Polyamine profiles in the urine of patients with leukemia

Determination of polyamines in urine via electrospun nanofibers-based solid-phase extraction coupled with GC-MS and application to gastric cancer patients

The simultaneous determination of polyamines and their metabolites in urine samples was achieved by gas chromatography-mass spectrometry in the selected ion monitoring mode. After conjugating with the ion-pair reagent bis-2-ethylhexylphosphate in the aqueous phase, the polyamines in the samples were extracted with polystyrene nanofiber-based packed-fiber solid-phase extraction followed by a derivatization step using pentafluoropropionyl anhydride. With optimal conditions, all analytes were separated well. For analytes of putrescine, cadaverine, N-acetylputrescine, and N-acetylcadaverine, the linearity was good in the range of 0.05-500 μmol/L (R²  ≥ 0.993). While for spermidine, spermine, acetylspermidine, N⁸ -acetylspermidine, and N-acetylspermine, the linearity was good in the range of 0.5-500 μmol/L (R²  ≥ 0.990). The recoveries of three spiked concentrations (0.5, 5, 300 μmol/L) were 85.6%-108.4%, and relative standard deviations for intra- and interday were in the range of 2.9%-13.4% and 4.5%-15.1%, respectively. The method was successfully applied to the analysis of urine samples of gastric cancer patients. The results showed that the levels of most polyamines and N-acetylated polyamines from the patient group were significantly higher than those from the control group. The altered concentrations of the above-mentioned metabolites suggest their role in the pathogenesis of gastric cancer, and they should be further evaluated as potential markers of gastric cancer.

Search for Structural Basis of Interactions of Biogenic Amines with Human TAAR1 and TAAR6 Receptors

The identification and characterization of ligand-receptor binding sites are important for drug development. Trace amine-associated receptors (TAARs, members of the class A GPCR family) can interact with different biogenic amines and their metabolites, but the structural basis for their recognition by the TAARs is not well understood. In this work, we have revealed for the first time a group of conserved motifs (fingerprints) characterizing TAARs and studied the docking of aromatic (β-phenylethylamine, tyramine) and aliphatic (putrescine and cadaverine) ligands, including gamma-aminobutyric acid, with human TAAR1 and TAAR6 receptors. We have identified orthosteric binding sites for TAAR1 (Asp68, Asp102, Asp284) and TAAR6 (Asp78, Asp112, Asp202). By analyzing the binding results of 7500 structures, we determined that putrescine and cadaverine bind to TAAR1 at one site, Asp68 + Asp102, and to TAAR6 at two sites, Asp78 + Asp112 and Asp112 + Asp202. Tyramine binds to TAAR6 at the same two sites as putrescine and cadaverine and does not bind to TAAR1 at the selected Asp residues. β-Phenylethylamine and gamma-aminobutyric acid do not bind to the TAAR1 and TAAR6 receptors at the selected Asp residues. The search for ligands targeting allosteric and orthosteric sites of TAARs has excellent pharmaceutical potential.

Prioritizing candidate diseases-related metabolites based on literature and functional similarity

Background

As the terminal products of cellular regulatory process, functional related metabolites have a close relationship with complex diseases, and are often associated with the same or similar diseases. Therefore, identification of disease related metabolites play a critical role in understanding comprehensively pathogenesis of disease, aiming at improving the clinical medicine. Considering that a large number of metabolic markers of diseases need to be explored, we propose a computational model to identify potential disease-related metabolites based on functional relationships and scores of referred literatures between metabolites. First, obtaining associations between metabolites and diseases from the Human Metabolome database, we calculate the similarities of metabolites based on modified recommendation strategy of collaborative filtering utilizing the similarities between diseases. Next, a disease-associated metabolite network (DMN) is built with similarities between metabolites as weight. To improve the ability of identifying disease-related metabolites, we introduce scores of text mining from the existing database of chemicals and proteins into DMN and build a new disease-associated metabolite network (FLDMN) by fusing functional associations and scores of literatures. Finally, we utilize random walking with restart (RWR) in this network to predict candidate metabolites related to diseases.

