Determination of low-molecular-weight organic acids in non-small cell lung cancer with a new liquid chromatography–tandem mass spectrometry method

Determination of succinic acid and lactic acid in pigs' serum, intestinal contents, and meat by ultrahigh-performance liquid chromatography-tandem mass spectrometry

RATIONALE

Succinic acid and lactic acid have been associated with diarrhea in weaned piglets. The level of succinic acid and lactic acid in serum, meat, and intestinal contents is important to elucidate the mechanism of diarrhea in weaned piglets.

METHODS

A facile method was developed for the quantification of succinic acid and lactic acid in pigs' serum, intestinal contents, and meat using ultrahigh-performance liquid chromatography-tandem mass spectrometry (UHPLC/MS/MS). The serum samples underwent protein precipitation with methanol. The meat and intestinal contents were freeze-dried and homogenized using a tissue grinding apparatus. Methanol-water mixture (80:20, v/v) was used for homogenizing the meat, while water was used for homogenizing the intestinal contents. An additional step of protein precipitation with acetonitrile was required for the intestinal contents. The resulting solution was diluted with water before being analyzed by UHPLC/MS/MS. Separation of succinic acid and lactic acid could be achieved within 3 min using a Kinetic XB-C18 column.

RESULTS

The coefficients of variation for peak areas of succinic acid and lactic acid were less than 5.0%. The established method demonstrated good linearity as indicated by correlation coefficients exceeding 0.996. Additionally, satisfactory recoveries ranging from 88.58% to 108.8% were obtained. The detection limits (RS/N = 3) for succinic acid and lactic acid were determined to be 0.75 ng/mL and 0.02 μg/mL, respectively.

CONCLUSION

This method exhibited high sensitivity, simplicity in operation, and small sample weight, making it suitable for quantitative determination of succinic acid and lactic acid in pigs' serum, intestinal contents, and meat. The method developed will provide valuable technical support in studying the metabolic mechanisms of succinic acid and lactic acid in pigs.

Metabolomics-based search for lung cancer markers among patients with different smoking status

Tobacco smoking is the main etiological factor of lung cancer (LC), which can also cause metabolome disruption. This study aimed to investigate whether the observed metabolic shift in LC patients was also associated with their smoking status. Untargeted metabolomics profiling was applied for the initial screening of changes in serum metabolic profile between LC and chronic obstructive pulmonary disease (COPD) patients, selected as a non-cancer group. Differences in metabolite profiles between current and former smokers were also tested. Then, targeted metabolomics methods were applied to verify and validate the proposed LC biomarkers. For untargeted metabolomics, a single extraction-dual separation workflow was applied. The samples were analyzed using a liquid chromatograph-high resolution quadrupole time-of-flight mass spectrometer. Next, the selected metabolites were quantified using liquid chromatography-triple-quadrupole mass spectrometry. The acquired data confirmed that patients' stratification based on smoking status impacted the discriminating ability of the identified LC marker candidates. Analyzing a validation set of samples enabled us to determine if the putative LC markers were truly robust. It demonstrated significant differences in the case of four metabolites: allantoin, glutamic acid, succinic acid, and sphingosine-1-phosphate. Our research showed that studying the influence of strong environmental factors, such as tobacco smoking, should be considered in cancer marker research since it reduces the risk of false positives and improves understanding of the metabolite shifts in cancer patients.

Recent Analytical Advances for Decoding Metabolic Reprogramming in Lung Cancer

Lung cancer is the leading cause of cancer-related death worldwide. Metabolic reprogramming is a fundamental trait associated with lung cancer development that fuels tumor proliferation and survival. Monitoring such metabolic pathways and their intermediate metabolites can provide new avenues concerning treatment strategies, and the identification of prognostic biomarkers that could be utilized to monitor drug responses in clinical practice. In this review, recent trends in the analytical techniques used for metabolome mapping of lung cancer are capitalized. These techniques include nuclear magnetic resonance (NMR), gas chromatography-mass spectrometry (GC-MS), liquid chromatography-mass spectrometry (LC-MS), and imaging mass spectrometry (MSI). The advantages and limitations of the application of each technique for monitoring the metabolite class or type are also highlighted. Moreover, their potential applications in the analysis of many biological samples will be evaluated.

