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

Metabolomic study for the identification of symptomatic carotid plaque biomarkers

Carotid artery stenosis is mainly produced due to the progressive accumulation of atherosclerotic plaque in the vascular wall. The atherosclerotic plaque is characterized by the accumulation of lipids, low density proteins, expression of chemokines and adhesion molecules, and migration of monocytes and lymphocytes into the plaque. Its rupture can produce stroke, but embolic propensity depends principally on the composition and vulnerability of plaque rather than the severity of stenosis. It is important, then, to ascertain which patients with carotid artery stenosis have a greater risk of developing neurological symptomatology. Here, we present a metabolomic study by using nuclear magnetic resonance (NMR) spectroscopy in atheroma plaque and serum samples from patients with recently symptomatic and asymptomatic carotid stenosis to search for metabolites that could be used as biomarkers associated with plaque vulnerability and subsequent risk of rupture. Thirty-eight atheromatous plaque samples (24 asymptomatic patients and 14 symptomatic) and 70 serum samples (43 asymptomatic and 27 symptomatic) were studied by NMR spectroscopy. The data were analysed using multivariate statistics (PLS-DA) to determine a model to discriminate between symptomatic and asymptomatic samples (atheroma plaques and sera). The calculated PLS-DA models showed a 100 % sensitivity and a 96.6 % specificity for the cross validation to discriminate between symptomatic and asymptomatic plaques, and 88.37 % sensitivity and 77.78 % specificity when serum samples were analysed. According to the results of our multivariate and univariate analysis, the most discriminative metabolites for plaque vulnerability were threonine in serum samples, and glutamate in plaque samples. Also, an analysis of the main metabolic pathways involved in plaque vulnerability revealed that d-glutamine and d-glutamate metabolism, and phenylalanine, tyrosine, and tryptophan biosynthesis were the most affected pathways in plaque and serum, respectively.

Validation of urine p-cresol glucuronide as renal cell carcinoma non-invasive biomarker

Renal cell carcinoma (RCC) stands among the most lethal urological malignancies. Most RCCs are incidentally diagnosed as initial symptoms are unspecific. Novel, minimally-invasive diagnostic and prognostic methods for RCC are needed, ideally in urine. Using UPLC-Q-ToF MS untargeted metabolomic analysis in urine, we previously revealed p-cresol glucuronide as potential RCC diagnostic marker. Additionally, urine samples one-year post-nephrectomy revealed isobutyryl-l-carnitine and L-proline betaine as potential RCC prognostic markers. Our present aim was to validate these differences in an independent cohort of RCC patients and healthy controls to strengthen their value as non-invasive biomarkers. In an independent cohort of 69 RCC patients and 52 controls we validated an increase in p-cresol glucuronide in urine from patients at diagnosis compared to controls (P = 0.0043). It remained increased one-year post-nephrectomy (P = 0.0288). The value of p-cresol glucuronide for RCC diagnosis was assessed with ROC curves analysis (AUC = 0.66, 95 % Confidence Interval 0.56-0.76). The role of isobutyryl-l-carnitine and L-proline betaine as prognostic markers could not be validated and will require a larger cohort. Our findings confirm the value of p-cresol glucuronide in urine as diagnostic marker for RCC in an independent cohort. This non-invasive method holds promise for enhancing patient care by reducing the need for potentially risky diagnostic procedures. Further metaproteomics-oriented approaches towards the tyrosine oxidation pathway and microbiota metagenomics studies may promote a holistic management of RCC. SIGNIFICANCE: Current imaging techniques available to diagnose and monitor renal cell carcinoma (RCC) are harmful for the patient given the high-radiation dose, and unspecific in low-grade tumors. Thus, novel non-invasive biomarkers with diagnostic and prognostic capabilities are of utmost importance. Herein, we have validated urine p-cresol glucuronide as diagnostic marker for RCC. This novel non-invasive biomarker could improve accurate assessments of tumor behavior, while enhancing patient outcomes by reducing discomfort and detrimental side effects.

UPLC-Q-TOF/MS-based urine metabolomics for the diagnosis and staging of bladder cancer

BACKGROUND

Bladder cancer (BC) is a common malignant tumour of the urinary system. Currently, the gold standard for diagnosing BC is cystoscopy, but it is an invasive examination that can lead to a certain psychological burden on the patient. In this study, we aimed to identify non-invasive potential metabolic biomarkers that could improve the diagnostic accuracy of bladder cancer.

METHODS

Urine from 30 healthy people and 50 BC patients, including 40 non-muscle-invasive bladder cancer (NMIBC) patients and 10 muscle-invasive bladder cancer (MIBC) patients, were analyzed by liquid chromatography coupled with mass spectrometry to identify potential diagnostic metabolites. Binary Logistic regression was used to construct biomarker panels. Correlation analysis and construction of compound-reaction-enzyme-gene network were also performed to explore the possible mechanisms of BC development.

