Metabolomic analysis of plasma from breast tumour patients. A pilot study.

BACKGROUND: Patients at risk of breast cancer are submitted to mammography, resulting in a classification of the lesions following the Breast Imaging Reporting and Data System (BI-RADS®). Due to BI-RADS 3 classification problems and the great uncertainty of the possible evolution of this kind of tumours, the integration of mammographic imaging with other techniques and markers of pathology, as metabolic information, may be advisable. DESIGN AND METHODS: Our study aims to evaluate the possibility to quantify by gas chromatography-mass spectrometry (GC-MS) specific metabolites in the plasma of patients with mammograms classified from BI-RADS 3 to BI-RADS 5, to find similarities or differences in their metabolome. Samples from BI-RADS 3 to 5 patients were compared with samples from a healthy control group. This pilot project aimed at establishing the sensitivity of the metabolomic classification of blood samples of patients undergoing breast radiological analysis and to support a better classification of mammographic cases. RESULTS: Metabolomic analysis revealed a panel of metabolites more abundant in healthy controls, as 3-aminoisobutyric acid, cholesterol, cysteine, stearic, linoleic and palmitic fatty acids. The comparison between samples from BI-RADS 3 and BI-RADS 5 patients, revealed the importance of 4-hydroxyproline, found in higher amount in BI-RADS 3 subjects. CONCLUSION: Although the low sample number did not allow the attainment of high validated statistical models, some interesting data were obtained, revealing the potential of metabolomics for an improvement in the classification of different mammographic lesions.

Metabolomic profile of patients with left ventricular assist devices: a pilot study.

BACKGROUND: Metabolomic profiling has important diagnostic and prognostic value in heart failure (HF). We investigated whether left ventricular assist device (LVAD) support has an impact on the metabolomic profile of chronic HF patients and if specific metabolic patterns are associated with the development of adverse events. METHODS: We applied untargeted metabolomics to detect and analyze molecules such as amino acids, sugars, fatty acids and other metabolites in plasma samples collected from thirty-three patients implanted with a continuous-flow LVAD. Data were analyzed at baseline, i.e., before implantation of the LVAD, and at long-term follow-up. RESULTS: Our results reveal significant changes in the metabolomic profile after LVAD implant compared to baseline. In detail, we observed a pre-implant reduction in amino acid metabolism (aminoacyl-tRNA biosynthesis) and increased galactose metabolism, which reversed over the course of support [median follow-up 187 days (63-334 days)]. These changes were associated with improved patient functional capacity driven by LVAD therapy, according to NYHA functional classification of HF (NYHA class I-II: pre-implant =0% of the patients; post-implant =97% of the patients; P<0.001). Moreover, patients who developed adverse thromboembolic events (n=4, 13%) showed a pre-operative metabolomic fingerprint mainly associated with alterations of fatty acid biosynthesis and mitochondrial beta-oxidation of short-chain saturated fatty acids. CONCLUSIONS: Our data provide preliminary evidence that LVAD therapy is associated with changes in the metabolomic profile of HF and suggest the potential use of metabolomics as a new tool to stratify LVAD patients in regard to the risk of adverse events.

Metabolomic Analysis of Patients with Chronic Myeloid Leukemia and Cardiovascular Adverse Events after Treatment with Tyrosine Kinase Inhibitors.

BACKGROUND: Cardiovascular adverse events (CV-AEs) are considered critical complications in chronic myeloid leukemia (CML) patients treated with second- and third-generation tyrosine kinase inhibitors (TKIs). The aim of our study was to assess the correlation between metabolic profiles and CV-AEs in CML patients treated with TKIs. METHODS: We investigated 39 adult CML patients in chronic-phase (mean age 49 years, range 24-70 years), with no comorbidities evidenced at baseline, who were consecutively identified with CML and treated with imatinib, nilotinib, dasatinib, and ponatinib. All patients performed Gas-Chromatography-Mass-Spectrometry-based metabolomic analysis and were divided into two groups (with and without CV-AEs). RESULTS: Ten CV-AEs were documented. Seven CV-AEs were rated as 3 according to the Common Toxicity Criteria, and one patient died of a dissecting aneurysm of the aorta. The patients' samples were clearly separated into two groups after analysis and the main discriminant metabolites were tyrosine, lysine, glutamic acid, ornithine, 2-piperdinecarboxylic acid, citric acid, proline, phenylalanine, threonine, mannitol, leucine, serine, creatine, alanine, and 4-hydroxyproline, which were more abundant in the CV-AE group. Conversely, myristic acid, oxalic acid, arabitol, 4-deoxy rithronic acid, ribose, and elaidic acid were less represented in the CV-AE group. CONCLUSIONS: CML patients with CV-AEs show a different metabolic profile, suggesting probable mechanisms of endothelial damage.

Synthesis, protonation constants and biological activity determination of amino acid-salicylaldehyde-derived Schiff bases.

