Rapid Prostate Cancer Noninvasive Biomarker Screening Using Segmented Flow Mass Spectrometry-Based Untargeted Metabolomics

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.

Point-of-care applicable metabotyping using biofluid-specific electrospun MetaSAMPs directly amenable to ambient LA-REIMS

In recent years, ambient ionization mass spectrometry (AIMS) including laser ablation rapid evaporation IMS, has enabled direct biofluid metabolome analysis. AIMS procedures are, however, still hampered by both analytical, i.e., matrix effects, and practical, i.e., sample transport stability, drawbacks that impede metabolome coverage. In this study, we aimed at developing biofluid-specific metabolome sampling membranes (MetaSAMPs) that offer a directly applicable and stabilizing substrate for AIMS. Customized rectal, salivary, and urinary MetaSAMPs consisting of electrospun (nano)fibrous membranes of blended hydrophilic (polyvinylpyrrolidone and polyacrylonitrile) and lipophilic (polystyrene) polymers supported metabolite absorption, adsorption, and desorption. Moreover, MetaSAMP demonstrated superior metabolome coverage and transport stability compared to crude biofluid analysis and was successfully validated in two pediatric cohorts (MetaBEAse, n = 234 and OPERA, n = 101). By integrating anthropometric and (patho)physiological with MetaSAMP-AIMS metabolome data, we obtained substantial weight-driven predictions and clinical correlations. In conclusion, MetaSAMP holds great clinical application potential for on-the-spot metabolic health stratification.

Design of a printed electrochemical strip towards miRNA-21 detection in urine samples: optimization of the experimental procedures for real sample application

MicroRNAs (miRNAs) are clinical biomarkers for various human diseases, including cancer. They have been found in liquid biopsy samples, including various bodily fluids. They often play an important role in the early diagnosis and prognosis of cancer, and the development of simple and effective analytical methods would be of pivotal importance for the entire community. The determination of these targets may be affected by the different physicochemical parameters of the specimen of interest. In this work, an electrochemical detection platform for miRNA based on a screen-printed gold electrode was developed. In the present study, miRNA-21 was selected as a model sequence, due to its role in prostate, breast, colon, pancreatic, and liver cancers. A DNA sequence modified with methylene blue (MB) was covalently bound to the electrochemical strip and used to detect the selected target miRNA-21. After optimization of selected parameters in standard solutions, including the study of the effect of pH, the presence of interferent species, and NaCl salt concentration in the background, the application of square-wave voltammetry (SWV) technique allowed the detection of miRNA-21 down to a limit in the order of 2 nM. The developed device was then applied to several urine samples. In this case too, the device showed high selectivity in the presence of the complex matrix, satisfactory repeatability, and a limit of detection in the order of magnitude of nM, similarly as what observed in standard solutions.

Canine-Inspired Chemometric Analysis of Volatile Organic Compounds in Urine Headspace to Distinguish Prostate Cancer in Mice and Men

Canines can identify prostate cancer with high accuracy by smelling volatile organic compounds (VOCs) in urine. Previous studies have identified VOC biomarkers for prostate cancer utilizing solid phase microextraction (SPME) gas chromatography-mass spectrometry (GC-MS) but have not assessed the ability of VOCs to distinguish aggressive cancers. Additionally, previous investigations have utilized murine models to identify biomarkers but have not determined if the results are translatable to humans. To address these challenges, urine was collected from mice with prostate cancer and men undergoing prostate cancer biopsy and VOCs were analyzed by SPME GC-MS. Prior to analysis, SPME fibers/arrows were compared, and the fibers had enhanced sensitivity toward VOCs with a low molecular weight. The analysis of mouse urine demonstrated that VOCs could distinguish tumor-bearing mice with 100% accuracy. Linear discriminant analysis of six VOCs in human urine distinguished prostate cancer with sensitivity = 75% and specificity = 69%. Another panel of seven VOCs could classify aggressive cancer with sensitivity = 78% and specificity = 85%. These results show that VOCs have moderate accuracy in detecting prostate cancer and a superior ability to stratify aggressive tumors. Furthermore, the overlap in the structure of VOCs identified in humans and mice shows the merit of murine models for identifying biomarker candidates.