RESULTS

Twenty-six metabolites were identified for differentiating BC patients from healthy controls, and eight metabolites were identified for differentiating NMIBC patients form MIBC patients. The biomarker panel consisting of urate, 4-Androstene-3α, 17β-diol and 3-Indoxyl sulfate can distinguish well between BC patients and healthy controls, with an area under the ROC curve (AUC) value of 0.983. And the biomarker panel consisting of L-Octanoylcarnitine, γ-Glutamylleucine, and heptanoylcarnitine for distinguishing NMIBC patients from MIBC patients had an AUC value of 0.941.

CONCLUSIONS

The diagnostic capability of the biomarker panels are superior to that of any single potential biomarker. This panel significantly benefits bladder cancer diagnostics and reveals insight into bladder cancer pathogenesis.

Urinary microbiome dysbiosis is associated with an inflammatory environment and perturbed fatty acids metabolism in the pathogenesis of bladder cancer

BACKGROUND

Bladder cancer is a common malignancy with high recurrence rate. Early diagnosis and recurrence surveillance are pivotal to patients' outcomes, which require novel minimal-invasive diagnostic tools. The urinary microbiome is associated with bladder cancer and can be used as biomarkers, but the underlying mechanism is to be fully illustrated and diagnostic performance to be improved.

METHODS

A total of 23 treatment-naïve bladder cancer patients and 9 non-cancerous subjects were enrolled into the Before group and Control group. After surgery, 10 patients from the Before group were further assigned into After group. Void mid-stream urine samples were collected and sent for 16S rDNA sequencing, targeted metabolomic profiling, and flow cytometry. Next, correlations were analyzed between microbiota, metabolites, and cytokines. Finally, receiver operating characteristic (ROC) curves of the urinary biomarkers were plotted and compared.

RESULTS

Comparing to the Control group, levels of IL-6 (p < 0.01), IL-8 (p < 0.05), and IL-10 (p < 0.05) were remarkably elevated in the Before group. The α diversity of urine microbiome was also significantly higher, with the feature microbiota positively correlated to the level of IL-6 (r = 0.58, p < 0.01). Significant differences in metabolic composition were also observed between the Before and Control groups, with fatty acids and fatty acylcarnitines enriched in the Before group. After tumor resection, cytokine levels and the overall microbiome structure in the After group remained similar to that of the Before group, but fatty acylcarnitines were significantly reduced (p < 0.05). Pathway enrichment analysis revealed beta-oxidation of fatty acids was significantly involved (p < 0.001). ROC curves showed that the biomarker panel of Actinomycetaceae + arachidonic acid + IL-6 had superior diagnostic performance, with sensitivity of 0.94 and specificity of 1.00.

CONCLUSIONS

Microbiome dysbiosis, proinflammatory environment and altered fatty acids metabolism are involved in the pathogenesis of bladder cancer, which may throw light on novel noninvasive diagnostic tool development.

Metabolomics for searching validated biomarkers in cancer studies: a decade in review

INTRODUCTION

In the dynamic landscape of modern healthcare, the ability to anticipate and diagnose diseases, particularly in cases where early treatment significantly impacts outcomes, is paramount. Cancer, a complex and heterogeneous disease, underscores the critical importance of early diagnosis for patient survival. The integration of metabolomics information has emerged as a crucial tool, complementing the genotype-phenotype landscape and providing insights into active metabolic mechanisms and disease-induced dysregulated pathways.

AREAS COVERED

This review explores a decade of developments in the search for biomarkers validated within the realm of cancer studies. By critically assessing a diverse array of research articles, clinical trials, and studies, this review aims to present an overview of the methodologies employed and the progress achieved in identifying and validating biomarkers in metabolomics results for various cancer types.

EXPERT OPINION

Through an exploration of more than 800 studies, this review has allowed to establish a general idea about state-of-art in the search of biomarkers in metabolomics studies involving cancer which include certain level of results validation. The potential for metabolites as diagnostic markers to reach the clinic and make a real difference in patient health is substantial, but challenges remain to be explored.

