Omics-Based Approaches for the Characterization of Pompe Disease Metabolic Phenotypes.

Lysosomal storage disorders (LSDs) constitute a large group of rare, multisystemic, inherited disorders of metabolism, characterized by defects in lysosomal enzymes, accessory proteins, membrane transporters or trafficking proteins. Pompe disease (PD) is produced by mutations in the acid alpha-glucosidase (GAA) lysosomal enzyme. This enzymatic deficiency leads to the aberrant accumulation of glycogen in the lysosome. The onset of symptoms, including a variety of neurological and multiple-organ pathologies, can range from birth to adulthood, and disease severity can vary between individuals. Although very significant advances related to the development of new treatments, and also to the improvement of newborn screening programs and tools for a more accurate diagnosis and follow-up of patients, have occurred over recent years, there exists an unmet need for further understanding the molecular mechanisms underlying the progression of the disease. Also, the reason why currently available treatments lose effectiveness over time in some patients is not completely understood. In this scenario, characterization of the metabolic phenotype is a valuable approach to gain insights into the global impact of lysosomal dysfunction, and its potential correlation with clinical progression and response to therapies. These approaches represent a discovery tool for investigating disease-induced modifications in the complete metabolic profile, including large numbers of metabolites that are simultaneously analyzed, enabling the identification of novel potential biomarkers associated with these conditions. This review aims to highlight the most relevant findings of recently published omics-based studies with a particular focus on describing the clinical potential of the specific metabolic phenotypes associated to different subgroups of PD patients.

IgG antibody response to pneumococcal-conjugated vaccine (Prevenar®13) in children with immunodeficiency disorders.

Measurement of anti-pneumococcal capsular polysaccharides (anti-PnPs) IgG titers is an important tool in the immunologic assessment of patients with suspected immunodeficiency disorders (ID) to reduce the morbi-mortality and minimize severe infections. Retrospectively, we studied the relationship among anti-PnPs IgG response to 3 doses of Prevenar®13, levels of immune system components, leukocyte populations, and clinical data in children with ID. Serum samples were collected at least 4 weeks post vaccination. Subsequently, multi-serotype enzyme-linked immunosorbent assay (ELISA) was performed. Eighty-seven children (under 12 years) were enrolled. Primary immunodeficiency disorder (PID) was the most common disorder (45) followed by possible immunodeficiency disorder (POID) (19), secondary immunodeficiency disorder (SID) (15), and mixed immunodeficiency disorder (MID) (8). The median age was 3 (1.50-5.33) years, 65% of patients were male. Deficient production of anti-PnPs IgG (titer ≤ 50 mg/L) was detected in 47 patients (54%), especially in the MID group, all of them under immunosuppressive therapy. In PCV13 responders, the mean of leukocyte population levels was higher with statistically significance differences in CD4 + /CD8 + T lymphocytes (p = 0.372, p = 0.014) and CD56 + /CD16 + NK (p = 0.016). Patients with previous bone marrow transplantation were the worst PCV13 responders. Pneumococcal IgG antibody titers (post-vaccination) along with clinical and analytical markers represented.

Microbiome-mediated fructose depletion restricts murine gut colonization by vancomycin-resistant Enterococcus.

Multidrug-resistant organisms (MDRO) are a major threat to public health. MDRO infections, including those caused by vancomycin-resistant Enterococcus (VRE), frequently begin by colonization of the intestinal tract, a crucial step that is impaired by the intestinal microbiota. However, the specific members of the microbiota that suppress MDRO colonization and the mechanisms of such protection are largely unknown. Here, using metagenomics and mouse models that mimic the patients' exposure to antibiotics, we identified commensal bacteria associated with protection against VRE colonization. We further found a consortium of five strains that was sufficient to restrict VRE gut colonization in antibiotic treated mice. Transcriptomics in combination with targeted metabolomics and in vivo assays indicated that the bacterial consortium inhibits VRE growth through nutrient depletion, specifically by reducing the levels of fructose, a carbohydrate that boosts VRE growth in vivo. Finally, in vivo RNA-seq analysis of each strain of the consortium in combination with ex vivo and in vivo assays demonstrated that a single bacterium (Olsenella sp.) could recapitulate the effect of the consortium. Our results indicate that nutrient depletion by specific commensals can reduce VRE intestinal colonization, which represents a novel non-antibiotic based strategy to prevent infections caused by this multidrug-resistant organism.

