the microenvironment of BC. Further clinical trials and experimental explorations are needed to validate our observations in BC.

Metabolomic profiling in neuroblastoma

BACKGROUND AND OBJECTIVES

Previous studies on several cancer types show that metabolomics provides a potentially useful noninvasive screening approach for outcome prediction and accurate response to treatment assessment. Neuroblastoma (NB) accounts for at least 15% of cancer-related deaths in children. Although current risk-based treatment approaches in NB have resulted in improved outcome, survival for high-risk patients remains poor. This study aims to evaluate the use of metabolomics for improving patients' risk-group stratification and outcome prediction in NB.

DESIGN AND METHODS

Plasma samples from 110 patients with NB were collected at diagnosis prior to starting therapy and at the end of treatment if available. Metabolomic analysis of samples was carried out by ultra-performance liquid chromatography-time of flight mass spectrometry (UPLC-MS).

RESULTS

The metabolomic analysis was able to identify different plasma metabolic profiles in high-risk and low-risk NB patients at diagnosis. The metabolic model correctly classified 16 high-risk and 15 low-risk samples in an external validation set providing 84.2% sensitivity (60.4-96.6, 95% CI) and 93.7% specificity (69.8-99.8, 95% CI). Metabolomic profiling could also discriminate high-risk patients with active disease from those in remission. Notably, a plasma metabolomic signature at diagnosis identified a subset of high-risk NB patients who progressed during treatment.

CONCLUSIONS

To the best of our knowledge, this is the largest NB study investigating the prognostic power of plasma metabolomics. Our results support the potential of metabolomic profiling for improving NB risk-group stratification and outcome prediction. Additional validating studies with a large cohort are needed.

Improving diagnosis of genitourinary cancers: Biomarker discovery strategies through mass spectrometry-based metabolomics

The genitourinary oncology field needs integration of results from basic science, epidemiological studies, clinical and translational research to improve the current methods for diagnosis. MS-based metabolomics can be transformative for disease diagnosis and contribute to global health parity. Metabolite panels are promising to translate metabolomic findings into the clinics, changing the current diagnosis paradigm based on single biomarker analysis. This review article describes capabilities of the MS-based oncometabolomics field for improving kidney, prostate, and bladder cancer detection, early diagnosis, risk stratification, and outcome. Published works are critically discussed based on the study design; type and number of samples analyzed; data quality assessment through quality assurance and quality control practices; data analysis workflows; confidence levels reported for identified metabolites; validation attempts; the overlap of discriminant metabolites for the different genitourinary cancers; and the translation capability of findings into clinical settings. Ongoing challenges are discussed, and future directions are delineated.

Urinary Metabolic Signatures Detect Recurrences in Non-Muscle Invasive Bladder Cancer

Patients with non-muscle invasive bladder cancer (NMIBC) undergo lifelong monitoring based on repeated cystoscopy and urinary cytology due to the high recurrence rate of this tumor. Nevertheless, these techniques have some drawbacks, namely, low accuracy in detection of low-grade tumors, omission of pre-neoplastic lesions and carcinomas in situ (CIS), invasiveness, and high costs. This work aims to identify a urinary metabolomic signature of recurrence by proton Nuclear Magnetic Resonance (¹H NMR) spectroscopy for the follow-up of NMIBC patients. To do this, changes in the urinary metabolome before and after transurethral resection (TUR) of tumors are analyzed and a Partial Least Square Discriminant Analysis (PLS-DA) model is developed. The usefulness of this discriminant model for the detection of tumor recurrences is assessed using a cohort of patients undergoing monitoring. The trajectories of the metabolomic profile in the follow-up period provide a negative predictive value of 92.7% in the sample classification. Pathway analyses show taurine, alanine, aspartate, glutamate, and phenylalanine perturbed metabolism associated with NMIBC. These results highlight the potential of ¹H NMR metabolomics to detect bladder cancer (BC) recurrences through a non-invasive approach.

Integrative Metabolomic and Transcriptomic Analysis for the Study of Bladder Cancer

Metabolism reprogramming is considered a hallmark of cancer. The study of bladder cancer (BC) metabolism could be the key to developing new strategies for diagnosis and therapy. This work aimed to identify tissue and urinary metabolic signatures as biomarkers of BC and get further insight into BC tumor biology through the study of gene-metabolite networks and the integration of metabolomics and transcriptomics data. BC and control tissue samples (n = 44) from the same patients were analyzed by High-Resolution Magic Angle Spinning Nuclear Magnetic Resonance and microarrays techniques. Besides, urinary profiling study (n = 35) was performed in the same patients to identify a metabolomic profile, linked with BC tissue hallmarks, as a potential non-invasive approach for BC diagnosis. The metabolic profile allowed for the classification of BC tissue samples with a sensitivity and specificity of 100%. The most discriminant metabolites for BC tissue samples reflected alterations in amino acids, glutathione, and taurine metabolic pathways. Transcriptomic data supported metabolomic results and revealed a predominant downregulation of metabolic genes belonging to phosphorylative oxidation, tricarboxylic acid cycle, and amino acid metabolism. The urinary profiling study showed a relation with taurine and other amino acids perturbed pathways observed in BC tissue samples, and classified BC from non-tumor urine samples with good sensitivities (91%) and specificities (77%). This urinary profile could be used as a non-invasive tool for BC diagnosis and follow-up.