Schiff bases represent a class of molecules widely studied for their importance in organic and coordination chemistry. Despite the large amount of studies on the chemical and biological properties of the Schiff bases, the different experimental conditions prevent a useful comparison to search for a correlation structure-activity. Moreover, literature is lacking in comprehensive data on the spectroscopic characterization of these compounds. For this reason, six Schiff bases, derived from salicylaldehyde and natural amino acids were fully characterized by nuclear magnetic resonance and infrared spectroscopy, and their aqueous solution equilibria, antiproliferative activity and DNA-binding activity were examined. All experimental conditions were kept constants to achieve comparable information and useful insights about their structure-activity correlation. The synthesized compounds showed DNA binding constants in the 101-102 M-1 range, depending on the substituent present in the amino acid side-chain, and resulted devoid of significant cytotoxic activity against the different human tumor cell lines showing IC50 values higher than 100 µM.

The Metabolomic Profile of Lymphoma Subtypes: A Pilot Study.

Lymphoma defines a group of different diseases. This study examined pre-treatment plasma samples from 66 adult patients (aged 20-74) newly diagnosed with any lymphoma subtype, and 96 frequency matched population controls. We used gas chromatography-mass spectrometry (GC-MS) to compare the metabolic profile by case/control status and across the major lymphoma subtypes. We conducted univariate and multivariate analyses, and partial least square discriminant analysis (PLS-DA). When compared to the controls, statistically validated models were obtained for diffuse large B-cell lymphoma (DLBCL), chronic lymphocytic leukemia (CLL), multiple myeloma (MM), and Hodgkin lymphoma (HL), but not follicular lymphoma (FL). The metabolomic analysis highlighted interesting differences between lymphoma patients and population controls, allowing the discrimination between pathologic and healthy subjects: Important metabolites, such as hypoxanthine and elaidic acid, were more abundant in all lymphoma subtypes. The small sample size of the individual lymphoma subtypes prevented obtaining PLS-DA validated models, although specific peculiar features of each subtype were observed; for instance, fatty acids were most represented in MM and HL patients, while 2-aminoadipic acid, 2-aminoheptanedioic acid, erythritol, and threitol characterized DLBCL and CLL. Metabolomic analysis was able to highlight interesting differences between lymphoma patients and population controls, allowing the discrimination between pathologic and healthy subjects. Further studies are warranted to understand whether the peculiar metabolic patterns observed might serve as early biomarkers of lymphoma.

A gas chromatography-mass spectrometry (GC-MS) metabolomic approach in human colorectal cancer (CRC): the emerging role of monosaccharides and amino acids.

BACKGROUND: Colorectal cancer (CRC) has been confirmed to be the third most commonly diagnosed cancer in males and the second in females. We investigated the blood plasma metabolome in CRC patients and in healthy adults to elucidate the role of monosaccharides, amino acids, and their respective metabolic pathways as prognostic factors in patients with CRC. METHODS: Fifteen patients with CRC and nine healthy adults were enrolled in the study and their blood plasma samples analyzed by gas chromatography-mass spectrometry (GC-MS). Univariate Student's t-test, multivariate principal component analysis (PCA) and partial least square-discriminant analysis (PLS-DA) were conducted on MetaboAnalyst 4.0. The analysis of metabolic profiles was carried out by the web-based extension Metabolite Sets Enrichment Analysis (MSEA). RESULTS: Overall, 125 metabolites were identified in plasma samples by GC-MS. In CRC patient samples, nine metabolites, including D-mannose and fructose, were significantly more abundant than in controls; conversely, eleven amino derivatives were less abundant, including methionine, valine, lysine, and proline. Methionine was significantly less abundant in died patients compared with survivors. The most significantly altered metabolic pathways in CRC patients are those involving monosaccharides (primarily the catabolic pathway of fructose and D-mannose), and amino acids (primarily methionine, valine, leucine, and isoleucine). CONCLUSIONS: The abundance of D-mannose in CRC patient samples contributes to inhibiting the growth of cancer cells, while the abundance of fructose may be consistent either with low consumption of fructose by aerobic glycolysis within cancer cells or with a high bioavailability of fructose from diet. The reduction in methionine concentration may be related to increased activity of the threonine and methionine catabolic pathways, confirmed by high levels of α-hydroxybutyrate.

Urine metabolome analysis by gas chromatography-mass spectrometry (GC-MS): Standardization and optimization of protocols for urea removal and short-term sample storage.

