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

Recent solid-phase microextraction-based analytical approaches for the profiling of biliary bile acids in pre-transplant assessments of liver grafts subjected to normothermic ex vivo liver perfusion

BACKGROUND

Liver transplantation is the definitive treatment for end-stage liver failure, but the scarcity of donor organs remains a significant challenge. Leveraging organs from extended criteria donors (ECD) offers a potential avenue to address worldwide shortages, though these organs are more susceptible to post-reperfusion injury. This study explores the use of normothermic ex vivo liver perfusion (NEVLP) as a method for organ preservation - an approach that sustains liver metabolism and facilitates pre-transplant assessments of organ viability via bile analysis. The focal point of this study revolves on the development of analytical methods for determining the bile acid profile throughout the peritransplantation period as a potential indicator of liver function and viability.

RESULTS

The study optimized and validated a high-throughput analytical method to quantify selected bile acids in bile samples using a thin-film microextraction-liquid chromatography-mass spectrometry (TFME-LC-MS) platform. Furthermore, it introduced a solid-phase microextraction-microfluidic open interface-mass spectrometry (SPME-MOI-MS) method for rapid direct analysis of bile acid isobar groups. In the animal study, discernible variations in the concentrations of specific bile acids were observed between donors after circulatory death (DCD) and heart-beating donors (HBD), particularly following normothermic perfusion and reperfusion. Noteworthy fluctuations in individual bile acid concentrations were observed throughout the entire organ transplantation process, with taurocholic acid (TCA), glycocholic acid (GCA), and glycochenodeoxycholic acid (GCDCA) emerging as promising indicators of organ quality. The efficacy of the SPME-MOI-MS platform in corroborating these trends highlights its potential for real-time bile acid analysis during liver transplantation procedures.

SIGNIFICANCE

Our findings underscore the efficacy of NEVLP in tandem with advanced bile acid analysis methods as a reliable strategy for pre-transplant assessments of organ viability, potentially increasing the use of ECD organs and reducing organ shortages. The ability to monitor bile acid profiles in real-time provides crucial insights into liver function and ischemic injury, making significant strides in improving transplant outcomes and patient survival rates.

Emerging biomarkers for non-invasive diagnosis and treatment of cancer: a systematic review

Cancer remains a global health challenge, necessitating continuous advancements in diagnostic and treatment strategies. This review focuses on the utility of non-invasive biomarkers in cancer diagnosis and treatment, their role in early detection, disease monitoring, and personalized therapeutic interventions. Through a systematic review of the literature, we identified 45 relevant studies that highlight the potential of these biomarkers across various cancer types, such as breast, prostate, lung, and colorectal cancers. The non-invasive biomarkers discussed include liquid biopsies, epigenetic markers, non-coding RNAs, exosomal cargo, and metabolites. Notably, liquid biopsies, particularly those based on circulating tumour DNA (ctDNA), have emerged as the most promising method for early, non-invasive cancer detection due to their ability to provide comprehensive genetic and epigenetic information from easily accessible blood samples. This review demonstrates how non-invasive biomarkers can facilitate early cancer detection, accurate subtyping, and tailored treatment strategies, thereby improving patient outcomes. It underscores the transformative potential of non-invasive biomarkers in oncology, highlighting their application for enhancing early detection, survival rates, and treatment precision in cancer care.

Systematic review registration

https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023474749 PROSPERO, identifier CRD42023474749.

Metabolomics for the diagnosis of bladder cancer: A systematic review

Objective

Metabolomics has been extensively utilized in bladder cancer (BCa) research, employing mass spectrometry and nuclear magnetic resonance spectroscopy to compare various variables (tissues, serum, blood, and urine). This study aimed to identify potential biomarkers for early BCa diagnosis.

Methods

A search strategy was designed to identify clinical trials, descriptive and analytical observational studies from databases such as Medline, Embase, Cochrane Central Register of Controlled Trials, and Latin American and Caribbean Literature in Health Sciences. Inclusion criteria comprised studies involving BCa tissue, serum, blood, or urine profiling using widely adopted metabolomics techniques like mass spectrometry and nuclear magnetic resonance. Primary outcomes included description of metabolites and metabolomics profiling in BCa patients and the association of metabolites and metabolomics profiling with BCa diagnosis compared to control patients. The risk of bias was assessed using the Quality Assessment of Studies of Diagnostic Accuracy.

Results

The search strategy yielded 2832 studies, of which 30 case-control studies were included. Urine was predominantly used as the primary sample for metabolite identification. Risk of bias was often unclear inpatient selection, blinding of the index test, and reference standard assessment, but no applicability concerns were observed. Metabolites and metabolomics profiles associated with BCa diagnosis were identified in glucose, amino acids, nucleotides, lipids, and aldehydes metabolism.