2 Hydroxybutyric Acid-Producing Bacteria in Gut Microbiome and Fusobacterium nucleatum Regulates 2 Hydroxybutyric Acid Level In Vivo

2-hydroxybutyric acid (2HB) serves as an important regulatory factor in a variety of diseases. The circulating level of 2HB in serum is significantly higher in multiple diseases, such as cancer and type 2 diabetes (T2D). However, there is currently no systematic study on 2HB-producing bacteria that demonstrates whether gut bacteria contribute to the circulating 2HB pool. To address this question, we used BLASTP to reveal the taxonomic profiling of 2HB-producing bacteria in the human microbiome, which are mainly distributed in the phylum Proteobacteria and Firmicutes. In vitro experiments showed that most gut bacteria (21/32) have at least one path to produce 2HB, which includes Aspartic acid, methionine, threonine, and 2-aminobutyric acid. Particularly, Fusobacterium nucleatum has the strongest ability to synthesize 2HB, which is sufficient to alter colon 2HB concentration in mice. Nevertheless, neither antibiotic (ABX) nor Fusobacterium nucleatum gavage significantly affected mouse serum 2HB levels during the time course of this study. Taken together, our study presents the profiles of 2HB-producing bacteria and demonstrates that gut microbiota was a major contributor to 2HB concentration in the intestinal lumen but a relatively minor contributor to serum 2HB concentration.

Data-driven identification of plasma metabolite clusters and metabolites of interest for potential detection of early-stage non-small cell lung cancer cases versus cancer-free controls

BACKGROUND

Metabolomics is a potential means for biofluid-based lung cancer detection. We conducted a non-targeted, data-driven assessment of plasma from early-stage non-small cell lung cancer (ES-NSCLC) cases versus cancer-free controls (CFC) to explore and identify the classes of metabolites for further targeted metabolomics biomarker development.

METHODS

Plasma from 250 ES-NSCLC cases and 250 CFCs underwent ultra-high-performance liquid chromatography/quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-MS) in positive and negative electrospray ionization (ESI) modes. Molecular feature extraction, formula generation, and find-by-ion tools annotated metabolic entities. Analysis was restricted to endogenous metabolites present in ≥ 80% of samples. Unsupervised hierarchical cluster analysis identified clusters of metabolites. The metabolites with the strongest correlation with the principal component of each cluster were included in logistic regression modeling to assess discriminatory performance with and without adjustment for clinical covariates.

RESULTS

A total of 1900 UHPLC-QTOF-MS assessments identified 1667 and 2032 endogenous metabolites in the ESI-positive and ESI-negative modes, respectively. After data filtration, 676 metabolites remained, and 12 clusters of metabolites were identified from each ESI mode. Multivariable logistic regression using the representative metabolite from each cluster revealed effective classification of cases from controls with overall diagnostic accuracy of 91% (ESI positive) and 94% (ESI negative). Metabolites of interest identified for further targeted analysis include the following: 1b, 3a, 12a-trihydroxy-5b-cholanoic acid, pyridoxamine 5'-phosphate, sphinganine 1-phosphate, gamma-CEHC, 20-carboxy-leukotriene B4, isodesmosine, and 18-hydroxycortisol.

CONCLUSIONS

Plasma-based metabolomic detection of early-stage NSCLC appears feasible. Further metabolomics studies targeting phospholipid, steroid, and fatty acid metabolism are warranted to further develop noninvasive metabolomics-based detection of early-stage NSCLC.