Results

We construct the disease-associated metabolite network and its improved network (FLDMN) with 245 diseases, 587 metabolites and 28,715 disease-metabolite associations. Subsequently, we extract training sets and testing sets from two different versions of the Human Metabolome database and assess the performance of DMN and FLDMN on 19 diseases, respectively. As a result, the average AUC (area under the receiver operating characteristic curve) of DMN is 64.35%. As a further improved network, FLDMN is proven to be successful in predicting potential metabolic signatures for 19 diseases with an average AUC value of 76.03%.

Conclusion

In this paper, a computational model is proposed for exploring metabolite-disease pairs and has good performance in predicting potential metabolites related to diseases through adequate validation. This result suggests that integrating literature and functional associations can be an effective way to construct disease associated metabolite network for prioritizing candidate diseases-related metabolites.

A pilot case-control study on the association between N-acetyl derivatives in serum and first-episode schizophrenia

N-acetyl group metabolites are a general class of endogenous compounds characterized by a conjugated system consisting of an acetyl group and nitrogen moiety. The aim of our exploratory pilot case-control study is to compare the levels of five N-acetyl derivatives (i.e., N-acetyl-glutamine, N-acetyl-ornithine, N⁶-acetyl-L-lysine, N-acetyl-putrescine, and N-acetyl-galactosamine) in serum samples between individuals with first-episode schizophrenia and healthy controls (HC). A 1:2 age- and sex- matched pilot case-control study was performed, involving 30 cases of first-episode schizophrenia and 60 HC aged between 18 and 40 years old. The serum samples containing these N-acetyl derivatives from (first-episode patients with schizophrenia and HC were measured using liquid chromatography-tandem mass spectrometry (LC-MS). Results indicated that higher levels of N-acetyl-glutamine and lower levels of N⁶-acetyl-L-lysine may have a significant association with schizophrenia after adjusting for age, sex and BMI. N-acetyl-putrescine was elevated among subjects with first-episode schizophrenia when compared to HC, suggesting it as a predictor for schizophrenia onset. Further exploration of the mechanisms of N-acetyl group metabolites with respect to schizophrenia is warranted and may be useful for identifying novel disease markers and/or drug target molecules in schizophrenia.

Rapid LC-MS/MS quantification of cancer related acetylated polyamines in human biofluids

Increased urinary acetylated polyamines (APs) are reported as cancer biomarkers in many studies. N¹,N¹²-diacetylspermine has been proposed as a biomarker indicative of different cancers in urine and plasma. N¹-Acetylspermine has previously been found to be increased in the saliva of patients with breast cancer; however, in plasma this metabolite was too low abundant to be detected by previous analytical methods. In addition, no method has been reported to perform AP analysis on the level of speed, robustness and sensitivity required for daily clinical routines. Here we describe a high-throughput sample preparation and LC-MS/MS method for the fast, accurate and precise quantification of three APs: N⁸-acetylspermidine, N¹-acetylspermine, and N¹,N¹²-diacetylspermine in plasma, urine and saliva. Stable isotope labeled N¹,N¹²-diacetylspermine was used as internal standard. Robustness was validated by intra- and inter-day reproducibility. Precision and accuracy of the method were tested at six concentration levels from 0.0375 to 750 ng/mL resulting in less than 15% relative standard deviation and less than 15% percent error in quantification. Using 96-well plates, the assay described herein allows for preparing, analyzing, and quantifying 240 samples per day for a single researcher to quantify three APs commonly related to cancer status.

Metabolomics profiling in plasma samples from glioma patients correlates with tumor phenotypes

Background

Tumor-based molecular biomarkers have redefined in the classification gliomas. However, the association of systemic metabolomics with glioma phenotype has not been explored yet.

Methods

In this study, we conducted two-step (discovery and validation) metabolomic profiling in plasma samples from 87 glioma patients. The metabolomics data were tested for correlation with glioma grade (high vs low), glioblastoma (GBM) versus malignant gliomas, and IDH mutation status.