Lactobacillus supports Clostridiales to restrict gut colonization by multidrug-resistant Enterobacteriaceae.

Infections by multidrug-resistant Enterobacteriaceae (MRE) are life-threatening to patients. The intestinal microbiome protects against MRE colonization, but antibiotics cause collateral damage to commensals and open the way to colonization and subsequent infection. Despite the significance of this problem, the specific commensals and mechanisms that restrict MRE colonization remain largely unknown. Here, by performing a multi-omic prospective study of hospitalized patients combined with mice experiments, we find that Lactobacillus is key, though not sufficient, to restrict MRE gut colonization. Lactobacillus rhamnosus and murinus increase the levels of Clostridiales bacteria, which induces a hostile environment for MRE growth through increased butyrate levels and reduced nutrient sources. This mechanism of colonization resistance, an interaction between Lactobacillus spp. and Clostridiales involving cooperation between microbiota members, is conserved in mice and patients. These results stress the importance of exploiting microbiome interactions for developing effective probiotics that prevent infections in hospitalized patients.

Therapeutic targeting of PD-1/PD-L1 blockade by novel small-molecule inhibitors recruits cytotoxic T cells into solid tumor microenvironment.

BACKGROUND: Inhibiting programmed cell death protein 1 (PD-1) or PD-ligand 1 (PD-L1) has shown exciting clinical outcomes in diverse human cancers. So far, only monoclonal antibodies are approved as PD-1/PD-L1 inhibitors. While significant clinical outcomes are observed on patients who respond to these therapeutics, a large proportion of the patients do not benefit from the currently available immune checkpoint inhibitors, which strongly emphasize the importance of developing new immunotherapeutic agents. METHODS: In this study, we followed a transdisciplinary approach to discover novel small molecules that can modulate PD-1/PD-L1 interaction. To that end, we employed in silico analyses combined with in vitro, ex vivo, and in vivo experimental studies to assess the ability of novel compounds to modulate PD-1/PD-L1 interaction and enhance T-cell function. RESULTS: Accordingly, in this study we report the identification of novel small molecules, which like anti-PD-L1/PD-1 antibodies, can stimulate human adaptive immune responses. Unlike these biological compounds, our newly-identified small molecules enabled an extensive infiltration of T lymphocytes into three-dimensional solid tumor models, and the recruitment of cytotoxic T lymphocytes to the tumor microenvironment in vivo, unveiling a unique potential to transform cancer immunotherapy. CONCLUSIONS: We identified a new promising family of small-molecule candidates that regulate the PD-L1/PD-1 signaling pathway, promoting an extensive infiltration of effector CD8 T cells to the tumor microenvironment.

The bone marrow niche regulates redox and energy balance in MLL::AF9 leukemia stem cells.

