Comparative Analysis of Amino Acid Profiles in Patients with Glioblastoma and Meningioma Using Liquid Chromatography Electrospray Ionization Tandem Mass Spectrometry (LC-ESI-MS/MS).

Brain tumors account for 1% of all cancers diagnosed de novo. Due to the specificity of the anatomical area in which they grow, they can cause significant neurological disorders and lead to poor functional status and disability. Regardless of the results of biochemical markers of intracranial neoplasms, they are currently of no diagnostic significance. The aim of the study was to use LC-ESI-MS/MS in conjunction with multivariate statistical analyses to examine changes in amino acid metabolic profiles between patients with glioblastoma, meningioma, and a group of patients treated for osteoarthritis of the spine as a control group. Comparative analysis of amino acids between patients with glioblastoma, meningioma, and the control group allowed for the identification of statistically significant differences in the amino acid profile, including both exogenous and endogenous amino acids. The amino acids that showed statistically significant differences (lysine, histidine, α-aminoadipic acid, phenylalanine) were evaluated for diagnostic usefulness based on the ROC curve. The best results were obtained for phenylalanine. Classification trees were used to build a model allowing for the correct classification of patients into the study group (patients with glioblastoma multiforme) and the control group, in which cysteine turned out to be the most important amino acid in the decision-making algorithm. Our results indicate amino acids that may prove valuable, used alone or in combination, toward improving the diagnosis of patients with glioma and meningioma. To better assess the potential utility of these markers, their performance requires further validation in a larger cohort of samples.

Serum amino acid profiling in differentiating clinical outcomes of multiple sclerosis.

AIM OF THE STUDY: Amino acid metabolism is crucial for regulating immune responses and can be monitored in blood serum samples. This study aimed to analyse serum amino acid profiles in people with multiple sclerosis (pwMS), taking into account differences depending on the disease outcomes. CLINICAL RATIONALE FOR THE STUDY: Serum amino acid profiling is a promising, reproducible and minimally invasive technology, available at different stages of the disease, enabling the search for a specific biomarker to differentiate MS clinical outcomes. MATERIAL AND METHODS: The serum concentrations of 29 amino acids were determined using high-performance liquid chromatography mass spectrometry. RESULTS: A total of 121 pwMS (41 relapsing-remitting MS-RRMS; 55 secondary progressive MS - SPMS; and 25 primary progressive MS-RRMS) with a median Expanded Disability Status Scale (EDSS) score of 6 and 53 healthy controls (HCs) were included. We found significantly higher serum total amino acids concentrations in pwMS compared to HCs. Serum concentrations of arginine, 1-methyl-L-histidine and proline were higher in pwMS, while circulating citrulline, α-aminobutyric acid and tryptophan were lower in pwMS. We observed significant differences in serum total amino acids concentrations depending on MS type, with the highest level in the PPMS group and the lowest in the RRMS group. We found significantly higher serum levels of beta-aminoisobutyric acid in PPMS patients compared to those with RRMS and SPMS, and significantly higher serum levels of aspartic acid in PPMS patients compared to RRMS patients. From visual inspection, no trend was observed in total amino acids concentration with respect to the EDSS score. When analysing serum total amino acids concentration in pwMS with EDSS ≤ 5 compared to those with EDSS > 5, no significant differences were found. CONCLUSIONS AND CLINICAL IMPLICATIONS: Amino acid metabolism is altered in pwMS and depends on the clinical type of the disease. Further studies are needed to determine whether serum metabolomic profiling of amino acids may have an application in the search for clinical phenotype-specific MS biomarkers.

Serum amino acid profiles in patients with myasthenia gravis.

Myasthenia gravis (MG) is an autoimmune disease characterized by weakness and rapid fatigue. Diagnostic methods used for myasthenia gravis are not conclusive and satisfactory, therefore it is necessary to develop reliable tools to help diagnose myasthenia gravis as early as possible. The aim of the study was to use HPLC-MS in conjunction with multivariate statistical analyses to investigate changes in the amino acid metabolic profiles between myasthenia gravis patients compared and controls. In addition, the effect of treatment regimens and myasthenia gravis type, on the observed changes in amino acid metabolic profiles were assessed. Serum levels of 29 amino acids were determined in 2 groups of individuals-28 patients with myasthenia gravis and 53 control subjects (CS). The results of our study indicate that serum levels of several amino acids in patients with myasthenia gravis changed significantly compared to the control group. Statistical analysis revealed differences between amino acids concentration in patients with different therapeutic scheme. In conclusion, amino acids may be involved in mechanisms underlying myasthenia gravis pathogenesis as well as may be potential biomarkers in MG patients diagnosis. However, considering the multifactorial, heterogenous and complex nature of this disease, validation on a larger study sample in further research is required before application into diagnostic practice.