Results

Five metabolites, namely uracil, arginine, lactate, cystamine, and ornithine, significantly differed between high- and low-grade glioma patients in both the discovery and validation cohorts. When the discovery and validation cohorts were combined, we identified 29 significant metabolites with 18 remaining significant after adjusting for multiple comparisons. Those 18 significant metabolites separated high- from low-grade glioma patients with 91.1% accuracy. In the pathway analysis, a total of 18 significantly metabolic pathways were identified. Similarly, we identified 2 and 6 metabolites that significantly differed between GBM and non-GBM, and IDH mutation positive and negative patients after multiple comparison adjusting. Those 6 significant metabolites separated IDH1 mutation positive from negative glioma patients with 94.4% accuracy. Three pathways were identified to be associated with IDH mutation status. Within arginine and proline metabolism, levels of intermediate metabolites in creatine pathway were all significantly lower in IDH mutation positive than in negative patients, suggesting an increased activity of creatine pathway in IDH mutation positive tumors.

Conclusion

Our findings identified metabolites and metabolic pathways that differentiated tumor phenotypes. These may be useful as host biomarker candidates to further help glioma molecular classification.

Cerebrospinal fluid metabolomic profiles can discriminate patients with leptomeningeal carcinomatosis from patients at high risk for leptomeningeal metastasis

Purpose

Early diagnosis of leptomeningeal carcinomatosis (LMC) is necessary to improve outcomes of this formidable disease. However, cerebrospinal fluid (CSF) cytology is frequently false negative. We examined whether CSF metabolome profiles can be used to differentiate patients with LMC from patients having a risk for development of LMC.

Results

A total of 10,905 LMIs were evaluated using PCA-DA. The LMIs defined Group 2 with a sensitivity of 85% and a specificity of 91%. After selecting 33 LMIs, including diacetylspermine and fibrinogen fragments, the CSF metabolomics profile had a sensitivity of 100% and a specificity of 93% for discriminating Group 1b from the other groups. After selecting 21 LMIs, including phosphatidylcholine, the CSF metabolomics profile differentiated LMC (Group 2) patients from the high-risk groups of Group 3 and Group 4 with 100% sensitivity and 100% specificity.

Materials and Methods

We prospectively collected CSF from five groups of patients: Group 1a, systemic cancer; Group 1b, no tumor; Group 2, LMC; Group 3, brain metastasis; Group 4, brain tumor other than brain metastasis. All metabolites in the CSF samples were detected as low-mass ions (LMIs) using mass spectrometry. Principal component analysis-based discriminant analysis (PCA-DA) and two search algorithms were used to select the LMIs that differentiated the patient groups of interest from controls.

Conclusions

Analysis of CSF metabolite profiles could be used to diagnose LMC and exclude patients at high-risk of LMC with a 100% accuracy. We expect a future validation trial to evaluate CSF metabolic profiles supporting CSF cytology.

Polyamine Metabolites Profiling for Characterization of Lung and Liver Cancer Using an LC-Tandem MS Method with Multiple Statistical Data Mining Strategies: Discovering Potential Cancer Biomarkers in Human Plasma and Urine

Polyamines, one of the most important kind of biomarkers in cancer research, were investigated in order to characterize different cancer types. An integrative approach which combined ultra-high performance liquid chromatography—tandem mass spectrometry detection and multiple statistical data processing strategies including outlier elimination, binary logistic regression analysis and cluster analysis had been developed to discover the characteristic biomarkers of lung and liver cancer. The concentrations of 14 polyamine metabolites in biosamples from lung (n = 50) and liver cancer patients (n = 50) were detected by a validated UHPLC-MS/MS method. Then the concentrations were converted into independent variables to characterize patients of lung and liver cancer by binary logic regression analysis. Significant independent variables were regarded as the potential biomarkers. Cluster analysis was engaged for further verifying. As a result, two values was discovered to identify lung and liver cancer, which were the product of the plasma concentration of putrescine and spermidine; and the ratio of the urine concentration of S-adenosyl-l-methionine and N-acetylspermidine. Results indicated that the established advanced method could be successfully applied to characterize lung and liver cancer, and may also enable a new way of discovering cancer biomarkers and characterizing other types of cancer.

