Plasma metabolomics provides new insights into the relationship between metabolites and outcomes and left ventricular remodeling of coronary artery disease

BACKGROUND

Coronary artery disease (CAD) is a metabolically perturbed pathological condition. However, the knowledge of metabolic signatures on outcomes of CAD and their potential causal effects and impacts on left ventricular remodeling remains limited. We aim to assess the contribution of plasma metabolites to the risk of death and major adverse cardiovascular events (MACE) as well as left ventricular remodeling.

RESULTS

In a prospective study with 1606 Chinese patients with CAD, we have identified and validated several independent metabolic signatures through widely-targeted metabolomics. The predictive model respectively integrating four metabolic signatures (dulcitol, β-pseudouridine, 3,3',5-Triiodo-L-thyronine, and kynurenine) for death (AUC of 83.7% vs. 76.6%, positive IDI of 0.096) and metabolic signatures (kynurenine, lysoPC 20:2, 5-methyluridine, and L-tryptophan) for MACE (AUC of 67.4% vs. 59.8%, IDI of 0.068) yielded better predictive value than trimethylamine N-oxide plus clinical model, which were successfully applied to predict patients with high risks of death (P = 0.0014) and MACE (P = 0.0008) in the multicenter validation cohort. Mendelian randomisation analysis showed that 11 genetically inferred metabolic signatures were significantly associated with risks of death or MACE, such as 4-acetamidobutyric acid, phenylacetyl-L-glutamine, tryptophan metabolites (kynurenine, kynurenic acid), and modified nucleosides (β-pseudouridine, 2-(dimethylamino) guanosine). Mediation analyses show that the association of these metabolites with the outcomes could be partly explained by their roles in promoting left ventricular dysfunction.

CONCLUSIONS

This study provided new insights into the relationship between plasma metabolites and clinical outcomes and its intermediate pathological process left ventricular dysfunction in CAD. The predictive model integrating metabolites can help to improve the risk stratification for death and MACE in CAD. The metabolic signatures appear to increase death or MACE risks partly by promoting adverse left ventricular dysfunction, supporting potential therapeutic targets of CAD for further investigation.

Sex differences in the human metabolome

BACKGROUND

The sexual dimorphism represents one of the triggers of the metabolic disparities between the organisms, advising about wild implications in research or diagnostics contexts. Despite the mounting recognition of the importance of sex consideration in the biomedical fields, the identification of male- and female-specific metabolic signatures has not been achieved.

MAIN BODY

This review pointed the focus on the metabolic differences related to the sex, evidenced by metabolomics studies performed on healthy populations, with the leading aim of understanding how the sex influences the baseline metabolome. The main shared signatures and the apparent dissimilarities between males and females were extracted and highlighted from the metabolome of the most commonly analyzed biological fluids, such as serum, plasma, and urine. Furthermore, the influence of age and the significant interactions between sex and age have been taken into account.

CONCLUSIONS

The recognition of sex patterns in human metabolomics has been defined in diverse biofluids. The detection of sex- and age-related differences in the metabolome of healthy individuals are helpful for translational applications from the bench to the bedside to set targeted diagnostic and prevention approaches in the context of personalized medicine.

[Immunohistochemical analysis of a hypoxia-associated signature in melanomas with positive and negative sentinel lymph nodes : Hypoxia-associated signature of primary cutaneous melanomas]

Metabolic reprogramming mediated by hypoxia-inducible factors and its downstream targets plays a crucial role in many human malignancies. Excessive proliferation of tumor cells under hypoxic conditions leads to metabolic reprogramming and altered gene expression enabling tumors to adapt to their hypoxic environment. Here we analyzed the metabolic signatures of primary cutaneous melanomas with positive and negative sentinel node status in order to evaluate potential differences in their metabolic signature. We found a positive correlation of the expression of glucose transporter 1 (GLUT-1) with tumor thickness and ulceration in all melanomas with subgroup analyses as well as in the subgroup with a negative sentinel node. Furthermore, the expression of vascular endothelial growth factor (VEGF) was positively correlated with the presence of ulceration in melanomas with positive sentinel node.