Metal-Polyphenol Network-Mediated Protein Encapsulation Strategy Facilitating the Separation of Proteins and Metabolites in Biospecimens

Access to both protein and metabolite biomarker information in biospecimens from trace samples remains a significant challenge, and it is necessary to separate proteins and metabolites before analysis. In this work, the Fe₃O₄@SiO₂@Proteins@Metal-polyphenol network (MPN) was successfully constructed and applied to separate metabolites and proteins. Tannic acid (TA) and Cu²⁺ were involved in the synthesis of MPN because of rapid degradation and maintaining the assay performance of proteins. There are a variety of interactions between TA and proteins, including hydrogen-bonding, hydrophobic, and ionic interactions. Moreover, benefiting from the small molecule permeability and surface adherence of MPN, proteins were encapsulated and immobilized on the surface of substrates with the growth of MPN. At the same time, endogenous metabolites remained dispersed in the supernatant. In the model sample and real biospecimen cases, the protein biomarkers (e.g., carcinoembryonic antigen and alanine aminotransferase) were encapsulated on the surface of Fe₃O₄@SiO₂, which allowed the isolation of proteins from the original matrix, as well as release and analysis in a short time. Meanwhile, the metabolites in the produced supernatant were analyzed by LC-MS/MS. By the self-assembly and disassembly of MPN, the group differences of proteins and metabolites between physiological and pathological biospecimens are correctly characterized without multisampling. Overall, an MPN-mediated separation strategy of biomarkers was proposed, and MPN facilitated a "two birds with one stone" approach, where the proteins were encapsulated and immobilized in the precipitation while endogenous metabolites distributed in the produced supernatant, opening a new chapter in the application of MPNs.

Metabolic fingerprinting of chemotherapy-resistant prostate cancer stem cells. An untargeted metabolomic approach by liquid chromatography-mass spectrometry

Chemoresistance is one of the most important challenges in cancer therapy. The presence of cancer stem cells within the tumor may contribute to chemotherapy resistance since these cells express high levels of extrusion pumps and xenobiotic metabolizing enzymes that inactivate the therapeutic drug. Despite the recent advances in cancer cell metabolism adaptations, little is known about the metabolic adaptations of the cancer stem cells resistant to chemotherapy. In this study, we have undertaken an untargeted metabolomic analysis by liquid chromatography–high-resolution spectrometry combined with cytotoxicity assay, western blot, quantitative real-time polymerase chain reaction (qPCR), and fatty acid oxidation in a prostate cancer cell line resistant to the antiandrogen 2-hydroxiflutamide with features of cancer stem cells, compared to its parental androgen-sensitive cell line. Metabolic fingerprinting revealed 106 out of the 850 metabolites in ESI+ and 67 out of 446 in ESI- with significant differences between the sensitive and the resistant cell lines. Pathway analysis performed with the unequivocally identified metabolites, revealed changes in pathways involved in energy metabolism as well as posttranscriptional regulation. Validation by enzyme expression analysis indicated that the chemotherapy-resistant prostate cancer stem cells were metabolically dormant with decreased fatty acid oxidation, methionine metabolism and ADP-ribosylation. Our results shed light on the pathways underlying the entry of cancer cells into dormancy that might contribute to the mechanisms of drug resistance.

A narrative review of metabolomics in the era of "-omics": integration into clinical practice for inborn errors of metabolism

BACKGROUND AND OBJECTIVE

Traditional targeted metabolomic investigations identify a pre-defined list of analytes in samples and have been widely used for decades in the diagnosis and monitoring of inborn errors of metabolism (IEMs). Recent technological advances have resulted in the development and maturation of untargeted metabolomics: a holistic, unbiased, analytical approach to detecting metabolic disturbances in human disease. We aim to provide a summary of untargeted metabolomics [focusing on tandem mass spectrometry (MS-MS)] and its application in the field of IEMs.