Use of microextraction by packed sorbents and gas chromatography-mass spectrometry for the determination of polyamines and related compounds in urine

A novel methodology for the determination of ornithine, putrescine, cadaverine, spermidine and gamma-amino butyric acid in urine samples has been developed. The method uses in situ aqueous derivatization followed by automated microextraction by packed sorbent coupled to a gas chromatography-mass spectrometry system equipped with a programmed temperature vaporizer. This instrumental configuration minimizes sample manipulation due to from the mixing of the reagents, the process is completely automated. The analytes were derivatized using ethyl chloroformate as derivatization reagent. The reaction occurred in aqueous medium and was carried out in 1min in the vial of an autosampler used to perform microextraction by packed sorbent. The parameters affecting derivatization, extraction and separation were optimized in order to obtain maximum sensitivity. Calibration curves were obtained for five calibration levels in three different matrices. All the calibration models displayed good linearity, with R(2) values higher than 0.95. The validity of the models was checked using ANOVA, and it was observed that they did not exhibit any lack of fit. Repeatability and reproducibility was evaluated, with values below 15% in both cases. LOD and LOQ values were found to be in the low μg/L level. Influence of the matrix was confirmed, thus quantification was performed using the standard additions method and normalization to IS. The method developed was applied to the analysis of these compounds in urine samples from healthy individuals and cancer diagnosed patients (Internal Medicine Unit of the Virgen de la Vega Hospital, Salamanca, Spain). Significant differences (Mann-Whitney U test) were observed for putrescine and ornithine concentrations.

Metabolomics: beyond biomarkers and towards mechanisms

Metabolomics, which is the profiling of metabolites in biofluids, cells and tissues, is routinely applied as a tool for biomarker discovery. Owing to innovative developments in informatics and analytical technologies, and the integration of orthogonal biological approaches, it is now possible to expand metabolomic analyses to understand the systems-level effects of metabolites. Moreover, because of the inherent sensitivity of metabolomics, subtle alterations in biological pathways can be detected to provide insight into the mechanisms that underlie various physiological conditions and aberrant processes, including diseases.

Diacetylated derivatives of spermine and spermidine as novel promising tumor markers

N1,N12-diacetylspermine (DiAcSpm) and N1,N8-diacetylspermidine (DiAcSpd) are minor components of human urinary polyamine to which little attention has been paid until recently. HPLC analysis of urinary polyamines has revealed that the excretion of these diacetylpolyamines, in particular, into urine was frequently and markedly increased in association with every type of cancer so far examined. Remission was usually accompanied by recovery of urinary diacetylpolyamines to the normal level. DiAcSpm was more sensitive than CEA for detecting colorectal cancer patients, while DiAcSpd was highly specific for malignant conditions in that the excretion of the latter was scarcely elevated in cases of benign urogenital diseases. An ELISA procedure for rapid determination of DiAcSpm was developed to promote the clinical application of these new tumor markers, and subsequent studies indicated that DiAcSpm was elevated in 60% of colorectal cancer patients at early stages (stage 0 + I), whereas only 10% of these patients were CEA-positive. DiAcSpm may also be useful as a follow-up marker that is efficient for detecting recurrence and sensitive to changes in the clinical condition of patients. The evidence accumulated so far indicates that DiAcSpm and DiAcSpd are promising novel tumor markers. They deserve more intensive studies, including studies of their biochemistry and metabolism.