Multiplatform metabolomics for an integrative exploration of metabolic syndrome in older men

BACKGROUND

Metabolic syndrome (MetS), a cluster of factors associated with risks of developing cardiovascular diseases, is a public health concern because of its growing prevalence. Considering the combination of concomitant components, their development and severity, MetS phenotypes are largely heterogeneous, inducing disparity in diagnosis.

METHODS

A case/control study was designed within the NuAge longitudinal cohort on aging. From a 3-year follow-up of 123 stable individuals, we present a deep phenotyping approach based on a multiplatform metabolomics and lipidomics untargeted strategy to better characterize metabolic perturbations in MetS and define a comprehensive MetS signature stable over time in older men.

FINDINGS

We characterize significant changes associated with MetS, involving modulations of 476 metabolites and lipids, and representing 16% of the detected serum metabolome/lipidome. These results revealed a systemic alteration of metabolism, involving various metabolic pathways (urea cycle, amino-acid, sphingo- and glycerophospholipid, and sugar metabolisms…) not only intrinsically interrelated, but also reflecting environmental factors (nutrition, microbiota, physical activity…).

INTERPRETATION

These findings allowed identifying a comprehensive MetS signature, reduced to 26 metabolites for future translation into clinical applications for better diagnosing MetS.

FUNDING

The NuAge Study was supported by a research grant from the Canadian Institutes of Health Research (CIHR; MOP-62842). The actual NuAge Database and Biobank, containing data and biologic samples of 1,753 NuAge participants (from the initial 1,793 participants), are supported by the Fonds de recherche du Québec (FRQ; 2020-VICO-279753), the Quebec Network for Research on Aging, a thematic network funded by the Fonds de Recherche du Québec - Santé (FRQS) and by the Merck-Frost Chair funded by La Fondation de l'Université de Sherbrooke. All metabolomics and lipidomics analyses were funded and performed within the metaboHUB French infrastructure (ANR-INBS-0010). All authors had full access to the full data in the study and accept responsibility to submit for publication.

Metabolomic profiling of pancreatic adenocarcinoma reveals key features driving clinical outcome and drug resistance

BACKGROUND

Although significant advances have been made recently to characterize the biology of pancreatic ductal adenocarcinoma (PDAC), more efforts are needed to improve our understanding and to face challenges related to the aggressiveness, high mortality rate and chemoresistance of this disease.

METHODS

In this study, we perform the metabolomics profiling of 77 PDAC patient-derived tumor xenografts (PDTX) to investigate the relationship of metabolic profiles with overall survival (OS) in PDAC patients, tumor phenotypes and resistance to five anticancer drugs (gemcitabine, oxaliplatin, docetaxel, SN-38 and 5-Fluorouracil).

FINDINGS

We identified a metabolic signature that was able to predict the clinical outcome of PDAC patients (p < 0.001, HR=2.68 [95% CI: 1.5-4.9]). The correlation analysis showed that this metabolomic signature was significantly correlated with the PDAC molecular gradient (PAMG) (R = 0.44 and p < 0.001) indicating significant association to the transcriptomic phenotypes of tumors. Resistance score established, based on growth rate inhibition metrics using 35 PDTX-derived primary cells, allowed to identify several metabolites related to drug resistance which was globally accompanied by accumulation of several diacy-phospholipids and decrease in lysophospholipids. Interestingly, targeting glycerophospholipid synthesis improved sensitivity to the three tested cytotoxic drugs indicating that interfering with metabolism could be a promising therapeutic strategy to overcome the challenging resistance of PDAC.

INTERPRETATION

In conclusion, this study shows that the metabolomic profile of pancreatic PDTX models is strongly associated to clinical outcome, transcriptomic phenotypes and drug resistance. We also showed that targeting the lipidomic profile could be used in combinatory therapies against chemoresistance in PDAC.

Sulfasalazine modifies metabolic profiles and enhances cisplatin chemosensitivity on cholangiocarcinoma cells in in vitro and in vivo models

Background

Sulfasalazine (SSZ) is widely known as an xCT inhibitor suppressing CD44v9-expressed cancer stem-like cells (CSCs) being related to redox regulation. Cholangiocarcinoma (CCA) has a high recurrence rate and no effective chemotherapy. A recent report revealed high levels of CD44v9-positive cells in CCA patients. Therefore, a combination of drugs could prove a suitable strategy for CCA treatment via individual metabolic profiling.