BACKGROUND: Before derivatization, urine analyzed by gas chromatography-mass spectrometry (GC-MS) requires the complete removal of urea to avoid interferences. We aimed at establishing the most effective sample pretreatment for urea removing; moreover, we explored the impact of two short-term sample storage conditions on urine metabolome. METHODS: 92 aliquots were obtained from a single sample collected from a healthy adult; they were divided into 6 groups. Group 1 consisted of untreated aliquots while groups 2-6 differed from each other for the addition of various defined urease solution volumes combined with either 30 min or 1-hour sonication time. Urine sample storage was tested by comparing 20 fresh aliquots analyzed after collection with 20 aliquots frozen at -80 °C for 72 h. RESULTS: the most effective protocol consisted of the combination between 200 µL urease solution with 1-h sonication time; urease solution volumes >200 µL increase the risk to underestimate metabolite peaks because of sample dilution. Short-term storage of samples at -80 °C pointed out significant changes in the urine metabolic profile compared with that of fresh samples. CONCLUSIONS: our study confirms the importance of urea removal for a reliable recognition and quantitation of metabolites; urine short-term storage at -80 °C should be carefully reconsidered.

Urinary gas chromatography mass spectrometry metabolomics in asphyxiated newborns undergoing hypothermia: from the birth to the first month of life.

BACKGROUND: Perinatal asphyxia is a severe clinical condition affecting around four million newborns worldwide. It consists of an impaired gas exchange leading to three biochemical components: hypoxemia, hypercapnia and metabolic acidosis. METHODS: The aim of this longitudinal experimental study was to identify the urine metabolome of newborns with perinatal asphyxia and to follow changes in urine metabolic profile over time. Twelve babies with perinatal asphyxia were included in this study; three babies died on the eighth day of life. Total-body cooling for 72 hours was carried out in all the newborns. Urine samples were collected in each baby at birth, after 48 hours during hypothermia, after the end of the therapeutic treatment (72 hours), after 1 week of life, and finally after 1 month of life. Urine metabolome at birth was considered the reference against which to compare metabolic profiles in subsequent samples. Quantitative metabolic profiling in urine samples was measured by gas chromatography mass spectrometry (GC-MS). The statistical approach was conducted by using the multivariate analysis by means of principal component analysis (PCA) and orthogonal partial least square discriminant analysis (OPLS-DA). Pathway analysis was also performed. RESULTS: The most important metabolites depicting each time collection point were identified and compared each other. At birth before starting therapeutic hypothermia (TH), urine metabolic profiles of the three babies died after 7 days of life were closely comparable each other and significantly different from those in survivors. CONCLUSIONS: In conclusion, a plethora of data have been extracted by comparing the urine metabolome at birth with those observed at each time point collection. The modifications over time in metabolites composition and concentration, mainly originated from the depletion of cellular energy and homeostasis, seems to constitute a fingerprint of perinatal asphyxia.

Primary HCMV infection in pregnancy from classic data towards metabolomics: An exploratory analysis.

BACKGROUND: Human cytomegalovirus (HCMV) is one of the most frequent risk of viral infections during pregnancy. The aim of this study was to evaluate the metabolic profile in amniotic fluid (AF) samples obtained from HCMV-infected, and uninfected fetuses in order to elucidate changes in metabolic pathways during congenital HCMV infection and to recognize new potential diagnostic and/or prognostic biomarkers. METHODS: A retrospective cohort study was conducted on 63 pregnant women: 20 contracted primary HCMV infection during pregnancy and, subsequently, transmitted the virus to the fetus (transmitters); 20 contracted the infection without transmitting the virus to the fetus (non-transmitters); 23 who underwent amniocentesis for cytogenetic-based diagnosis were considered controls. Metabolomics analysis was performed by using the hyphenated technique Gas chromatography-mass spectrometry (GC-MS) followed by a multivariate statistical approach. Four PLS-DA models were generated: controls vs. transmitters; controls vs. non-transmitters; transmitters vs. non-transmitters; and asymptomatic infected vs. symptomatic infected newborns. Subsequently, these models were exploited for network mapping. RESULTS: Compared with controls, HCMV transmitters showed significantly increased levels in glutamine, glycine, serine, pyruvic acid, threonine, threonic acid, and cystine; conversely, unknown U1715 and U1804, glutamic acid, U1437, fructose, sugar-like A203003 and A203005, and tyrosine levels were found decreased. In non-transmitters, glutamine, serine, glycine, threonic acid, threonine, 1-monostearin, urea, and cystine were found increased, while sorbitol, unknown U1804, sugar-like A203003, U1751, xylitol, leucine and fructose were decreased. The comparison between transmitters and non-transmitters did not produce a statistically significant model. Unlike controls' profile, a common feature of HCMV infected subjects (transmitters and non-transmitters) was the activation of glutamine-glutamate and pyrimidine metabolic pathways. In addition, a clusterization for asymptomatic vs. symptomatic outcome was also observed due to alteration of fatty acids biosynthesis. CONCLUSIONS: Metabolomics approach could highlight the significant modification of maternal and placental status during HCMV infection for both transmitter and non-transmitter subjects. A further separation was observed for asymptomatic vs. symptomatic HCMV congenital infections model. Therefore, metabolomics may be a promising tool to improve the accuracy of an early diagnosis, and the management of HCMV pregnancy-related infections.