Eradicating leukemia requires a deep understanding of the interaction between leukemic cells and their protective microenvironment. The CXCL12/CXCR4 axis has been postulated as a critical pathway dictating leukemia stem cell (LSC) chemoresistance in AML due to its role in controlling cellular egress from the marrow. Nevertheless, the cellular source of CXCL12 in the acute myeloid leukemia (AML) microenvironment and the mechanism by which CXCL12 exerts its protective role in vivo remain unresolved. Here, we show that CXCL12 produced by Prx1+ mesenchymal cells but not by mature osteolineage cells provide the necessary cues for the maintenance of LSCs in the marrow of an MLL::AF9-induced AML model. Prx1+ cells promote survival of LSCs by modulating energy metabolism and the REDOX balance in LSCs. Deletion of Cxcl12 leads to the accumulation of reactive oxygen species and DNA damage in LSCs, impairing their ability to perpetuate leukemia in transplantation experiments, a defect that can be attenuated by antioxidant therapy. Importantly, our data suggest that this phenomenon appears to be conserved in human patients. Hence, we have identified Prx1+ mesenchymal cells as an integral part of the complex niche-AML metabolic intertwining, pointing towards CXCL12/CXCR4 as a target to eradicate parenchymal LSCs in AML.

Metabolic Phenotyping in Prostate Cancer Using Multi-Omics Approaches.

Prostate cancer (PCa), one of the most frequently diagnosed cancers among men worldwide, is characterized by a diverse biological heterogeneity. It is well known that PCa cells rewire their cellular metabolism to meet the higher demands required for survival, proliferation, and invasion. In this context, a deeper understanding of metabolic reprogramming, an emerging hallmark of cancer, could provide novel opportunities for cancer diagnosis, prognosis, and treatment. In this setting, multi-omics data integration approaches, including genomics, epigenomics, transcriptomics, proteomics, lipidomics, and metabolomics, could offer unprecedented opportunities for uncovering the molecular changes underlying metabolic rewiring in complex diseases, such as PCa. Recent studies, focused on the integrated analysis of multi-omics data derived from PCa patients, have in fact revealed new insights into specific metabolic reprogramming events and vulnerabilities that have the potential to better guide therapy and improve outcomes for patients. This review aims to provide an up-to-date summary of multi-omics studies focused on the characterization of the metabolomic phenotype of PCa, as well as an in-depth analysis of the correlation between changes identified in the multi-omics studies and the metabolic profile of PCa tumors.

Pharmacometabolomics by NMR in Oncology: A Systematic Review.

Pharmacometabolomics (PMx) studies aim to predict individual differences in treatment response and in the development of adverse effects associated with specific drug treatments. Overall, these studies inform us about how individuals will respond to a drug treatment based on their metabolic profiles obtained before, during, or after the therapeutic intervention. In the era of precision medicine, metabolic profiles hold great potential to guide patient selection and stratification in clinical trials, with a focus on improving drug efficacy and safety. Metabolomics is closely related to the phenotype as alterations in metabolism reflect changes in the preceding cascade of genomics, transcriptomics, and proteomics changes, thus providing a significant advance over other omics approaches. Nuclear Magnetic Resonance (NMR) is one of the most widely used analytical platforms in metabolomics studies. In fact, since the introduction of PMx studies in 2006, the number of NMR-based PMx studies has been continuously growing and has provided novel insights into the specific metabolic changes associated with different mechanisms of action and/or toxic effects. This review presents an up-to-date summary of NMR-based PMx studies performed over the last 10 years. Our main objective is to discuss the experimental approaches used for the characterization of the metabolic changes associated with specific therapeutic interventions, the most relevant results obtained so far, and some of the remaining challenges in this area.

Multi-Omic Approaches to Breast Cancer Metabolic Phenotyping: Applications in Diagnosis, Prognosis, and the Development of Novel Treatments.

Breast cancer (BC) is characterized by high disease heterogeneity and represents the most frequently diagnosed cancer among women worldwide. Complex and subtype-specific gene expression alterations participate in disease development and progression, with BC cells known to rewire their cellular metabolism to survive, proliferate, and invade. Hence, as an emerging cancer hallmark, metabolic reprogramming holds great promise for cancer diagnosis, prognosis, and treatment. Multi-omics approaches (the combined analysis of various types of omics data) offer opportunities to advance our understanding of the molecular changes underlying metabolic rewiring in complex diseases such as BC. Recent studies focusing on the combined analysis of genomics, epigenomics, transcriptomics, proteomics, and/or metabolomics in different BC subtypes have provided novel insights into the specificities of metabolic rewiring and the vulnerabilities that may guide therapeutic development and improve patient outcomes. This review summarizes the findings of multi-omics studies focused on the characterization of the specific metabolic phenotypes of BC and discusses how they may improve clinical BC diagnosis, subtyping, and treatment.