Quantification of succinic acid levels, linked to succinate dehydrogenase (SDH) dysfunctions, by an automated and fully validated liquid chromatography tandem mass spectrometry method suitable for multi-matrix applications

The hallmarks of cancer include metabolism with deregulating cellular energetics. Dysfunctions in succinate dehydrogenase (SDH) metabolic enzyme activity, leading to an abnormal accumulation of succinic acid has been described in solid tumors but also in inflammation and ischemia reperfusion injury. Succinic acid is a potential biomarker of SDH related pathologies for diagnostic, evaluation of treatment response and follow-up of the disease. We developed a liquid chromatography tandem mass spectrometry (LC-MS/MS) method allowing a rapid, accurate and precise quantification of succinic acid levels in clinical (serum, urine) and preclinical (cellular pellets, supernatants) samples. ¹³C₄ succinic acid disodium salt was used as internal standard and added to samples before a solid phase extraction (SPE) on Phenomenex STRATA^TM XL-A (200 mg - 3 mL) 33 µm cartridges. This method is automated by a Freedom EVO® platform from TECAN and succinic acid is separated on a C18 column combined to a Xevo® TQ-S micro Waters mass spectrometer with electrospray ionization (ESI) source. This biomedical analysis allows standard curves to be linear over the range 1.0-135.5 µM with r² values > 0.999 and low matrix effects (<9.1 %). This method, which is validated according updated European Medicine Agency (EMA) guidelines, is accurate between-run (<11.0 %) and within-run (<7.8 %), precise between-run (<14.4 CV %) and within-run (<3.7 CV %), and is suitable for clinical and preclinical applications.

Serum metabolomic profiling based on GC/MS helped to discriminate Diffuse Large B-cell Lymphoma patients with different prognosis

BACKGROUND

The varied clinical outcomes of patients with Diffuse Large B Cell Lymphoma (DLBCL) are attributed to the different genetic and phenotypic subtypes. The purpose of this study was to determine whether metabolic alterations were related to cell-of-origin subtypes of DLBCL and find some metabolites which are associated with the clinical outcomes.

METHODS

Pre-treatment serum samples from eighty (80) newly diagnosed DLBCL patients, including twenty-eight (28) patients with Germinal Center B cell-like (GCB) subtypes and fifty-two (52) patients with non-GCB subtypes, were tested by the Gas Chromatography-Mass Spectrometry (GC-MS) technique. Univariate and multivariate analysis methods, principal component analysis (PCA), and partial least square discriminant analysis (PLS-DA) were conducted to examine the potential differential metabolites. Overall survival (OS) was calculated.

RESULTS

Overall, 65 out of 1472 entities were identified for subsequent analysis. Unfortunately, the initial PLS-DA analysis failed to discriminate GCB from non-GCB samples. Intriguingly, further PLS-DA analysis identified two subgroups of DLBCL (named as group A and group B) and the metabolic subgroups were significantly associated with overall survival. Valine, hexadecenoic acid, and pyroglutamic acid were identified and verified as the most important altered metabolites and could be candidate biomarkers for the prognosis of DLBCL.

CONCLUSIONS

Our results demonstrated that metabolic alterations in serum could be helpful to predict different clinical outcomes of DLBCL patients. Further studies are warranted to understand whether the altered metabolites might serve as prognostic factors for DLBCL.

Combined Metabolomics with Transcriptomics Reveals Important Serum Biomarkers Correlated with Lung Cancer Proliferation through a Calcium Signaling Pathway

Lung cancer (LC) is one of the most malignant cancers in the world, but currently, it lacks effective noninvasive biomarkers to assist its early diagnosis. Our study aims to discover potential serum diagnostic biomarkers for LC. In our study, untargeted serum metabolomics of a discovery cohort and targeted analysis of a test cohort were performed based on gas chromatography-mass spectrometry. Both univariate and multivariate statistical analyses were employed to screen for differential metabolites between LC and healthy control (HC), followed by the selection of candidate biomarkers through multiple algorithms. The results showed that 15 metabolites were significantly dysregulated between LC and HC, and a panel, comprising cholesterol, oleic acid, myo-inositol, 2-hydroxybutyric acid, and 4-hydroxybutyric acid, was demonstrated to have excellent differentiating capability for LC based on multiple classification modelings. In addition, the molecular interaction analysis combined with transcriptomics revealed a close correlation between the candidate biomarkers and LC proliferation via a Ca²⁺ signaling pathway. Our study discovered that cholesterol, oleic acid, myo-inositol, 2-hydroxybutyric acid, and 4-hydroxybutyric acid in combination could be a promising diagnostic biomarker for LC, and most importantly, our results will shed some light on the pathophysiological mechanism underlying LC to understand it deeply. The data that support the findings of this study are openly available in MetaboLights at https://www.ebi.ac.uk/metabolights/, reference number MTBLS1517.