Conclusion

The identified metabolites in urine included citric acid, valine, tryptophan, taurine, aspartic acid, uridine, ribose, phosphocholine, and carnitine. Tissue samples exhibited elevated levels of lactic acid, amino acids, and lipids. Consistent findings across tissue, urine, and serum samples revealed downregulation of citric acid and upregulation of lactic acid, valine, tryptophan, taurine, glutamine, aspartic acid, uridine, ribose, and phosphocholine.

Advances in mass spectrometry imaging for spatial cancer metabolomics

Mass spectrometry (MS) has become a central technique in cancer research. The ability to analyze various types of biomolecules in complex biological matrices makes it well suited for understanding biochemical alterations associated with disease progression. Different biological samples, including serum, urine, saliva, and tissues have been successfully analyzed using mass spectrometry. In particular, spatial metabolomics using MS imaging (MSI) allows the direct visualization of metabolite distributions in tissues, thus enabling in-depth understanding of cancer-associated biochemical changes within specific structures. In recent years, MSI studies have been increasingly used to uncover metabolic reprogramming associated with cancer development, enabling the discovery of key biomarkers with potential for cancer diagnostics. In this review, we aim to cover the basic principles of MSI experiments for the nonspecialists, including fundamentals, the sample preparation process, the evolution of the mass spectrometry techniques used, and data analysis strategies. We also review MSI advances associated with cancer research in the last 5 years, including spatial lipidomics and glycomics, the adoption of three-dimensional and multimodal imaging MSI approaches, and the implementation of artificial intelligence/machine learning in MSI-based cancer studies. The adoption of MSI in clinical research and for single-cell metabolomics is also discussed. Spatially resolved studies on other small molecule metabolites such as amino acids, polyamines, and nucleotides/nucleosides will not be discussed in the context.

Metabolomic biomarkers in liquid biopsy: accurate cancer diagnosis and prognosis monitoring

Liquid biopsy, a novel detection method, has recently become an active research area in clinical cancer owing to its unique advantages. Studies on circulating free DNA, circulating tumor cells, and exosomes obtained by liquid biopsy have shown great advances and they have entered clinical practice as new cancer biomarkers. The metabolism of the body is dynamic as cancer originates and progresses. Metabolic abnormalities caused by cancer can be detected in the blood, sputum, urine, and other biological fluids via systemic or local circulation. A considerable number of recent studies have focused on the roles of metabolic molecules in cancer. The purpose of this review is to provide an overview of metabolic markers from various biological fluids in the latest clinical studies, which may contribute to cancer screening and diagnosis, differentiation of cancer typing, grading and staging, and prediction of therapeutic response and prognosis.

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.

Solid-Phase Microextraction and Related Techniques in Bioanalysis

Living organisms, such as microorganisms, plants and animals, are composed of complex constituents, which may include bioactive components that maintain their functions [...]

Disentangling the Complexity of Nutrition, Frailty and Gut Microbial Pathways during Aging: A Focus on Hippuric Acid

Hippuric acid (HA) is a metabolite resulting from the hepatic glycine conjugation of benzoic acid (BA) or from the gut bacterial metabolism of phenylalanine. BA is generally produced by gut microbial metabolic pathways after the ingestion of foods of vegetal origin rich in polyphenolic compounds, namely, chlorogenic acids or epicatechins. It can also be present in foods, either naturally or artificially added as a preservative. The plasma and urine HA levels have been used in nutritional research for estimating the habitual fruit and vegetable intake, especially in children and in patients with metabolic diseases. HA has also been proposed as a biomarker of aging, since its levels in the plasma and urine can be influenced by the presence of several age-related conditions, including frailty, sarcopenia and cognitive impairment. Subjects with physical frailty generally exhibit reduced plasma and urine levels of HA, despite the fact that HA excretion tends to increase with aging. Conversely, subjects with chronic kidney disease exhibit reduced HA clearance, with HA retention that may exert toxic effects on the circulation, brain and kidneys. With regard to older patients with frailty and multimorbidity, interpreting the HA levels in the plasma and urine may result particularly challenging because HA is at the crossroads between diet, gut microbiota, liver and kidney function. Although these considerations may not make HA the ideal biomarker of aging trajectories, the study of its metabolism and clearance in older subjects may provide valuable information for disentangling the complex interaction between diet, gut microbiota, frailty and multimorbidity.

