Identification of organic acids as potential biomarkers in the urine of autistic children using gas chromatography/mass spectrometry.

There is a need to identify metabolic phenotypes in autism as they might each require unique approaches to prevention. Biological markers can help define autism subtypes and reveal potential therapeutic targets. The aim of the study was to identify alterations of small molecular weight compounds and to find potential biomarkers. Gas chromatography/mass spectrometry was employed to evaluate major metabolic changes in low molecular weight urine metabolites of 14 children with autism spectrum disorders vs. 10 non-autistic subjects. The results prove the usefulness of an identified set of 21 endogenous compounds (including 14 organic acids), whose levels are changed in diseased children. Gas chromatography/mass spectrometry method combined with multivariate statistical analysis techniques provide an efficient way of depicting metabolic perturbations of diseases, and may potentially be applicable as a novel strategy for the noninvasive diagnosis and treatment of autism.

Liquid chromatography tandem mass spectrometry study of urinary nucleosides as potential cancer markers.

The aim of this work was a comprehensive analysis of metabolite profiles of nucleosides from biological samples obtained from patients with urogenital cancer disease as well as an interpretation of cancer-related patterns of the analyzed profiles. In our study we proposed a targeted approach that was focused on the simultaneous determination of twelve nucleosides from over a hundred urine samples. For analytes' quantification high performance liquid chromatography technique hyphenated with tripple quadrupole mass spectrometer was applied. The developed method was validated in terms of linearity, precision, accuracy as well as in terms of limit of quantification and limit of detection. The obtained, normalized data set was analyzed using univariate statistical analysis. The achieved results revealed statistically significant (p<0.05) differences between levels of five nucleosides determined in urine samples from cancer patients and healthy volunteers, namely: 6-methyladenosine, inosine, N-2-methylguanosine, 3-methyluridine and N,N-dimethylguanosine. Basing on the putative markers we built the discrimination models using partial least squares discriminant analysis as well as K-nearest neighbor method. The sensitivity and specificity of the markers calculated from the obtained models were in the range of 61.9-88.89% and 27.78-50%, respectively. The proposed procedure can be considered as a holistic approach for metabolites' analysis and includes clinical, analytical and bioinformatics sections.

Advanced assessment of the endogenous hormone level as a potential biomarker of the urogenital tract cancer.

The evaluation of the relationships between the hormones involved in the urogenital tract cancer, including bladder, kidney, prostate, and testis, could prove important from diagnostic point of view. The determination of the steroid hormone profiles may likely provide a biomarker for discrimination of hormone-related diseases, as well as for differentiation of healthy volunteers from patients with cancer. The aim of the study was to demonstrate the changes in the steroid hormone profile (comprising corticosteroids, androgens and progesterone) in the urine of patients with the urogenital tract cancer versus urine from healthy subjects. A reliable analytical method based on liquid chromatography coupled with mass spectrometry was successfully applied to determine the urinary profiles of 6 endogenous steroids: cortisol, cortisone, corticosterone, testosterone, epitestosterone and progesterone for 92 urogenital tract cancer patients and 100 healthy controls. The obtained data was further evaluated by in-depth chemometric analysis, including the applied standardized Kennard-Stone's algorithm to pre-process the data. Mann-Whitney U test revealed statistically significant (p <0.05) differences in concentration of androgens and progesterone in the case of bladder cancer for male and female population, for male also cortisol and cortisone levels were significantly increased. PCA analysis proved a reasonable trend for differentiating healthy and cancer patients, and finally, applying PLS-DA model we were able to correctly classify 80.56%of cancer patients. Our results indicate that steroid hormone profile determination could be a promising approach for early diagnosis of urogenital tract cancer. However our preliminary results require an extension both in patient number and steroid profile.

Steroid profiles as potential biomarkers in patients with urogenital tract cancer for diagnostic investigations analyzed by liquid chromatography coupled to mass spectrometry.

Large discrepancy remains for the hormone-responsible cancers with regards to the conditions generating the optimal opportunity for cancerogenesis. In the research, altered steroid profiles were observed in patients with urogenital tract cancer diseases, namely bladder, kidney, prostate and testis ones. The presented steroid profiles from 154 subjects, including 77 urogenital tract cancer patient and 77 healthy controls were determined by liquid chromatography coupled to mass spectrometry method. Because the original experimental data obtained as a result of analytical experiment in order to interpret them in better way required the appropriate pre-treatment, the data were standardized by scaling and centering. In order to determine which samples form a collection for a high-capacity predictive model, Kennard-Stone's algorithm was used. A principal component analysis of preprocessed data provided better consistency of the steroid profiles with health status of subjects than PCA profiles without data preprocessing and showed a tendency to separate clusters of cancer patients from healthy subjects. The discriminant analysis was also performed and the percent of correct classification of cancer patients and control group was calculated. Finally, detailed studies examined the role of steroid profiles measured in urine, and considered as potential biomarkers related to urogenital cancer and associated renal dysfunctions.

The osteopontin tissue level as a breast cancer biomarker in females after mastectomy measured by the capillary gel electrophoresis technique.