Method development and validation for the quantification of organic acids in microbial samples using anionic exchange solid-phase extraction and gas chromatography-mass spectrometry

Organic acids play a key role in central metabolic functions of organisms, are crucial for understanding regulatory processes and are ubiquitous inside the cell. Therefore, quantification of these compounds provides a valuable approach for studying dynamics of metabolic processes, in particular when the organism faces changing environmental conditions. However, the extraction and analysis of organic acids can be challenging and validated methods available in this field are limited. In this study, we developed a method for the extraction and quantification of organic acids from microbial samples based on solid-phase extraction on a strong anionic exchange cartridge and gas chromatographic-mass spectrometric analysis. Full method validation was conducted to determine quality parameters of the new method. Recoveries for 12 of the 15 aromatic and aliphatic acids were between 100 and 111% and detection limits between 3 and 272 ng/mL. The ranges for the regression coefficients and process standard deviations for these compound classes were 0.9874–0.9994 and 0.04–0.69 μg/mL, respectively. Limitations were encountered when targeting aliphatic acids with hydroxy, oxo or enol ester functions. Finally, we demonstrated the applicability of the method on cell extracts of the bacterium Escherichia coli and the dinoflagellate Prorocentrum minimum.

Association between Metabolites and the Risk of Lung Cancer: A Systematic Literature Review and Meta-Analysis of Observational Studies

Globally, lung cancer is the most prevalent cancer type. However, screening and early detection is challenging. Previous studies have identified metabolites as promising lung cancer biomarkers. This systematic literature review and meta-analysis aimed to identify metabolites associated with lung cancer risk in observational studies. The literature search was performed in PubMed and EMBASE databases, up to 31 December 2019, for observational studies on the association between metabolites and lung cancer risk. Heterogeneity was assessed using the I2 statistic and Cochran's Q test. Meta-analyses were performed using either a fixed-effects or random-effects model, depending on study heterogeneity. Fifty-three studies with 297 metabolites were included. Most identified metabolites (252 metabolites) were reported in individual studies. Meta-analyses were conducted on 45 metabolites. Five metabolites (cotinine, creatinine riboside, N-acetylneuraminic acid, proline and r-1,t-2,3,c-4-tetrahydroxy-1,2,3,4-tetrahydrophenanthrene) and five metabolite groups (total 3-hydroxycotinine, total cotinine, total nicotine, total 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (sum of concentrations of the metabolite and its glucuronides), and total nicotine equivalent (sum of total 3-hydroxycotinine, total cotinine and total nicotine)) were associated with higher lung cancer risk, while three others (folate, methionine and tryptophan) were associated with lower lung cancer risk. Significant heterogeneity was detected across most studies. These significant metabolites should be further evaluated as potential biomarkers for lung cancer.

Simultaneous Quantification of γ-Hydroxybutyrate, γ-Butyrolactone, and 1,4-Butanediol in Four Kinds of Beverages

γ-Hydroxybutyrate (GHB) is a neurotransmitter, which exhibits a strong central nervous system depressant effect. The abuse of GHB or its precursor substances (γ-butyrolactone (GBL) and 1,4-butanediol (1,4-BD)) may cause serious problems. This study developed a fast and effective UHPLC-MS/MS method for the simultaneous quantification of GHB, GBL, and 1,4-BD in four popular beverages, including carbonated drinks, tea, apple cider vinegar, and coffee. The established method overcomes the influence of the in-source collision-induced dissociation of unstable compounds during quantification. The limits of detection were 0.2 μg/mL for GBL and 0.5 μg/mL for GHB and 1,4-BD with excellent linearity in the range of 0.2–50 μg/mL. The recoveries of the three compounds at three spiked levels (2.5, 5.0, and 10.0 μg/mL) in the four kinds of beverages studied were between 90 and 110%, while the relative standard deviations (RSDs) were all <10%. The matrix effect was negligible using this simple and appropriate preprocessed procedure. The method established in this study can quickly and reliably detect the GHB content and its analogues in beverages.