The Microbiome and Genitourinary Cancer: A Collaborative Review

CONTEXT

The recent discovery of the existence of a human genitourinary microbiome has led to the investigation of its role in mediating the pathogenesis of genitourinary malignancies, including bladder, kidney, and prostate cancers. Furthermore, although it is largely recognized that members of the gastrointestinal microbiota are actively involved in drug metabolism, new studies demonstrate additional roles and the potential necessity of the gastrointestinal microbiota in dictating cancer treatment response.

OBJECTIVE

To summarize the current evidence of a mechanistic role for the genitourinary and gastrointestinal microbiome in genitourinary cancer initiation and treatment response.

EVIDENCE ACQUISITION

We conducted a literature search up to October 2018. Search terms included microbiome, microbiota, urinary microbiome, bladder cancer, urothelial carcinoma, renal cell carcinoma, kidney cancer, testicular cancer, and prostate cancer.

EVIDENCE SYNTHESIS

There is preliminary evidence to implicate the members of the genitourinary microbiota as causative factors or cofactors in genitourinary malignancy. Likewise, the current evidence for gastrointestinal microbes in dictating cancer treatment response is mainly correlative; however, we provide examples where therapeutic agents used for the treatment of genitourinary cancers are affected by the human-associated microbiota, or vice versa. Clinical trials, such as fecal microbiota transplant to increase the efficacy of immunotherapy, are currently underway.

CONCLUSIONS

The role of the microbiome in genitourinary cancer is an emerging field that merits further studies. Translating microbiome research into clinical action will require incorporation of microbiome surveillance into ongoing and future clinical trials as well as expansion of studies to include metagenomic sequencing and metabolomics.

PATIENT SUMMARY

This review covers recent evidence that microbial populations that reside in the genitourinary tract-and were previously not known to exist-may influence the development of genitourinary malignancies including bladder, kidney, and prostate cancers. Furthermore, microbial populations that exist at sites outside of the genitourinary tract, such as those that reside in our gut, may influence cancer development and/or treatment response.

Recent advances in the metabolomic study of bladder cancer

INTRODUCTION

Metabolomics is a chemical process, involving the characterization of metabolites and cellular metabolism. Recent studies indicate that numerous metabolic pathways are altered in bladder cancer (BLCA), providing potential targets for improved detection and possible therapeutic intervention. We review recent advances in metabolomics related to BLCA and identify various metabolites that may serve as potential biomarkers for BLCA. Areas covered: In this review, we describe the latest advances in defining the BLCA metabolome and discuss the possible clinical utility of metabolic alterations in BLCA tissues, serum, and urine. In addition, we focus on the metabolic alterations associated with tobacco smoke and racial disparity in BLCA. Expert commentary: Metabolomics is a powerful tool which can shed new light on BLCA development and behavior. Key metabolites may serve as possible markers of BLCA. However, prospective validation will be needed to incorporate these markers into clinical care.

Magnetic multiwalled carbon nanotubes with controlled release of epirubicin: an intravesical instillation system for bladder cancer

Background

Traditional intravesical instillation treatment in bladder cancer has limited efficacy, which results in a high frequency of recurrence.

Purpose

The aim of this study was to report on an epirubicin (EPI)-loaded magnetic multi-walled carbon nanotube (mMWCNTs-EPI) system for intravesical instillation in place of the current formulation.

Methods

The mMWCNTs-EPI system was formulated with carboxylated MWCNTs, Fe₃O₄ magnetic nanoparticles, and EPI. Features and antitumor activity of the system were investigated.

Results

Under the effect of external magnets, the mMWCNTs-EPI system showed sustained release and prolonged retention behavior and better antitumor activity than free EPI. The mMWCNTs-EPI system had higher efficiency in enhancing cytotoxicity and inhibiting proliferation in vitro and in vivo than free EPI. Our studies also revealed the atoxic nature of mMWCNTs.

Conclusion

These findings suggested that mMWCNTs are effective intravesical instillation agents with great potential for clinical application.