Methods

We examined the effect of xCT-targeted CD44v9-CSCs using sulfasalazine combined with cisplatin (CIS) or gemcitabine in CCA in vitro and in vivo models and did NMR-based metabolomics analysis of xenograft mice tumor tissues.

Results

Our findings suggest that combined SSZ and CIS leads to a higher inhibition of cell proliferation and induction of cell death than CIS alone in both in vitro and in vivo models. Xenograft mice showed that the CD44v9-CSC marker and CK-19-CCA proliferative marker were reduced in the combination treatment. Interestingly, different metabolic signatures and significant metabolites were observed in the drug-treated group compared with the control group that revealed the cancer suppression mechanisms.

Conclusions

SSZ could improve CCA therapy by sensitization to CIS through killing CD44v9-positive cells and modifying the metabolic pathways, in particular tryptophan degradation (i.e., kynurenine pathway, serotonin pathway) and nucleic acid metabolism.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40170-021-00249-6.

Identification of a six-gene metabolic signature predicting overall survival for patients with lung adenocarcinoma

Background

Lung cancer is the leading cause of cancer-related deaths worldwide. Lung adenocarcinoma (LUAD) is one of the main subtypes of lung cancer. Hundreds of metabolic genes are altered consistently in LUAD; however, their prognostic role remains to be explored. This study aimed to establish a molecular signature that can predict the prognosis in patients with LUAD based on metabolic gene expression.

Methods

The transcriptome expression profiles and corresponding clinical information of LUAD were obtained from The Cancer Genome Atlas and Gene Expression Omnibus databases. The differentially expressed genes (DEGs) between LUAD and paired non-tumor samples were identified by the Wilcoxon rank sum test. Univariate Cox regression analysis and the lasso Cox regression model were used to construct the best-prognosis molecular signature. A nomogram was established comprising the prognostic model for predicting overall survival. To validate the prognostic ability of the molecular signature and the nomogram, the Kaplan-Meier survival analysis, Cox proportional hazards model, and receiver operating characteristic analysis were used.

Results

The six-gene molecular signature (PFKP, PKM, TPI1, LDHA, PTGES, and TYMS) from the DEGs was constructed to predict the prognosis. The molecular signature demonstrated a robust independent prognostic ability in the training and validation sets. The nomogram including the prognostic model had a greater predictive accuracy than previous systems. Furthermore, a gene set enrichment analysis revealed several significantly enriched metabolic pathways, which suggests a correlation of the molecular signature with metabolic systems and may help explain the underlying mechanisms.

Conclusions

Our study identified a novel six-gene metabolic signature for LUAD prognosis prediction. The molecular signature could reflect the dysregulated metabolic microenvironment, provide potential biomarkers for predicting prognosis, and indicate potential novel metabolic molecular-targeted therapies.

Disruption of redox homeostasis for combinatorial drug efficacy in K-Ras tumors as revealed by metabolic connectivity profiling

Abstract

Background

Rewiring of metabolism induced by oncogenic K-Ras in cancer cells involves both glucose and glutamine utilization sustaining enhanced, unrestricted growth. The development of effective anti-cancer treatments targeting metabolism may be facilitated by the identification and rational combinatorial targeting of metabolic pathways.

Methods

We performed mass spectrometric metabolomics analysis in vitro and in vivo experiments to evaluate the efficacy of drugs and identify metabolic connectivity.

Results

We show that K-Ras-mutant lung and colon cancer cells exhibit a distinct metabolic rewiring, the latter being more dependent on respiration. Combined treatment with the glutaminase inhibitor CB-839 and the PI3K/aldolase inhibitor NVP-BKM120 more consistently reduces cell growth of tumor xenografts. Maximal growth inhibition correlates with the disruption of redox homeostasis, involving loss of reduced glutathione regeneration, redox cofactors, and a decreased connectivity among metabolites primarily involved in nucleic acid metabolism.