Molecular recognition of protonated polyamines at calix[4]crown-5 self-assembled monolayer modified electrodes by impedance measurements

Molecular recognition of protonated aliphatic polyamines has been studied at calix[4]crown-5 self-assembled monolayer modified gold electrodes by electrochemical impedance spectroscopic (EIS) experiments. The energy of complex formation between the calix [4]crown-5 molecule and a series of alkyl ammonium ions was shown by molecular modeling and EIS experiments to depend on the number of amine groups in the alkyl chain as well as the number of methylene groups between the amine groups. The structures of complexes formed between the crown ether on the lower rim of calix[4]arene and protonated amines were determined by minimizing the complex formation energies. The adducts thus formed on the SAM rendered the electron transfer from the electrode to the probe (Fe(CN)63-/4- pair) easier or more difficult depending on the number of ammonium groups and their arrangement in linear alkyl chains. Analytical procedures have been developed to detect protonated spermidine (a recognized cancer marker) in simulated urine, blood, erythrocyte, and cerebrospinal fluids.

N(1),N(12)-Diacetylspermine as a sensitive and specific novel marker for early- and late-stage colorectal and breast cancers

PURPOSE

N(1),N(12)-diacetylspermine (DiAcSpm) in the urine of colorectal and breast cancer patients was examined to establish its usefulness as a novel diagnostic tool for detecting these cancers at clinically early stages.

EXPERIMENTAL DESIGN

Urine samples from 248 colon cancer patients and 83 breast cancer patients as well as 51 patients with benign gastrointestinal diseases treated in Tokyo Metropolitan Komagome Hospital during the period of August 1999 to January 2004 were collected. DiAcSpm was analyzed by ELISA and its sensitivity for malignant conditions was compared with that of serum carcinoembryonic antigen (CEA), CA19-9, and CA15-3.

RESULTS

The sensitivity of urinary DiAcSpm for colon cancer patients (n = 248) was 75.8% (mean +/- 2 SD for 52 healthy controls as a cutoff value), which was markedly higher than the sensitivities of serum CEA (39.5%, P < 0.0001) and CA19-9 (14.1%, P < 0.0001). DiAcSpm was elevated in 60% of tumor-node-metastasis cancer stage 0 + I patients, whereas only 10% (P < 0.0001) and 5% (P < 0.0001) of these patients were CEA- and CA19-9-positive, respectively. The sensitivity of urinary DiAcSpm for 83 cases of breast cancer (60.2%) was higher than the sensitivities of CEA (37.3%, P = 0.0032) and CA15-3 (37.3%, P = 0.0032). DiAcSpm was elevated in 28% of tumor-node-metastasis stage I + II patients, whereas only 3% (P = 0.0064) and 0% (P = 0.001) of these patients were CEA- and CA15-3-positive, respectively.

CONCLUSION

The observations indicate that urinary DiAcSpm is a more sensitive marker than CEA, CA19-9, and CA15-3 and that it can efficiently detect colorectal and breast cancers at early stages.

Impact of Topoisomerase II alpha and spermine on the clinical outcome of children with acute lymphoblastic leukemia

It has been reported in the literature that a leukemic cell may be (or become) resistant to anti-cancer treatment because many mechanisms, such as efflux membrane pump (multi-drug resistance, MDR-P170), intracellular transport (LRP, MRP), or different detoxification systems (glutathione transferases, methallothioneines) may be implicated. Topoisomerase II alpha (TopoII) are also reported as responsible for resistance since their main action is to repair DNA breakage. Polyamines are described as having a protective DNA action by stabilizing the double stranded DNA helix. For these reasons we investigated 65 children with acute lymphoblastic leukemia using an immunocytochemical method to elucidate the potential role of Topoisomerase and polyamines in drug resistance. Most children (60/65) were treated with the French (acute lymphoblastic leukemia, ALL) protocol (FRALLE-93) in which B and C arms include (at least) VP16. Children with cytoplasmic TopoII positivity (18 cases) were more resistant since their overall survival was 34 months compared to more than 110 months for negative cases ( P = 0.0003). Polyamines may be associated with drug resistance since the overall survivals were 51 months and 92 months for positive and negative patients, respectively, but the P-value is only 0.13. We conclude that Topoisomerase and polyamines must be tested at diagnosis as new possible markers for chemo-resistance. Larger series are needed to confirm these preliminary results and to verify if the use of anti epipodophillotoxin agents (as it is the case for FRALLE B or C) should be excluded for positive cases.