Design and Synthesis of Water-Soluble and Potent MMP-13 Inhibitors with Activity in Human Osteosarcoma Cells.

Osteoarthritis is a degenerative disease, often resulting in chronic joint pain and commonly affecting elderly people. Current treatments with anti-inflammatory drugs are palliative, making the discovery of new treatments necessary. The inhibition of matrix metalloproteinase MMP-13 is a validated strategy to prevent the progression of this common joint disorder. We recently described polybrominated benzotriazole derivatives with nanomolar inhibitory activity and a promising selectivity profile against this collagenase. In this work, we have extended the study in order to explore the influence of bromine atoms and the nature of the S1' heterocyclic interacting moiety on the solubility/selectivity balance of this type of compound. Drug target interactions have been assessed through a combination of molecular modeling studies and NMR experiments. Compound 9a has been identified as a water-soluble and highly potent inhibitor with activity in MG-63 human osteosarcoma cells.

Characterization of anaphylaxis reveals different metabolic changes depending on severity and triggers.

BACKGROUND: Despite the increasing incidence of anaphylaxis, its underlying molecular mechanisms and biomarkers for appropriate diagnosis remain undetermined. The rapid onset and potentially fatal outcome in the absence of managed treatment prevent its study. Up today, there are still no known biomarkers that allow an unequivocal diagnosis. Therefore, the aim of this study was to explore metabolic changes in patients suffering anaphylactic reactions depending on the trigger (food and/or drug) and severity (moderate and severe) in a real-life set-up. METHODS: Eighteen episodes of anaphylaxis, one per patient, were analysed. Sera were collected during the acute phase (T1), the recovery phase (T2) and around 2-3 months after the anaphylactic reaction (T0: basal state). Reactions were classified following an exhaustive allergological evaluation for severity and trigger. Sera samples were analysed using untargeted metabolomics combining liquid chromatography coupled to mass spectrometry (LC-MS) and proton nuclear magnetic resonance spectroscopy (1 H-NMR). RESULTS: 'Food T1 vs T2' and 'moderate T1 vs T2' anaphylaxis comparisons showed clear metabolic patterns during the onset of an anaphylactic reaction, which differed from those induced by drugs, food + drug or severe anaphylaxis. Moreover, the model of food anaphylaxis was able to distinguish the well-characterized IgE (antibiotics) from non-IgE-mediated anaphylaxis (nonsteroidal anti-inflammatory drugs), suggesting a differential metabolic pathway associated with the mechanism of action. Metabolic differences between 'moderate vs severe' at the acute phase T1 and at basal state T0 were studied. Among the altered metabolites, glucose, lipids, cortisol, betaine and oleamide were observed altered. CONCLUSIONS: The results of this exploratory study provide the first evidence that different anaphylactic triggers or severity induce differential metabolic changes along time or at specific time-point, respectively. Besides, the basal status T0 might identify high-risk patients, thus opening new ways to understand, diagnose and treat anaphylaxis.

A surface plasmon resonance based approach for measuring response to pneumococcal vaccine.