Biliary Metabolome Profiling for Evaluation of Liver Metabolism and Biliary Tract Function Related to Organ Preservation Method and Degree of Ischemia in a Porcine Model

The development of surgical techniques, immunosuppressive strategies and new organ preservation methods have meant that transplant centers have to face the problem of an insufficient number of organs for transplantation concerning the constantly growing demand. Therefore, using organs from expanded criteria donors and developing new analytical solutions to find parameters or compounds that would allow a more efficient assessment of organ quality before transplantation are options for meeting this challenge. This study proposed bile metabolomic analysis to evaluate liver metabolism and biliary tract function depending on the organ preservation method and degree of warm ischemia time. The analyses were performed on solid-phase microextraction-prepared bile samples from porcine model donors with mild (heart beating donor [HBD]) and moderate warm ischemia (donation after circulatory death [DCD]) grafts subjected to static cold storage (SCS) or normothermic ex vivo liver perfusion (NEVLP) before transplantation. Bile produced in the SCS-preserved livers was characterized by increased levels of metabolites such as chenodeoxycholic acid, arachidonic acid and 5S-hydroxyeicosatetraeonic acid, as well as saturated and monounsaturated lysophosphatidylcholines (LPC). Such changes may be associated with differences in the bile acid synthesis pathways and organ inflammation. Moreover, it has been shown that NEVLP reduced the negative effect of ischemia on organ function. A linear relationship was observed between levels of lipids from the LPC group and the time of organ ischemia. This study identified metabolites worth considering as potential markers of changes occurring in preserved grafts.

Development of the thin film solid phase microextraction (TF-SPME) method for metabolomics profiling of steroidal hormones from urine samples using LC-QTOF/MS

In the present study, the development and optimization of a thin film solid phase microextraction method (TF-SPME) was conducted for metabolomics profiling of eight steroid compounds (androsterone, dihydrotestosterone, dihydroepiandrosterone, estradiol, hydroxyprogesterone, pregnenolone, progesterone and testosterone) from urine samples. For optimization of extraction method, two extraction sorbents (PAN-C18 and PS-DVB) were used as they are known to be effective for isolation of low-polarity analytes. The stages of sample extraction and analyte desorption were considered as the most crucial steps in the process. Regarding the selection of the most suitable desorption solution, six different mixtures were analyzed. As a result, the mixture of ACN: MeOH (1:1, v/v) was chosen in terms of the highest analytes' abundances that were achieved using the chosen solvent. Besides other factors were examined such as the volume of desorption solvent and the time of both extraction and desorption processes. The analytical determination was carried out using the ultra-high performance liquid chromatography coupled with high resolution tandem mass spectrometry detection in electrospray ionization and positive polarity in a scan mode (UHPLC-ESI-QTOF/MS). The developed and optimized TF-SPME method was validated in terms of such parameters as extraction efficiency, recovery as well as matrix effect. As a result, the extraction efficiency and recovery were in a range from 79.3% to 99.2% and from 88.8% to 111.8%, respectively. Matrix effect, calculated as coefficient of variation was less than 15% and was in a range from 1.4% to 11.1%. The values of both validation parameters (recovery and matrix effect) were acceptable in terms of EMA criteria. The proposed TF-SPME method was used successfully for isolation of steroids hormones from pooled urine samples before and after enzymatic hydrolysis of analytes.

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.

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.

GC-MS based metabolite fingerprinting of serous ovarian carcinoma and benign ovarian tumor

The aim of this study is to identify urinary metabolomic profile of benign and malign ovarian tumors patients. Samples were analyzed using gas chromatography-mass spectrometry (GC-MS) and metabolomic tools to define biomarkers that cause differentiation between groups. 7 metabolites were found to be different in patients with ovarian cancer (OC) and benign tumors (BT). R2Y and Q2 values were found to be 0.670 and 0.459, respectively. L-tyrosine, glycine, stearic acid, turanose and L-threonine metabolites were defined as prominent biomarkers. The sensitivity of the model was calculated as 90.72% and the specificity as 82.09%. In the pathway analysis, glutathione metabolism, aminoacyl-tRNA biosynthesis, glycine serine and threonine metabolic pathway, primary bile acid biosynthesis pathways were found to be important. According to the t-test, 29 metabolites were found to be significant in urine samples of OC patients and healthy controls (HC). R2Y and Q2 values were found to be 0.8170 and 0.749, respectively. These results showed that the model has high compatibility and predictive power. Benzoic acid, L-threonine, L-pyroglutamic acid, creatinine and 3,4-dihydroxyphenylacetic acid metabolites were determined as prominent biomarkers. The sensitivity of the model was calculated as 93.81% and the specificity as 98.59%. Glycine serine and threonine metabolic pathway, glutathione metabolism and aminoacyl-tRNA biosynthesis pathways were determined important in OC patients and HC. The R2Y, Q2, sensitivity and specificity values in the urine samples of BT patients and HC were found to be 0.869, 0.794, 91.75, 97.01% and 97.18%, respectively. L-threonine, L-pyroglutamic acid, benzoic acid, creatinine and pentadecanol metabolites were determined as prominent biomarkers. Valine, leucine and isoleucine biosynthesis and aminoacyl-tRNA biosynthesis were significant. In this study, thanks to the untargeted metabolomic approach and chemometric methods, every group was differentiated from the others and prominent biomarkers were determined.