Conclusions

Our findings open the way to develop metabolic connectivity profiling as a tool for a selective strategy of combined drug repositioning in precision oncology.

Comprehensive metabolic flux analysis to explain skeletal muscle weakness in COPD

BACKGROUND & AIMS

Metabolic characterization of a well-defined group of patients could be a powerful tool in revealing metabolic signatures to explain limb muscle weakness in chronic diseases. Studies are currently limited in Chronic Obstructive Pulmonary Disease (COPD) to the identification of differential amino acid concentrations but lack comprehensive analysis of the flux through relevant muscle function related metabolic pathways.

METHODS

In 23 stable patients with moderate to very severe COPD and 19 healthy controls, a comprehensive metabolic flux analysis was conducted by administering an intravenous pulse and primed constant infusion of multiple stable tracers of amino acids known to play a role in muscle health. Blood samples were obtained to calculate production (WBP) and interconversion rates, and plasma concentrations of these amino acids. Lower and upper limb muscle strength, muscle mass, lung function, physical activity level, and disease history and characteristics were assessed.

RESULTS

The COPD group was characterized by lower and upper limb muscle weakness (P < 0.01) despite preserved muscle mass. Higher values were found in COPD for plasma glutamine, WBP of leucine (P < 0.001), 3-methylhistidine (P < 0.01) (marker of enhanced myofibrillar protein breakdown), citrulline (P < 0.05), and arginine to citrulline conversion (P < 0.05) (reflecting enhanced nitric oxide synthesis). Plasma concentration of β-hydroxy β-methylbutyrate (HMB with anticatabolic, anabolic and contractile properties), WBP of glycine (precursor of creatine and glutathione), and transcutaneous O₂ saturation explained up to 79% and 65% of the variation in strength of the lower and upper limb muscles, respectively, in COPD.

CONCLUSIONS

Comprehensive metabolic flux analysis revealed a homogenous metabolic signature in stable patients with COPD and a specific metabolic profile in those with skeletal muscle weakness.

CLINICAL TRIAL REGISTRY

ClinicalTrials.gov; No. NCT01787682; URL: www.clinicaltrials.gov.

Metabolic signatures of Besnoitia besnoiti-infected endothelial host cells and blockage of key metabolic pathways indicate high glycolytic and glutaminolytic needs of the parasite

Besnoitia besnoiti is an obligate intracellular and emerging coccidian parasite of cattle with a significant economic impact on cattle industry. During acute infection, fast-proliferating tachyzoites are continuously formed mainly in endothelial host cells of infected animals. Given that offspring formation is a highly energy and cell building block demanding process, the parasite needs to exploit host cellular metabolism to meet its metabolic demands. Here, we analyzed the metabolic signatures of B. besnoiti-infected endothelial host cells and aimed to influence parasite proliferation by inhibitors of specific metabolic pathways. The following inhibitors were tested: fluoro 2-deoxy-D-glucose and 2-deoxy-D-glucose (FDG, DG; inhibitors of glycolysis), 6-diazo-5-oxo-L-norleucin (DON; inhibitor of glutaminolysis), dichloroacetate (DCA; inhibitor of pyruvate dehydrogenase kinase which favorites channeling of glucose carbons into the TCA cycle) and adenosine-monophosphate (AMP; inhibitor of ribose 5-P synthesis). Overall, B. besnoiti infections of bovine endothelial cells induced a significant and infection rate-dependent increase of glucose, lactate, glutamine, glutamate, pyruvate, alanine, and serine conversion rates which together indicate a parasite-triggered up-regulation of glycolysis and glutaminolysis. Thus, addition of DON, FDG, and DG into the cultivation medium of B. besnoiti infected endothelial cells led to a dose-dependent inhibition of parasite replication (4 μM DON, 99.5 % inhibition; 2 mM FDG, 99.1 % inhibition; 2 mM DG, 93 % inhibition; and 8 mM DCA, 71.9 % inhibition). In contrast, AMP had no significant effects on total tachyzoite production up to a concentration of 20 mM. Together, these data may open new strategies for the development of therapeutics for B. besnoiti infections.