Unmasking the Metabolite Signature of Bladder Cancer: A Systematic Review

Bladder cancer (BCa) research relying on Omics approaches has increased over the last few decades, improving the understanding of BCa pathology and contributing to a better molecular classification of BCa subtypes. To gain further insight into the molecular profile underlying the development of BCa, a systematic literature search was performed in PubMed until November 2023, following the PRISMA guidelines. This search enabled the identification of 25 experimental studies using mass spectrometry or nuclear magnetic resonance-based approaches to characterize the metabolite signature associated with BCa. A total of 1562 metabolites were identified to be altered by BCa in different types of samples. Urine samples displayed a higher likelihood of containing metabolites that are also present in bladder tumor tissue and cell line cultures. The data from these comparisons suggest that increased concentrations of L-isoleucine, L-carnitine, oleamide, palmitamide, arachidonic acid and glycoursodeoxycholic acid and decreased content of deoxycytidine, 5-aminolevulinic acid and pantothenic acid should be considered components of a BCa metabolome signature. Overall, molecular profiling of biological samples by metabolomics is a promising approach to identifying potential biomarkers for early diagnosis of different BCa subtypes. However, future studies are needed to understand its biological significance in the context of BCa and to validate its clinical application.

Metabolites and MRI-Derived Markers of AD/ADRD Risk in a Puerto Rican Cohort

Objective

Several studies have examined metabolomic profiles in relation to Alzheimer's disease and related dementia (AD/ADRD) risk; however, few studies have focused on minorities, such as Latinos, or examined Magnetic-Resonance Imaging (MRI)-based outcomes.

Methods

We used multiple linear regression, adjusted for covariates, to examine the association between metabolite concentration and MRI-derived brain age deviation. Metabolites were measured at baseline with untargeted metabolomic profiling (Metabolon, Inc). Brain age deviation (BAD) was calculated at wave 4 (~ 9 years from Boston Puerto Rican Health Study (BPRHS) baseline) as chronologic age, minus MRI-estimated brain age, representing the rate of biological brain aging relative to chronologic age. We also examined if metabolites associated with BAD were similarly associated with hippocampal volume and global cognitive function at wave 4 in the BPRHS.

Results

Several metabolites, including isobutyrylcarnitine, propionylcarnitine, phenylacetylglutamine, phenylacetylcarnitine (acetylated peptides), p-cresol-glucuronide, phenylacetylglutamate, and trimethylamine N-oxide (TMAO) were inversely associated with brain age deviation. Taurocholate sulfate, a bile salt, was marginally associated with better brain aging. Most metabolites with negative associations with brain age deviation scores also were inversely associations with hippocampal volumes and wave 4 cognitive function.

Conclusion

The metabolites identifiedin this study are generally consistent with prior literature and highlight the role of BCAA, TMAO and microbially derived metabolites in cognitive decline.

Untargeted urinary metabolomics for bladder cancer biomarker screening with ultrahigh-resolution mass spectrometry

Bladder cancer (BC) is a common urological malignancy with a high probability of death and recurrence. Cystoscopy is used as a routine examination for diagnosis and following patient monitoring for recurrence. Repeated costly and intrusive treatments may discourage patients from having frequent follow-up screenings. Hence, exploring novel non-invasive ways to help identify recurrent and/or primary BC is critical. In this work, 200 human urine samples were profiled using ultra-high-performance liquid chromatography and ultra-high-resolution mass spectrometry (UHPLC-UHRMS) to uncover molecular markers differentiating BC from non-cancer controls (NCs). Univariate and multivariate statistical analyses with external validation identified metabolites that distinguish BC patients from NCs disease. More detailed divisions for the stage, grade, age, and gender are also discussed. Findings indicate that monitoring urine metabolites may provide a non-invasive and more straightforward diagnostic method for identifying BC and treating recurrent diseases.

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.

Integrated Analysis of Metabolomics and Lipidomics in Plasma of T2DM Patients with Diabetic Retinopathy

Diabetic retinopathy (DR) is a major cause of blindness worldwide and may be non-proliferative (NPDR) or proliferative (PDR). To Investig.gate the metabolomic and lipidomic characteristics of plasma in DR patients, plasma samples were collected from patients with type 2 diabetes mellitus (DR group) with PDR (n = 27), NPDR (n = 18), or no retinopathy (controls, n = 21). Levels of 54 and 41 metabolites were significantly altered in the plasma of DR patients under positive and negative ion modes, respectively. By subgroup analysis, 74 and 29 significantly changed plasma metabolites were detected in PDR patients compared with NPDR patients under positive and negative ion modes, respectively. KEGG analysis indicated that pathways such as biosynthesis of amino acids and neuroactive ligand-receptor interaction were among the most enriched pathways in altered metabolites in the DR group and PDR subgroup. Moreover, a total of 26 and 41 lipids were significantly changed in the DR group and the PDR subgroup, respectively. The panel using the 29-item index could discriminate effectively between diabetic patients with and without retinopathy, and the panel of 22 items showed effective discrimination between PDR and NPDR. These results provide a basis for further research into the therapeutic targets associated with these metabolite and lipid alterations.