Amino Acid Levels as Potential Biomarkers of Multiple Sclerosis in Elderly Patients: Preliminary Report.

BACKGROUND AND PURPOSE: Aging in multiple sclerosis is associated with both disease- and age-dependent neurodegeneration. Serum metabolomic profiling of amino acids seems to be a promising method for searching for biomarkers of neurodegenerative disorders. The aim of this study was to determine the profile of nonessential amino acids in the serum of elderly patients with secondary progressive multiple sclerosis (SPMS). METHODS: We used high-performance liquid chromatography to evaluate the serum concentrations of nonessential amino acids in subjects aged >65 years: six patients with SPMS and 20 control subjects (CS). RESULTS: The serine and alanine levels were significantly higher in SPMS patients than in CS, whereas the concentrations of aspartic acid, arginine, and cysteine were significantly lower in SPMS patients. These observations indicate that amino acids may be involved in SPMS neurodegeneration mechanisms. There were no significant differences in the serum concentrations of the other four amino acids investigated (glutamic acid, glycine, proline, and tyrosine) between patients with SPMS and CS. CONCLUSIONS: The preliminary results obtained in the study suggest that the metabolism of some amino acids is altered in patient with SPMS. We also conclude that amino acid profiling might be helpful in searching for putative biomarkers of central nervous system diseases. However, considering the multifactorial, heterogeneous, and complex nature of SPMS, further validation research involving larger study samples is required before applying these biomarkers in diagnostic practice.

Comparison of LC-MS and LC-DAD Methods of Detecting Abused Piperazine Designer Drugs.

Recreational use of piperazine designer drugs is a serious threat to human health. These compounds act on the body in a similar fashion to illegal drugs. They induce psychostimulatory effects as well as visual and auditory hallucinations to varying degrees. In many cases of poisoning and deaths, the presence of two or even several psychoactive substances have been demonstrated. Piperazine derivatives are often found in such mixtures and pose a great analytical problem during their identification. Additionally, some piperazine derivatives can be detected in biological material as a result of metabolic changes to related drugs. Therefore, it is necessary to correctly identify these compounds and ensure repeatability of determinations. This article presents a comparison of the methods used to detect abused piperazine designer drugs using liquid chromatography in combination with a diode-array detector (LC-DAD) or mass spectrometer (LC-MS). Each of methods can be used independently for determinations, obtaining reliable results in a short time of analysis. These methods can also complement each other, providing qualitative and quantitative confirmation of results. The proposed methods provide analytical confirmation of poisoning and may be helpful in toxicological diagnostics.

Amino acids levels as a potential biomarker in myasthenia gravis.

The search for new diagnostic and therapeutic approaches for myasthenia gravis (MG) is highly desirable. Therefore, the aim of the present study is to assess the profile of non-essential amino acids in the serum of MG patients. We evaluated the serum levels of non-essential amino acids in MG patients (n = 10) and control subjects (CS, n = 10) using high-performance liquid chromatography (HPLC) method and assuming a two-fold concentration difference between the groups as significant. Serum levels of aspartic acid and glutamic acid in MG patients were significantly higher than in CS. There were no significant differences in mean serum levels of glycine, proline, alanine, serine, cysteine, arginine and tyrosine between MG patients and CS. The results indicate the need for further research to assess the role of non-essential amino acids in MG. Moreover, our preliminary results suggest that the metabolism of some amino acids seems to be changed in patients with MG. Therefore, we conclude that amino acids profiling might be helpful in searching for putative biomarkers of the central nervous system diseases such as myasthenia gravis.

Rapid Targeted Method of Detecting Abused Piperazine Designer Drugs.