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.

Improving data quality in liquid chromatography-mass spectrometry metabolomics of human urine

Signal variation is a common drawback in untargeted metabolomics using liquid chromatography-mass spectrometry (LC-MS), mainly due to the complexity of biological matrices and reduced sample preparation, which results in the accumulation of sample components in the column and the ion source. Here we propose a simple, easy to implement approach to improve data quality in untargeted metabolomics by LC-MS. This approach involves the use of a divert valve to direct the column effluent to waste at the beginning of the chromatographic run and during column cleanup and equilibration, in combination with longer column cleanups in between injections. Our approach was tested using urine samples collected from patients after renal transplantation. Analytical responses were contrasted before and after introducing these modifications by analyzing a batch of untargeted metabolomics data. A significant improvement in peak area repeatability was observed for the quality controls, with relative standard deviations (RSDs) for several metabolites decreasing from ∼60% to ∼10% when our approach was introduced. Similarly, RSDs of peak areas for internal standards improved from ∼40% to ∼10%. Furthermore, calibrant solutions were more consistent after introducing these modifications when comparing peak areas of solutions injected at the beginning and the end of each analytical sequence. Therefore, we recommend the use of a divert valve and extended column cleanup as a powerful strategy to improve data quality in untargeted metabolomics, especially for very complex types of samples where minimum sample preparation is required, such as in this untargeted metabolomics study with urine from renal transplanted patients.

High Performance Liquid Chromatography-Tandem Mass Spectrometry Method for Correlating the Metabolic Changes of Lactate, Pyruvate and L-Glutamine with Induced Tamoxifen Resistant MCF-7 Cell Line Potential Molecular Changes

Breast cancer is one of the most prevalent cancers worldwide usually treated with Tamoxifen. Tamoxifen resistance development is the most challenging issue in an initially responsive breast tumor, and mechanisms of resistance are still under investigation. The objective of this study is to develop and validate a selective, sensitive, and simultaneous high performance liquid chromatography–tandem mass spectrometry method to explore the changes in substrates and metabolites in supernatant media of developed Tamoxifen resistance MCF-7 cells. We focus on the determination of lactate, pyruvate, and L-glutamine which enables the tracking of changes in metabolic pathways as a result of the resistance process. Chromatographic separation was achieved within 3.5 min. using a HILIC column (4.6 × 100 mm, 3.5 µm particle size) and mobile phase of 0.05 M acetic acid–ammonium acetate buffer solution pH 3.0: Acetonitrile (40:60 v/v). The linear range was 0.11–2.25, 0.012–0.227, and 0.02–0.20 mM for lactate, pyruvate, and L-glutamine, respectively. Within- and between-run accuracy was in the range 98.94-105.50% with precision (CV, %) of ≤0.86%. The results revealed a significant increase in both lactate and pyruvate production after acquiring the resistant. An increase in L-glutamine levels was also observed and could be attributed to its over production or decline in its consumption. Therefore, further tracking of genes responsible of lactate, pyruvate, and glutamine metabolic pathways should be performed in parallel to provide in-depth explanation of resistance mechanism.

Benefits of Innovative and Fully Water-Compatible Stationary Phases of Thin-Film Microextraction (TFME) Blades

Octadecyl (C₁₈) groups are arguably the most popular ligands used for preparation of solid phase microextraction (SPME) devices. However, conventional C₁₈-bonded silica particles are not fully compatible with the nearly 100% aqueous composition of typical biological samples (e.g., plasma, saliva, or urine). This study presents the first evaluation of thin-film SPME devices coated with special water-compatible C₁₈-bonded particles. Device performance was assessed by extracting a mixture of 30 model compounds that exhibited various chemical structures and properties, such as hydrophobicity. Additionally, nine unique compositions of desorption solvents were tested. Thin-film SPME devices coated with C₁₈-bonded silica particles with polar end-capping groups (10 µm) were compared with conventional trimethylsilane end-capped C₁₈-bonded silica particles of various sizes (5, 10, and 45 µm) and characteristics. Polar end-capped particles provided the best extraction efficacy and were characterized by the strongest correlations between the efficacy of the extraction process and the hydrophobicity of the analytes. The results suggest that the original features of octadecyl ligands are best preserved in aqueous conditions by polar end-capped particles, unlike with conventional trimethylsilane end-capped particles that are currently used to prepare SPME devices. The benefits associated with this improved type of coating encourage further implementation of microextractraction as greener alternative to the traditional sample preparation methods.