Incidence of pneumococcal disease has increased worldwide in recent years. Response to pneumococcal vaccine is usually measured using the multiserotype enzyme-linked immunosorbent assay (ELISA) pneumococcal test. However, this approach presents several limitations. Therefore, the introduction of new and more robust analytical approaches able to provide information on the efficacy of the pneumococcal vaccine would be very beneficial for the clinical management of patients. Surface plasmon resonance (SPR) has been shown to offer a valuable understanding of vaccines' properties over the last years. The aim of this study is to evaluate the reliability of SPR for the anti-pneumococcal capsular polysaccharides (anti-PnPs) IgGs quantification in vaccinated. Fast protein liquid chromatography (FPLC) was used for the isolation of total IgGs from serum samples of vaccinated patients. Binding-SPR assays were performed to study the interaction between anti-PnPs IgGs and PCV13. A robust correlation was found between serum levels of anti-PnPs IgGs, measured by ELISA, and the SPR signal. Moreover, it was possible to correctly classify patients into "non-responder", "responder" and "high-responder" groups according to their specific SPR PCV13 response profiles. SPR technology provides a valuable tool for reliably characterize the interaction between anti-PnPs IgGs and PCV13 in a very short experimental time.

Polycythemia Vera and Essential Thrombocythemia Patients Exhibit Unique Serum Metabolic Profiles Compared to Healthy Individuals and Secondary Thrombocytosis Patients.

Most common myeloproliferative neoplasms (MPNs) include polycythemia vera (PV) and essential thrombocythemia (ET). Accurate diagnosis of these disorders remains a clinical challenge due to the lack of specific clinical or molecular features in some patients enabling their discrimination. Metabolomics has been shown to be a powerful tool for the discrimination between different hematological diseases through the analysis of patients' serum metabolic profiles. In this pilot study, the potential of NMR-based metabolomics to characterize the serum metabolic profile of MPNs patients (PV, ET), as well as its comparison with the metabolic profile of healthy controls (HC) and secondary thrombocytosis (ST) patients, was assessed. The metabolic profile of PV and ET patients, compared with HC, exhibited higher levels of lysine and decreased levels of acetoacetic acid, glutamate, polyunsaturated fatty acids (PUFAs), scyllo-inositol and 3-hydroxyisobutyrate. Furthermore, ET patients, compared with HC and ST patients, were characterized by decreased levels of formate, N-acetyl signals from glycoproteins (NAC) and phenylalanine, while the serum profile of PV patients, compared with HC, showed increased concentrations of lactate, isoleucine, creatine and glucose, as well as lower levels of choline-containing metabolites. The overall analysis revealed significant metabolic alterations mainly associated with energy metabolism, the TCA cycle, along with amino acid and lipid metabolism. These results underscore the potential of metabolomics for identifying metabolic alterations in the serum of MPNs patients that could contribute to improving the clinical management of these diseases.

The Pretreatment Gut Microbiome Is Associated With Lack of Response to Methotrexate in New-Onset Rheumatoid Arthritis.

OBJECTIVE: Although oral methotrexate (MTX) remains the anchor drug for rheumatoid arthritis (RA), up to 50% of patients do not achieve a clinically adequate outcome. In addition, there is a lack of prognostic tools for treatment response prior to drug initiation. This study was undertaken to investigate whether interindividual differences in the human gut microbiome can aid in the prediction of MTX efficacy in new-onset RA. METHODS: We performed 16S ribosomal RNA gene and shotgun metagenomic sequencing on the baseline gut microbiomes of drug-naive patients with new-onset RA (n = 26). Results were validated in an additional independent cohort (n = 21). To gain insight into potential microbial mechanisms, we conducted ex vivo experiments coupled with metabolomics analysis to evaluate the association between microbiome-driven MTX depletion and clinical response. RESULTS: Our analysis revealed significant associations of the abundance of gut bacterial taxa and their genes with future clinical response (q < 0.05), including orthologs related to purine and MTX metabolism. Machine learning techniques were applied to the metagenomic data, resulting in a microbiome-based model that predicted lack of response to MTX in an independent group of patients. Finally, MTX levels remaining after ex vivo incubation with distal gut samples from pretreatment RA patients significantly correlated with the magnitude of future clinical response, suggesting a possible direct effect of the gut microbiome on MTX metabolism and treatment outcomes. CONCLUSION: Taken together, these findings are the first step toward predicting lack of response to oral MTX in patients with new-onset RA and support the value of the gut microbiome as a possible prognostic tool and as a potential target in RA therapeutics.