Piperazine derivatives belong to the popular psychostimulating compounds from the group of designer drugs. They are an alternative to illegal drugs such as ecstasy and amphetamines. They are being searched by consumers for recreational use due to their stimulating and hallucinogenic effects. Many NPS-related poisonings and deaths have been reported where piperazines have been found. However, a major problem is the potential lack of laboratory confirmation of the involvement of piperazine derivatives in the occurrence of poisoning. Although many methods have been published, piperazine derivatives are not always included in a routine analytical approach or targeted toxicological analysis. There is an increasing need to provide qualitative evidence for the presence of piperazine derivatives and to ensure reproducible quantification. This article describes a new rapid method of detecting piperazine derivatives in biological material, using LC-MS. All target analytes were separated in a 15 min run time and identified based on the precursor ion, at least two product ions, and the retention time. Stable isotopically labeled (SIL) internal standards: BZP-D7, mCPP-D8 and TFMPP-D4 were used for analysis, obtaining the highest level of confidence in the results. The proposed detection method provides the analytical confirmation of poisoning with piperazine designer drugs.

Selected Drug-Likeness Properties of 2-Arylidene-indan-1,3-dione Derivatives-Chemical Compounds with Potential Anti-Cancer Activity.

2-Arylidene-indan-1,3-done derivatives have very different properties, thanks to which they find various applications in science, medicine, and industry. Selected derivatives show antiviral, antibacterial, and anti-inflammatory activity. This paper presents a procedure for the synthesis of a series of indan-1,3-dione derivatives that present antiproliferative activity. The aim of the work was to develop a method of simple synthesis and purification, evaluate the fulfillment of the Lipinski's and Veber's rule, and determine the potential scope of application of the obtained series of compounds. The structure of the synthesized compounds was confirmed, and their lipophilicity was determined using experimental and computational methods. Their antiproliferative activity against selected cell lines was tested in accordance with the MTT protocol; the ability to bind to albumin was tested, and the parameters related to the toxicity of substances in silico were determined. The selected compounds which showed antiproliferative activity were strongly bound to albumin and, in most cases, met the Lipinski's and Veber's rule. Thus, the obtained results suggest that 2-arylidene-indan-1,3-done derivatives appear to be good candidates for drugs with a potential leading structure for further development.

Serum amino acid profiles in patients with mild cognitive impairment and in patients with mild dementia or moderate dementia.

Neurodegenerative disorders are one of the greatest global challenges for social and health care in the twenty-first century. Nowadays, determination of cerebrospinal fluid biomarkers for early diagnosis is served by a complex sample preparation procedure with limited diagnostic accuracy. Furthermore, neuroimaging methods are expensive, time-consuming and are not readily available for use as a complimentary and common screening method. Recently, researchers have shown an increased interest in the identification and characterization of new blood biomarkers of dementia to minimize the limitations associated with the current methods of biomarker determination. Amino acids play many important roles in the central nervous system, acting as neuromodulators, neurotransmitters and regulators of energy metabolism. The aim of this study was to evaluate if serum amino acid levels change along the continuum from no cognitive impairment to moderate dementia, and to identify putative biomarkers for early diagnosis of neurodegenerative diseases. Serum levels of 16 amino acids were determined in 3 groups of patients-22 with mild cognitive impairment, 45 with mild dementia and 28 with moderate dementia-by high-performance liquid chromatography (HPLC) with fluorescence detection using AccQ Tag column (Waters). The most exciting result is the significantly elevated concentration of arginine in patients with both stages of dementia as compared to mild cognitive impairment individuals. Recent accumulating evidence suggests the implication of changed arginine metabolism in the pathogenesis of neurodegenerative diseases. We conclude that amino acids profiling might be helpful in searching for biomarkers of neurogenerative diseases. In the present study, we discovered that arginine in plasma may have a putative diagnostic value for dementia.

Amino Acid Levels as Potential Biomarker of Elderly Patients with Dementia.

Dementia is a clinical syndrome characterized by cognitive impairment, in which there is disturbance of multiple higher cortical functions. The primary risk factor of dementia is old age, and due to significant changes in the worldwide demographic structure, the prevalence of cognitive impairment is increasing dramatically with aging populations in most countries. Alzheimer's disease is the predominant and leading cause of dementia. The aim of this study was to evaluate the modifications of amino acids that characterize the initial stages of dementia to help our understanding of the complex and multifactorial pathogenesis of neurodegenerative disorders. A total of 123 participants were divided into two groups: healthy elderly subjects and patients with mild or moderate dementia. The results of this study indicate that the serum levels of three amino acids were changed significantly in patients with dementia, in relation to the subjects without dementia. In particular, we observed differences in concentrations for serine, arginine and isoleucine (all of them were significantly increased in patients with dementia, compared with the control group). Our results suggest that the metabolisms of some amino acids seem be changed in patients with dementia. We conclude that amino acid profiling might be helpful for the better understanding of biochemical and metabolic changes related to the pathogenesis and progression of dementia. However, considering the multifactorial, heterogenous and complex nature of this disease, validation with a greater study sample in further research is required.