A new diagnostic and prognostic biomarker may be of value in the diagnostic panel, especially among cancer diseases. The aim of the study was to evaluate the osteopontin (OPN) level measurable in the tumour tissue in females with diagnosed breast cancer after mastectomy, and to confirm its suitability to serve as a prognostic biomarker of the cancer.The OPN tissue levels and the classical risk factors were determined in twelve females. Tissue samples were collected and analysed by the capillary gel electrophoresis technique after previous appropriate preparation of the samples. A comparison between the OPN average values in the tissue of healthy versus cancer patients after mastectomy was performed using statistical univariate tests (ANOVA, t-test) and multivariate analysis (principal component analysis, PCA). The results demonstrate that the median values of the OPN in the tumour centre cancer tissue (10.940 µg/g; within the range of 3.772-23.648) are significantly higher compared to healthy cells (5.173 µg/g; within the range of 0.838- 17.583). Moreover, the increased tissue OPN level was correlated with the cancer stage.In this study osteopontin is presented as a possible candidate for a breast cancer biomarker. Further research is needed to obtain information on cancer signalling by means of the OPN threshold, and indication of its advanced stage.

New supervised alignment method as a preprocessing tool for chromatographic data in metabolomic studies.

The purpose of this work was to develop a new aligning algorithm called supervised alignment and to compare its performance with the correlation optimized warping. The supervised alignment is based on a "supervised" selection of a few common peaks presented on each chromatogram. The selected peaks are aligned based on a difference in the retention time of the selected analytes in the sample and the reference chromatogram. The retention times of the fragments between known peaks are subsequently linearly interpolated. The performance of the proposed algorithm has been tested on a series of simulated and experimental chromatograms. The simulated chromatograms comprised analytes with a systematic or random retention time shifts. The experimental chromatographic (RP-HPLC) data have been obtained during the analysis of nucleosides from 208 urine samples and consists of both the systematic and random displacements. All the data sets have been aligned using the correlation optimized warping and the supervised alignment. The time required to complete the alignment, the overall complexity of both algorithms, and its performance measured by the average correlation coefficients are compared to assess performance of tested methods. In the case of systematic shifts, both methods lead to the successful alignment. However, for random shifts, the correlation optimized warping in comparison to the supervised alignment requires more time (few hours versus few minutes) and the quality of the alignment described as correlation coefficient of the newly aligned matrix is worse 0.8593 versus 0.9629. For the experimental dataset supervised alignment successfully aligns 208 samples using 10 prior identified peaks. The knowledge about retention times of few analytes' in the data sets is necessary to perform the supervised alignment for both systematic and random shifts. The supervised alignment method is faster, more effective and simpler preprocessing method than the correlation optimized warping method and can be applied to the chromatographic and electrophoretic data sets.

The state-of-the-art determination of urinary nucleosides using chromatographic techniques "hyphenated" with advanced bioinformatic methods.

Over the last decade metabolomics has gained increasing popularity and significance in life sciences. Together with genomics, transcriptomics and proteomics, metabolomics provides additional information on specific reactions occurring in humans, allowing us to understand some of the metabolic pathways in pathological processes. Abnormal levels of such metabolites as nucleosides in the urine of cancer patients (abnormal in relation to the levels observed in healthy volunteers) seem to be an original potential diagnostic marker of carcinogenesis. However, the expectations regarding the diagnostic value of nucleosides may only be justified once an appropriate analytical procedure has been applied for their determination. The achievement of good specificity, sensitivity and reproducibility of the analysis depends on the right choice of the phases (e.g. sample pretreatment procedure), the analytical technique and the bioinformatic approach. Improving the techniques and methods applied implies greater interest in exploration of reliable diagnostic markers. This review covers the last 11 years of determination of urinary nucleosides conducted with the use of high-performance liquid chromatography in conjunction with various types of detection, sample pretreatment methods as well as bioinformatic data processing procedures.

Metabolomic approach for determination of urinary nucleosides as potential tumor markers using electromigration techniques.

In the postgenome-sequencing era, several large projects have been running recently. Proteomics and other analysis or structural biology are the most active today. Since the late 1990 s, metabolomics has been gaining importance in systems biology, as it provides real-world end points that complement and help in the interpretation of genomic and proteomic data. Comprehensive information about the level changes of numerous metabolites present in the analyzed samples is essential in metabolomic studies. Therefore, the applied analytical techniques must be suitable for the simultaneous analysis of a diverse range of low-molecular-mass endogenous metabolites such as nucleosides at various concentrations and in different matrices, in particular, in urine and serum. In the view of metabolomic study, this domain is obviously significant to understand specific humans' reactions and it can be perceived as a diagnostic and predictive tool in pathological reactions. Since the term "metabolom" has occurred in common scientific use, there have been many publications about possible ways of analysis of nucleosides as metabolites of either oxidative DNA damage or RNA's turnover that are used as the potential tumor markers. Besides, the availability of fast, reproducible and easy to apply analytical techniques that would allow the identification of a large number of metabolites is highly desirable since they may provide detailed information about the progression of a pathological process. This paper, which describes the most relevant electromigration techniques, covers the period starting from the review of Karl H. Schram (Mass Spectrom. Rev. 1998, 17, 131-251) up to the beginning of 2009.