METHODS

Data for this review was identified through a literature search using PubMed, Google Scholar, and personal repositories of articles collected by the authors. Findings are presented within several sections describing the metabolome, the current use of targeted metabolomics in the diagnostic pathway of patients with IEMs, the more recent integration of untargeted metabolomics into clinical care, and the limitations of this newly employed analytical technique.

KEY CONTENT AND FINDINGS

Untargeted metabolomic investigations are increasingly utilized in screening for rare disorders, improving understanding of cellular and subcellular physiology, discovering novel biomarkers, monitoring therapy, and functionally validating genomic variants. Although the untargeted metabolomic approach has some limitations, this "next generation metabolic screening" platform is becoming increasingly affordable and accessible.

CONCLUSIONS

When used in conjunction with genomics and the other promising "-omic" technologies, untargeted metabolomics has the potential to revolutionize the diagnostics of IEMs (and other rare disorders), improving both clinical and health economic outcomes.

Exploring the Role of 2D-Graphdiyne as a Charge Carrier Layer in Field-Effect Transistors for Non-Covalent Biological Immobilization against Human Diseases

Graphdiyne's (GDY's) outstanding features have made it a novel 2D nanomaterial and a great candidate for electronic gadgets and optoelectronic devices, and it has opened new opportunities for the development of highly sensitive electronic and optical detection methods as well. Here, we testified a non-covalent grafting strategy in which GDY serves as a charge carrier layer and a bioaffinity substrate to immobilize biological receptors on GDY-based field-effect transistor (FET) devices. Firm non-covalent anchoring of biological molecules via pyrene groups and electrostatic interactions in addition to preserved electrical properties of GDY endows it with features of an ultrasensitive and stable detection mechanism. With emerging new forms and extending the subtypes of the already existing fatal diseases, genetic and biological knowledge demands more details. In this regard, we constructed simple yet efficient platforms using GDY-based FET devices in order to detect different kinds of biological molecules that threaten human health. The resulted data showed that the proposed non-covalent bioaffinity assays in GDY-based FET devices could be considered reliable strategies for novel label-free biosensing platforms, which still reach a high on/off ratio of over 10⁴. The limits of detection of the FET devices to detect DNA strands, the CA19-9 antigen, microRNA-155, the CA15-3 antigen, and the COVID-19 antigen were 0.2 aM, 0.04 pU mL^-1, 0.11 aM, 0.043 pU mL^-1, and 0.003 fg mL^-1, respectively, in the linear ranges of 1 aM to 1 pM, 1 pU mL^-1 to 0.1 μU mL^-1, 1 aM to 1 pM, 1 pU mL^-1 to 10 μU mL^-1, and 1 fg mL^-1 to 10 ng mL^-1, respectively. Finally, the extraordinary performance of these label-free FET biosensors with low detection limits, high sensitivity and selectivity, capable of being miniaturized, and implantability for in vivo analysis makes them a great candidate in disease diagnostics and point-of-care testing.

The Biosynthesis and Metabolism of the N-Acylated Aromatic Amino Acids: N-Acylphenylalanine, N-Acyltyrosine, N-Acyltryptophan, and N-Acylhistidine