Targeted Metabolomics Analyses Reveal Specific Metabolic Alterations in High-Grade Prostate Cancer Patients.

Prostate cancer (PCa) is a hormone-dependent tumor characterized by an extremely heterogeneous prognosis. Despite recent advances in partially uncovering some of the biological processes involved in its progression, there is still an urgent need for identifying more accurate and specific prognostic procedures to differentiate between disease stages. In this context, targeted approaches, focused on mapping dysregulated metabolic pathways, could play a critical role in identifying the mechanisms driving tumorigenesis and metastasis. In this study, a targeted analysis of the nuclear magnetic resonance-based metabolomic profile of PCa patients with different tumor grades, guided by transcriptomics profiles associated with their stages, was performed. Serum and urine samples were collected from 73 PCa patients. Samples were classified according to their Gleason score (GS) into low-GS (GS < 7) and high-GS PCa (GS ≥ 7) groups. A total of 36 metabolic pathways were found to be dysregulated in the comparison between different PCa grades. Particularly, the levels of glucose, glycine and 1-methlynicotinamide, metabolites involved in energy metabolism and nucleotide synthesis were significantly altered between both groups of patients. These results underscore the potential of targeted metabolomic profiling to characterize relevant metabolic changes involved in the progression of this neoplastic process.

Pilot Multi-Omic Analysis of Human Bile from Benign and Malignant Biliary Strictures: A Machine-Learning Approach.

Cholangiocarcinoma (CCA) and pancreatic adenocarcinoma (PDAC) may lead to the development of extrahepatic obstructive cholestasis. However, biliary stenoses can also be caused by benign conditions, and the identification of their etiology still remains a clinical challenge. We performed metabolomic and proteomic analyses of bile from patients with benign (n = 36) and malignant conditions, CCA (n = 36) or PDAC (n = 57), undergoing endoscopic retrograde cholangiopancreatography with the aim of characterizing bile composition in biliopancreatic disease and identifying biomarkers for the differential diagnosis of biliary strictures. Comprehensive analyses of lipids, bile acids and small molecules were carried out using mass spectrometry (MS) and nuclear magnetic resonance spectroscopy (1H-NMR) in all patients. MS analysis of bile proteome was performed in five patients per group. We implemented artificial intelligence tools for the selection of biomarkers and algorithms with predictive capacity. Our machine-learning pipeline included the generation of synthetic data with properties of real data, the selection of potential biomarkers (metabolites or proteins) and their analysis with neural networks (NN). Selected biomarkers were then validated with real data. We identified panels of lipids (n = 10) and proteins (n = 5) that when analyzed with NN algorithms discriminated between patients with and without cancer with an unprecedented accuracy.

Vaginal metabolome: towards a minimally invasive diagnosis of microbial invasion of the amniotic cavity in women with preterm labor.

Microbial invasion of the amniotic cavity (MIAC) is only identified by amniocentesis, an invasive procedure that limits its clinical translation. Here, we aimed to evaluate whether the vaginal metabolome discriminates the presence/absence of MIAC in women with preterm labor (PTL) and intact membranes. We conducted a case-control study in women with symptoms of PTL below 34 weeks who underwent amniocentesis to discard MIAC. MIAC was defined as amniotic fluid positive for microorganisms identified by specific culture media. The cohort included 16 women with MIAC and 16 control (no MIAC). Both groups were matched for age and gestational age at admission. Vaginal fluid samples were collected shortly after amniocentesis. Metabolic profiles were analyzed by nuclear magnetic resonance (NMR) spectroscopy and compared using multivariate and univariate statistical analyses to identify significant differences between the two groups. The vaginal metabolomics profile of MIAC showed higher concentrations of hypoxanthine, proline, choline and acetylcholine and decreased concentrations of phenylalanine, glutamine, isoleucine, leucine and glycerophosphocholine. In conclusion, metabolic changes in the NMR-based vaginal metabolic profile are able to discriminate the presence/absence of MIAC in women with PTL and intact membranes. These metabolic changes might be indicative of enhanced glycolysis triggered by hypoxia conditions as a consequence of bacterial infection, thus explaining the utilization of alternative energy sources in an attempt to replenish glucose.