Comparison of Pteridine Normalization Methods in Urine for Detection of Bladder Cancer.

Pterin compounds belong to the group of biomarkers for which an increase in interest has been observed in recent years. Available literature data point to this group of compounds as potential biomarkers for cancer detection, although the biochemical justification for this claim is not yet fully understood. The aim of this study was to evaluate the usefulness of pterin compounds in the diagnosis of bladder cancer, with particular emphasis on the role of creatinine and the specific gravity of urine as factors for normalizing the concentration of pterin compounds in urine. The standardization of the concentration of pterin compounds to urine specific gravity allows the building of better classification models for screening patients with potential cancer of the bladder. Of the compounds that make up the pterin profile, isoxanthopterin appears to be a compound that can potentially be described as a biomarker of bladder cancer.

Amino acid profiling as a method of discovering biomarkers for diagnosis of neurodegenerative diseases.

The trend of growing population of 60+ years old people is visible in most of the highly developed European countries. Recently researchers have shown an increased interest in aging-associated diseases including neurological disorders. Neurodegenerative diseases are a very important clinical problem for several reasons. One of the key aspects are: frequency of occurrence as well as difficulties in the diagnosis, therapeutic problems and care of elderly patients. Furthermore, the very important point is the significant decrease of quality of life of untreated patients and late-stage diagnosis of the disease. It is crucial to develop a new, faster, high specificity and more sensitive diagnostic technology. Metabolomic profiling is a new, promising field of systems biology which may be applied in screening, diagnosis, disease typing and monitoring of treatment. It is a biochemical approach for biomarker discovery. Amino acids (AA) play very integral roles in the central nervous system as neurotransmitters, regulators of metabolism and neuromodulators. Research presented in this publication is focused on patients with Parkinson's disease, Alzheimer disease, and elderly patients. In all analyzed cases significant changes in the amino acid profile in patients comparing to healthy controls were observed. This study indicates potential of amino acid profiling as a method for diagnosis.

The metabolic profiles of pterin compounds as potential biomarkers of bladder cancer-Integration of analytical-based approach with biostatistical methodology.

Cancer disease is the second leading cause of death across the world. The analysis of potential biomarkers of cancer can be useful in cancer screening or cancer diagnosis, and may provide valuable information on the disease risk and progression. Pterin compounds have been studied as candidates of potential biomarkers as their elevated levels have been reported in various cancer diseases. The objective of the study was to compare the profiles of six pterin compounds in urine of 35 healthy subjects and 46 patients diagnosed of bladder cancer with the use of HPLC coupled with fluorimetric detection. The results of the chromatographic analysis together with biostatistical-based approach showed, that the concentrations of pterin compounds in bladder cancer patients were higher as compared to healthy individuals, and statistically significant differences between patients and controls were reported for xanthopterin and isoxanthopterin. Moreover, gender-specific analysis revealed, that the concentrations of pterins in the group of women reached higher values in comparison to men. For metabolites juxtaposed in pairs, namely xanthopterin and isoxanthopterin as well as for neopterin and biopterin, we found significant positive correlations in the group of both, patients and healthy individuals. We therefore conclude, that chromatographic analysis with simultaneous extensive biostatistical-based interpretation of the metabolite profiles may provide deeper understanding of the relationships between pterin metabolites. The results do not prejudge the possibility of using pterin compounds in the diagnosis of bladder tumors. However the results may have an impact on the study of bladder cancer biomarkers.

Least absolute shrinkage and selection operator and dimensionality reduction techniques in quantitative structure retention relationship modeling of retention in hydrophilic interaction liquid chromatography.