The fatty acid amides are a family of lipids composed of two chemical moieties, a fatty acid and a biogenic amine linked together in an amide bond. This lipid family is structurally related to the endocannabinoid anandamide (N-arachidonoylethanolamine) and, thus, is frequently referred to as a family of endocannabinoid-related lipids. The fatty acid amide family is divided into different classes based on the conjugate amine; anandamide being a member of the N-acylethanolamine class (NAE). Another class within the fatty acid amide family is the N-acyl amino acids (NA-AAs). The focus of this review is a sub-class of the NA-AAs, the N-acyl aromatic amino acids (NA-ArAAs). The NA-ArAAs are not broadly recognized, even by those interested in the endocannabinoids and endocannabinoid-related lipids. Herein, the NA-ArAAs that have been identified from a biological source will be highlighted and pathways for their biosynthesis, degradation, enzymatic modification, and transport will be presented. Also, information about the cellular functions of the NA-ArAAs will be placed in context with the data regarding the identification and metabolism of these N-acylated amino acids. A review of the current state-of-knowledge about the NA-ArAAs is to stimulate future research about this underappreciated sub-class of the fatty acid amide family.

Untargeted urine metabolite profiling by mass spectrometry aided by multivariate statistical analysis to predict prostate cancer treatment outcome

One of the key barriers to the prostate cancer is monitor treatment response. Here we described a conceptually new ‘MS-statistical analysis-metabolome’ strategy for discovery of metabolic features.

Droplet-assisted electrospray phase separation using an integrated silicon microfluidic platform

We report a silicon microfluidic platform that enables monolithic integration of transparent micron-scale microfluidic channels, an on-chip segmentation of analyte flows into picoliter-volume droplets, and a nano-electrospray ionization emitter that enables spatial and temporal separation of oil and aqueous phases during electro-spray for subsequent mass spectrometry analysis.

Nontargeted Analysis Study Reporting Tool: A Framework to Improve Research Transparency and Reproducibility

Non-targeted analysis (NTA) workflows using mass spectrometry are gaining popularity in many disciplines, but universally accepted reporting standards are nonexistent. Current guidance addresses limited elements of NTA reporting-most notably, identification confidence-and is insufficient to ensure scientific transparency and reproducibility given the complexity of these methods. This lack of reporting standards hinders researchers' development of thorough study protocols and reviewers' ability to efficiently assess grant and manuscript submissions. To overcome these challenges, we developed the NTA Study Reporting Tool (SRT), an easy-to-use, interdisciplinary framework for comprehensive NTA methods and results reporting. Eleven NTA practitioners reviewed eight published articles covering environmental, food, and health-based exposomic applications with the SRT. Overall, our analysis demonstrated that the SRT provides a valid structure to guide study design and manuscript writing, as well as to evaluate NTA reporting quality. Scores self-assigned by authors fell within the range of peer-reviewer scores, indicating that SRT use for self-evaluation will strengthen reporting practices. The results also highlighted NTA reporting areas that need immediate improvement, such as analytical sequence and quality assurance/quality control information. Although scores intentionally do not correspond to data/results quality, widespread implementation of the SRT could improve study design and standardize reporting practices, ultimately leading to broader use and acceptance of NTA data.

Challenges in LC-MS-based metabolomics for Alzheimer's disease early detection: targeted approaches versus untargeted approaches

BACKGROUND

Alzheimer's disease (AD) is one of the most common causes of dementia in old people. Neuronal deficits such as loss of memory, language and problem-solving are severely compromised in affected patients. The molecular features of AD are Aβ deposits in plaques or in oligomeric structures and neurofibrillary tau tangles in brain. However, the challenge is that Aβ is only one piece of the puzzle, and recent findings continue to support the hypothesis that their presence is not sufficient to predict decline along the AD outcome. In this regard, metabolomic-based techniques are acquiring a growing interest for either the early diagnosis of diseases or the therapy monitoring. Mass spectrometry is one the most common analytical platforms used for detection, quantification, and characterization of metabolic biomarkers. In the past years, both targeted and untargeted strategies have been applied to identify possible interesting compounds.

AIM OF REVIEW

The overall goal of this review is to guide the reader through the most recent studies in which LC-MS-based metabolomics has been proposed as a powerful tool for the identification of new diagnostic biomarkers in AD. To this aim, herein studies spanning the period 2009-2020 have been reported. Advantages and disadvantages of targeted vs untargeted metabolomic approaches have been outlined and critically discussed.