Analysis of low-molecular-weight metabolites in stomach cancer cells by a simplified and inexpensive GC/MS metabolomics method

GC/MS coupled metabolomics analysis, using a simplified and much less expensive silylation process with trimethylsilyl cyanide (TMSCN), was conducted to investigate metabolic abnormalities in stomach cancer cells. Under optimized conditions for derivatization by TMSCN and methanol extraction, 228 metabolites were detected using GC/MS spectrometry analysis, and 89 metabolites were identified using standard compounds and the NIST database. Ten metabolite levels were found to be lower in stomach cancer cells relative to normal cells. Among those ten metabolites, four metabolites-ribose, proline, pyroglutamic acid, and glucose-were known to be linked to cancers. In particular, pyroglutamic acid level showed a drastic reduction of 22-fold in stomach cancer cells. Since glutamine and glutamic acid are known to undergo cyclization to pyroglutamic acid, the 22-fold reduction might be the actual reduction in the levels of glutamine and/or glutamic acid-both known to be cancer-related. Hence, the marked reduction in pyroglutamic acid level might serve as a biomarker to aid early detection of stomach cancer. Graphical abstract.

Metabolomics of Children and Adolescents Exposed to Industrial Carcinogenic Pollutants

Studies on metabolomes of carcinogenic pollutants among children and adolescents are limited. We aim to identify metabolic perturbations in 107 children and adolescents (aged 9-15) exposed to multiple carcinogens in a polluted area surrounding the largest petrochemical complex in Taiwan. We measured urinary concentrations of eight carcinogen exposure biomarkers (heavy metals and polycyclic aromatic hydrocarbons (PAHs) represented by 1-hydroxypyrene), and urinary oxidative stress biomarkers and serum acylcarnitines as biomarkers of early health effects. Serum metabolomics was analyzed using a liquid chromatography mass spectrometry-based method. Pathway analysis and "meet-in-the-middle" approach were applied to identify potential metabolites and biological mechanisms linking carcinogens exposure with early health effects. We found 10 potential metabolites possibly linking increased exposure to IARC group 1 carcinogens (As, Cd, Cr, Ni) and group 2 carcinogens (V, Hg, PAHs) with elevated oxidative stress and deregulated serum acylcarnitines, including inosine monophosphate and adenosine monophosphate (purine metabolism), malic acid and oxoglutaric acid (citrate cycle), carnitine (fatty acid metabolism), and pyroglutamic acid (glutathione metabolism). Purine metabolism was identified as the possible mechanism affected by children and adolescents' exposure to carcinogens. These findings contribute to understanding the health effects of childhood and adolescence exposure to multiple industrial carcinogens during critical periods of development.

A study of low-molecular-weight organic acid urinary profiles in prostate cancer by a new liquid chromatography-tandem mass spectrometry method