The objective of this study was to model the retention of nucleosides and pterins in hydrophilic interaction liquid chromatography (HILIC) via QSRR-based approach. Two home-made (Amino-P-C18, Amino-P-C10) and one commercial (IAM.PC.DD2) HILIC stationary phases were considered. Logarithm of retention factor at 5% of acetonitrile (logkACN) along with descriptors obtained for 16 nucleosides and 11 pterins were used to develop QSRR models. We used and compared the predictive performance of three regression techniques: partial least square (PLS), the least absolute shrinkage and selection operator (LASSO), and the LASSO followed by stepwise multiple linear regression. The highest predictive squared correlation coefficient (QLOOCV(2)) in PLS analysis was found for Amino-P-C10 (QLOOCV(2)=0.687) and IAM.PC.DD2 (QLOOCV(2)=0.506) and the lowest for IAM.PC.DD2 (QLOOCV(2)=-0.01). Much higher values were obtained for the LASSO model. The QLOOCV(2) equaled 0.9 for Amino-P-C10, 0.66 for IAM.PC.DD2 and 0.59 for Amino-P-C18. The combination of LASSO with stepwise regression provided models with comparable predictive performance as the LASSO, however with possibility of calculating the standard error of estimates. The use of LASSO itself and in combination with classical stepwise regression may offer greater stability of the developed models thanks to more smooth change of coefficients and reduced susceptibility towards chance correlation. Application of QSRR-based approach, along with the computational methods proposed in this work, may offer a useful approach in the modeling of retention of nucleoside and pterin compounds in HILIC.

Determination of pterins in urine by HPLC with UV and fluorescent detection using different types of chromatographic stationary phases (HILIC, RP C8, RP C18).

Pterins are a class of potential cancer biomarkers. New methods involving hydrophilic interaction liquid chromatography (HILIC) and reversed phase (RP) high-performance liquid chromatography have been developed for analysis of eight pterin compounds: 6,7-dimethylpterin, pterin, 6-OH-methylpterin, biopterin, isoxanthopterin, neopterin, xanthopterin, and pterin-6-carboxylic acid. The effect of mobile phase composition, buffer type, pH and concentration on retention using HILIC, C8 and C18 RP stationary phases were examined. Separation of pterins on RP and HILIC stationary phase was performed and optimized. Eight pterins were successfully separated on HILIC Luna diol-bonded phases, Aquasil C18 RP column and LiChrospher C8 RP column. Determination and separation of the pterins from urine samples were performed on HILIC Luna and LiChrospher C8 RP columns which were chosen as the most appropriate ones. Finally, LiChrospher C8 RP column with fluorescence detection was selected for further validation of the method. The optimum chromatographic condition was mobile phase methanol (A)/phosphoric buffer pH 7, 10mM (B), isocratic elution 0-15min 5% A flow=0.5ml/min 15-17min. 5% A, flow=0.5-1ml/min the linearity (R(2)>0.997) and retention time repeatability (RSD%<1) were at satisfactory level. The precision of peak areas expressed as RSD in % was between 0.55 and 14. Pterins detection limits varied from 0.041ng/ml to 2.9ng/ml. Finally, HPLC method was used for the analysis of pterins in urine samples with two different oxidation procedures. Concentration levels of pterin compounds in bladder cancer patients and healthy subjects were compared.

Metabolic profiling of pteridines for determination of potential biomarkers in cancer diseases.

Cancer disease is the second leading cause of death in the world. Epidemiology data indicate that early diagnosis of a tumour increases a patient's chance of recovery. Biomarkers are effective instruments which can potentially lead to precancer screening or precancer diagnosis and may provide useful information on the cancer type and the disease's stage of progression. The analysis of new biomarkers for cancer is currently a popular area of study in clinical and cancer research. Pteridines are a class of potential cancer biomarkers. The monitoring levels of pteridines may have prospective value for controlling the course of the malignant process. This review describes the functional employment of pteridines, as biomarkers, in cancer diagnosis. It also contains the description of application of analytical techniques such as high-performance liquid chromatography (HPLC) and capillary electrophoresis (CE) used for pteridine analysis.

Metabolomics in urogenital cancer.

Although in recent decades the development of many drugs against cancer has been witnessed, the morbidity and mortality for the most prevalent urogenital cancer have not been significantly reduced. A key task in cancer medicine is to detect the disease as early as possible. In order to achieve this, many new technologies have been developed for cancer biomarker discovery. Monitoring fluctuations of certain metabolite levels in body fluids, such as urine, has become an important way to detect early stages in carcinogenesis. Moreover metabolomic approaches are likely to be used to screen for potential diagnostic and prognostic biomarkers of urogenital cancer. In future work, these potential biomarkers should be further validated with a large enough patient cohort to achieve earlier diagnosis not only of urogenital cancer, but also other malignancies. Moreover, the improvement of patient prognosis will be another aim of such investigations. This novel metabolomic approach has the potential to provide more information about the pathophysiological status of an organism and distinguish precancerous and cancerous stages.