Mitochondrial transcription factor A in RORγt+ lymphocytes regulate small intestine homeostasis and metabolism

RORγt+ lymphocytes, including interleukin 17 (IL-17)-producing gamma delta T (γδT17) cells, T helper 17 (Th17) cells, and group 3 innate lymphoid cells (ILC3s), are important immune regulators. Compared to Th17 cells and ILC3s, γδT17 cell metabolism and its role in tissue homeostasis remains poorly understood. Here, we report that the tissue milieu shapes splenic and intestinal γδT17 cell gene signatures. Conditional deletion of mitochondrial transcription factor A (Tfam) in RORγt+ lymphocytes significantly affects systemic γδT17 cell maintenance and reduces ILC3s without affecting Th17 cells in the gut. In vivo deletion of Tfam in RORγt+ lymphocytes, especially in γδT17 cells, results in small intestine tissue remodeling and increases small intestine length by enhancing the type 2 immune responses in mice. Moreover, these mice show dysregulation of the small intestine transcriptome and metabolism with less body weight but enhanced anti-helminth immunity. IL-22, a cytokine produced by RORγt+ lymphocytes inhibits IL-13-induced tuft cell differentiation in vitro, and suppresses the tuft cell-type 2 immune circuit and small intestine lengthening in vivo, highlighting its key role in gut tissue remodeling.

Rapid Diagnosis of Prostate Cancer Disease Progression Using Paper Spray Ionization Mass Spectrometry

The limitation of prostate specific antigen (PSA) for prostate cancer (PC) diagnosis is well-recognized. The Gleason score (GS) has been the most widely used grading system for prostate tumor differentiation and represents the best-established prognostic indicator for prostate cancer progression. However, a rapid and sensitive noninvasive diagnostic marker that differentiates GS-based prostate cancer disease progression is needed. As PC is becoming a leading cause of cancer related death for men in the U.S. and worldwide, an immediate need exists for an improved, sensitive, noninvasive, and rapid diagnostic test for PC screening. Here, we employed paper spray ionization-mass spectrometry (PSI MS)-based global metabolomics of urine liquid biopsies to distinguish between healthy (negative for any prostate specific health problems) and progressive PC states (low grade PC such as GS6 and high-grade PC such as GS7, GS8, and GS9). For PSI-MS-based direct untargeted metabolic investigation, a raw urine sample was directly pipetted onto a triangular paper substrate, without any additional sample preparation. Multivariate statistical analysis revealed distinct GS-specific metabolic signatures compared to a healthy control. Variable importance in projection from partial least-squares-discriminant analysis showed distinct metabolic patterns that were correlatively elevated with progressive disease and could serve as biomarkers for diagnosis of prostate cancer risk categorization.

Flow-based System: A Highly Efficient Tool Speeds Up Data Production and Improves Analytical Performance

In this review, we cite references from the period between 2015 and 2020 related to the use of a flow-based system as a tool to obtain a modern analytical system for speeding up data production and improving performance. Based on a great deal of concepts for automatic systems, there are several research groups introduced in the development of flow-based systems to increase sample throughput while retaining the reproducibility and repeatability as well as to propose new platforms of flow-based systems, such as microfluidic chip and paper-based devices. Additionally, to apply a developed system for on-site analysis is one of the key features for development. We believe that this review will be very interested and useful for readers because of its impact on developing novel analytical systems. The content of the review is categorized following their applications including quality control and food safety, clinical diagnostics, environmental monitoring and miscellaneous.