Metabolomics Contributions to the Discovery of Prostate Cancer Biomarkers.

Prostate cancer (PCa) is one of the most frequently diagnosed cancers and a leading cause of death among men worldwide. Despite extensive efforts in biomarker discovery during the last years, currently used clinical biomarkers are still lacking enough specificity and sensitivity for PCa early detection, patient prognosis, and monitoring. Therefore, more precise biomarkers are required to improve the clinical management of PCa patients. In this context, metabolomics has shown to be a promising and powerful tool to identify novel PCa biomarkers in biofluids. Thus, changes in polyamines, tricarboxylic acid (TCA) cycle, amino acids, and fatty acids metabolism have been reported in different studies analyzing PCa patients' biofluids. The review provides an up-to-date summary of the main metabolic alterations that have been described in biofluid-based studies of PCa patients, as well as a discussion regarding their potential to improve clinical PCa diagnosis and prognosis. Furthermore, a summary of the most significant findings reported in these studies and the connections and interactions between the different metabolic changes described has also been included, aiming to better describe the specific metabolic signature associated to PCa.

Development of inhibitors of receptor protein tyrosine phosphatase ß/ζ (PTPRZ1) as candidates for CNS disorders.

A new series of blood-brain barrier permeable molecules designed to mimic the activity of Pleiotrophin in the CNS has been designed and synthesized. These compounds exert their action by interacting with the intracellular domain PD1 of the Protein Tyrosine-Phosphatase Receptor Z1 (PTPRZ1), and inhibiting its tyrosine phosphatase activity. The most potent compounds 10a and 12b (IC50 = 0,1 µM) significantly increase the phosphorylation of key tyrosine residues of PTPRZ1 substrates involved in neuronal survival and differentiation, and display protective effects against amphetamine-induced toxicity. Docking and molecular dynamics experiments have been used to analyze the binding mode and to explain the observed selectivity against PTP1B. An In vivo experiment has demonstrated that 10a can cross the BBB, thus promoting the possibility of moving forward these candidates for the development of drugs for the treatment of CNS disorders, such as drug addiction and neurodegenerative diseases.

Non-invasive urinary metabolomic profiling discriminates prostate cancer from benign prostatic hyperplasia.

INTRODUCTION: Prostate cancer (PCa) is one of the most common malignancies in men worldwide. Serum prostate specific antigen (PSA) level has been extensively used as a biomarker to detect PCa. However, PSA is not cancer-specific and various non-malignant conditions, including benign prostatic hyperplasia (BPH), can cause a rise in PSA blood levels, thus leading to many false positive results. OBJECTIVES: In this study, we evaluated the potential of urinary metabolomic profiling for discriminating PCa from BPH. METHODS: Urine samples from 64 PCa patients and 51 individuals diagnosed with BPH were analysed using 1H nuclear magnetic resonance (1H-NMR). Comparative analysis of urinary metabolomic profiles was carried out using multivariate and univariate statistical approaches. RESULTS: The urine metabolomic profile of PCa patients is characterised by increased concentrations of branched-chain amino acids (BCAA), glutamate and pseudouridine, and decreased concentrations of glycine, dimethylglycine, fumarate and 4-imidazole-acetate compared with individuals diagnosed with BPH. CONCLUSION: PCa patients have a specific urinary metabolomic profile. The results of our study underscore the clinical potential of metabolomic profiling to uncover metabolic changes that could be useful to discriminate PCa from BPH in a clinical context.