Metabolomic studies constantly require high throughput screenings, and this drives development and optimization of methods that include more analytes in a single run, shorten the analysis time and simplify sample preparation. The aim of the study was to develop a new simple and fast liquid chromatography-tandem mass spectrometry-based methodology for quantitative analysis of a panel of ten organic acids in urine. The metabolites selected for the study include ten molecules potentially associated with cancer development. Chromatographic separation involved a Phenomenex Synergi Hydro-RP column under gradient conditions. Quantitation of the analytes was performed in multiple reaction monitoring mode under negative ionization. Validation parameters were satisfactory and in line with the international guidelines. The methodology enabled us to analyze urine samples collected from prostate cancer (PC) (n = 49) and benign prostate hyperplasia (BPH) (n = 49) patients. The obtained concentrations were normalized with urinary specific gravity (USG) prior to statistical analysis. Five analytes were quantified in all urine samples and we observed the following USG-normalized concentration ranges: citric acid (146.5-6339.8), 3-hydroxyisobutyric acid (22.5-431.7), 2-ketoglutaric acid (4.4-334.4), lactic acid (10.1-786.3), succinic acid (4.1-500.5). 3-hydroxyisobutyric acid significantly decreased between two groups of prostate cancer patients: ≥7 Gleason patients and <7 Gleason patients. Quick sample preparation limited to "dilute and shoot" makes the developed methodology a great tool for future metabolomic studies, especially for detecting disturbances in energy metabolism (Krebs cycle) and amino acids metabolism. The research also broadens our knowledge on the alteration of selected organic acids in PC and BPH patients.

Quantification of paracetamol and 5-oxoproline in serum by capillary electrophoresis: Implication for clinical toxicology

High anion gap metabolic acidosis frequently complicates acute paracetamol overdose and is generally attributed to lactic acidosis or compromised hepatic function. However, metabolic acidosis can also be caused by organic acid 5-oxoproline (pyroglutamic acid). Paracetamol's toxic intermediate, N-acetyl-p-benzoquinoneimine irreversibly binds to glutathione and its depletion leads to subsequent disruption of the gamma glutamyl cycle and an excessive 5-oxoproline generation. This is undoubtedly an underdiagnosed condition because measurement of serum 5-oxoproline level is not readily available. A simple, cost effective, and fast capillary electrophoresis method with diode array detection (DAD) for simultaneous measurement of both paracetamol (acetaminophen) and 5-oxoproline in serum was developed and validated. This method is highly suitable for clinical toxicology laboratory diagnostic, allowing rapid quantification of acidosis inducing organic acid 5-oxoproline present in cases of paracetamol overdose. The calibration dependence of the method was proved to be linear in the range of 1.3-250μgmL^-1, with adequate accuracy (96.4-107.8%) and precision (12.3%). LOQ equaled 1.3μgmL^-1 for paracetamol and 4.9μgmL^-1 for 5-oxoproline.

Study of early stage non-small-cell lung cancer using Orbitrap-based global serum metabolomics

Purpose

The aim of the project was to apply ultra-high-performance liquid chromatography–quadrupole-Orbitrap-high-resolution mass spectrometry for serum metabolite profiling of non-small-cell lung cancer (NSCLC). This Orbitrap-based methodology has been applied for a study of NSCLC potential markers for the first time.

Methods

After extraction using protein precipitation, sera were separated on the ACE Excel 2 C18-PFP (100 × 2.1 mm, 2.0 µm) column using gradient elution and analyzed within the range of 70–1000 m/z. Only patients with early stage disease (stages IA–IIB) were included in the study, providing opportunity to find biomarkers for early lung cancer detection. The resulting metabolite profiles were subjected to univariate and multivariate statistical tests.

Results

36 features were found significantly changed between NSCLC group and controls after FDR adjustment and 19 were identified using various metabolite databases (in-house library, HMDB, mzCloud). The study revealed a number of NSCLC biomarker candidates which belong to such compound classes as acylcarnitines, organic acids, and amino acids. Multivariate ROC curve built using 12 identified metabolites was characterized by AUC = 0.836 (0.722–0.946). There were no significant differences in the serum metabolite profiles between two most common histological types of lung cancer—adenocarcinoma and squamous cell carcinoma.

Conclusions

Through identification of novel potential tumor markers, Orbitrap-based global metabolic profiling is a useful strategy in cancer research. Our study can accelerate development of new diagnostic and therapeutic strategies in NSCLC. The metabolites involved in discrimination between NSCLC patients and the control subjects should be further explored using a targeted approach.

Electronic supplementary material

The online version of this article (doi:10.1007/s00432-017-2347-0) contains supplementary material, which is available to authorized users.