Mass Spectrometry Techniques in Emerging Pathogens Studies: COVID-19 Perspectives

As corona virus disease 2019 (COVID-19) is a rapidly growing public health crisis across the world, our knowledge of meaningful diagnostic tests and treatment for severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) is still evolving. This novel coronavirus disease COVID-19 can be diagnosed using RT-PCR, but inadequate access to reagents, equipment, and a nonspecific target has slowed disease detection and management. Precision medicine, individualized patient care, requires suitable diagnostics approaches to tackle the challenging aspects of viral outbreaks where many tests are needed in a rapid and deployable approach. Mass spectrometry (MS)-based technologies such as proteomics, glycomics, lipidomics, and metabolomics have been applied in disease outbreaks for identification of infectious disease agents such as virus and bacteria and the molecular phenomena associated with pathogenesis. Matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF/MS) is widely used in clinical diagnostics in the United States and Europe for bacterial pathogen identification. Paper spray ionization mass spectrometry (PSI-MS), a rapid ambient MS technique, has recently open a new opportunity for future clinical investigation to diagnose pathogens. Ultra-high-pressure liquid chromatography coupled high-resolution mass spectrometry (UHPLC-HRMS)-based metabolomics and lipidomics have been employed in large-scale biomedical research to discriminate infectious pathogens and uncover biomarkers associated with pathogenesis. PCR-MS has emerged as a new technology with the capability to directly identify known pathogens from the clinical specimens and the potential to identify genetic evidence of undiscovered pathogens. Moreover, miniaturized MS offers possible applications with relatively fast, highly sensitive, and potentially portable ways to analyze for viral compounds. However, beneficial aspects of these rapidly growing MS technologies in pandemics like COVID-19 outbreaks has been limited. Hence, this perspective gives a brief of the existing knowledge, current challenges, and opportunities for MS-based techniques as a promising avenue in studying emerging pathogen outbreaks such as COVID-19.

Prostate cancer management: long-term beliefs, epidemic developments in the early twenty-first century and 3PM dimensional solutions

In the early twenty-first century, societies around the world are facing the paradoxal epidemic development of PCa as a non-communicable disease. PCa is the most frequently diagnosed cancer for men in several countries such as the USA. Permanently improving diagnostics and treatments in the PCa management causes an impressive divergence between, on one hand, permanently increasing numbers of diagnosed PCa cases and, on the other hand, stable or even slightly decreasing mortality rates. Still, aspects listed below are waiting for innovate solutions in the context of predictive approaches, targeted prevention and personalisation of medical care (PPPM / 3PM).A.PCa belongs to the cancer types with the highest incidence worldwide. Corresponding economic burden is enormous. Moreover, the costs of treating PCa are currently increasing more quickly than those of any other cancer. Implementing individualised patient profiles and adapted treatment algorithms would make currently too heterogeneous landscape of PCa treatment costs more transparent providing clear "road map" for the cost saving.B.PCa is a systemic multi-factorial disease. Consequently, predictive diagnostics by liquid biopsy analysis is instrumental for the disease prediction, targeted prevention and curative treatments at early stages.C.The incidence of metastasising PCa is rapidly increasing particularly in younger populations. Exemplified by trends observed in the USA, prognosis is that the annual burden will increase by over 40% in 2025. To this end, one of the evident deficits is the reactive character of medical services currently provided to populations. Innovative screening programmes might be useful to identify persons in suboptimal health conditions before the clinical onset of metastasising PCa. Strong predisposition to systemic hypoxic conditions and ischemic lesions (e.g. characteristic for individuals with Flammer syndrome phenotype) and low-grade inflammation might be indicative for specific phenotyping and genotyping in metastasising PCa screening and disease management. Predictive liquid biopsy tests for CTC enumeration and their molecular characterisation are considered to be useful for secondary prevention of metastatic disease in PCa patients.D.Particular rapidly increasing PCa incidence rates are characteristic for adolescents and young adults aged 15-40 years. Patients with early onset prostate cancer pose unique challenges; multi-factorial risks for these trends are proposed. Consequently, multi-level diagnostics including phenotyping and multi-omics are considered to be the most appropriate tool for the risk assessment, prediction and prognosis. Accumulating evidence suggests that early onset prostate cancer is a distinct phenotype from both aetiological and clinical perspectives deserving particular attention from view point of 3P medical approaches.