Discriminating high-risk cervical Human Papilloma Virus infections with urinary biomarkers via non-targeted GC-MS-based metabolomics

Genital human papillomavirus (HPV) is the world’s most commonly diagnosed sexually transmitted infection, and high-risk HPV types are strongly linked to cervical dysplasia and carcinoma. Puerto Ricans are among the US citizens with higher HPV prevalence and lower screening rates and access to treatment. This bleak statistic was as a motivation to detect biomarkers for early diagnosis of HPV in this population. We collected both urine and cervical swabs from 43 patients attending San Juan Clinics. Cervical swabs were used for genomic DNA extractions and HPV genotyping with the HPV SPF10-LiPA25 kit, and gas chromatography-mass spectrometry (GC-MS) was employed on the urine-derived products for metabolomics analyses. We aimed at discriminating between patients with different HPV categories: HPV negative (HPV-), HPV positive with simultaneous low and high-risk infections (HPV+B) and HPV positive exclusively high-risk (HPV+H). We found that the metabolome of HPV+B is closer to HPV- than to HPV+H supporting evidence that suggests HPV co-infections may be antagonistic due to viral interference leading to a lower propensity for cervical cancer development. In contrast, metabolites of patients with HPV+H were significantly different from those that were HPV-. We identified three urinary metabolites 5-Oxoprolinate, Erythronic acid and N-Acetylaspartic acid that discriminate HPV+H cases from negative controls. These metabolites are known to be involved in a variety of biochemical processes related to energy and metabolism and may likely be biomarkers for HPV high-risk cervical infection. However, further validation should follow using a larger patient cohort and diverse populations to confirm our finding.

Discovering biomarkers in bladder cancer by metabolomics

It has become increasingly clear that the development of cancer, a multifactorial disease, cannot be explained by a single molecule or gene mutation. As a new discipline, metabolomics focuses on the body's metabolite changes, and attempts to find differences to explain the development of cancer; it has proven to be effective and credible. Metabolic studies of bladder cancer (BCa) lag behind those of other tumors. This review systematically outlines the specific process of metabolomics and the use of metabolomics in BCa studies in recent years. We have reviewed the in vitro cell line, bladder tumor tissue and biofluid (urine, plasma and serum) studies used in metabolomics analyses of BCa. The advantages and drawbacks of the use of different samples were compared. Based on the available studies, we have further described the aberrant metabolic pathways of BCa and have suggested some metabolites that may be potential biomarkers for BCa detection.

Urinary Markers in Bladder Cancer: An Update

Bladder cancer (BC) is ones of the most common cancer worldwide. It is classified in muscle invasive (MIBC) and muscle non-invasive (NMIBC) BC. NMIBCs frequently recur and progress to MIBCs with a reduced survival rate and frequent distant metastasis. BC detection require unpleasant and expensive cystoscopy and biopsy, which are often accompanied by several adverse effects. Thus, there is an urgent need to develop novel diagnostic methods for initial detection and surveillance in both MIBCs and NMIBCs. Multiple urine-based tests approved by FDA for BC detection and surveillance are commercially available. However, at present, sensitivity, specificity and diagnostic accuracy of these urine-based assays are still suboptimal and, in the attend to improve them, novel molecular markers as well as multiple-assays must to be translated in clinic. Now there are growing evidence toward the use of minimally invasive “liquid biopsy” to identify biomarkers in urologic malignancy. DNA- and RNA-based markers in body fluids such as blood and urine are promising potential markers in diagnostic, prognostic, predictive and monitoring urological malignancies. Thus, circulating cell-free DNA, DNA methylation and mutations, circulating tumor cells, miRNA, IncRNA and mRNAs, cell-free proteins and peptides, and exosomes have been assessed in urine specimens. However, proteomic and genomic data must to be validated in well-designed multicenter clinical studies, before to be employed in clinic oncology.

Liquid Biopsy Biomarkers in Bladder Cancer: A Current Need for Patient Diagnosis and Monitoring

Bladder Cancer (BC) represents a clinical and social challenge due to its high incidence and recurrence rates, as well as the limited advances in effective disease management. Currently, a combination of cytology and cystoscopy is the routinely used methodology for diagnosis, prognosis and disease surveillance. However, both the poor sensitivity of cytology tests as well as the high invasiveness and big variation in tumour stage and grade interpretation using cystoscopy, emphasizes the urgent need for improvements in BC clinical guidance. Liquid biopsy represents a new non-invasive approach that has been extensively studied over the last decade and holds great promise. Even though its clinical use is still compromised, multiple studies have recently focused on the potential application of biomarkers in liquid biopsies for BC, including circulating tumour cells and DNA, RNAs, proteins and peptides, metabolites and extracellular vesicles. In this review, we summarize the present knowledge on the different types of biomarkers, their potential use in liquid biopsy and clinical applications in BC.