• MeSH
• Molecular Diagnostic Techniques MeSH
• Neoplasms * diagnosis   genetics   MeSH
• Gene Expression Profiling MeSH

• Conspectus
• Biochemie. Molekulární biologie. Biofyzika
• NML Fields
• molekulární biologie, molekulární medicína
• onkologie
• NML Publication type
• kolektivní monografie

• MeSH
• Molecular Biology MeSH
• Publication type
• Laboratory Manual MeSH
• Handbook MeSH

• Conspectus
• Biochemie. Molekulární biologie. Biofyzika
• NML Fields
• biologie

Correct assessment of tissue histopathology is a necessary prerequisite for any clinical diagnosis. Nowadays, classical methods of histochemistry and immunohistochemistry are complemented by various techniques adopted from molecular biology and bioanalytical chemistry. Mass spectrometry profiling or imaging offered a new level of tissue visualization in the last decade, revealing hidden patterns of tissue molecular organization. It can be adapted to diagnostic purposes to improve decisions on complex and morphologically not apparent diagnoses. In this work, we successfully combined tissue profiling by mass spectrometry with analysis by artificial neural networks to classify normal and diseased liver and kidney tissues in a mouse model of primary hyperoxaluria type 1. Lack of the liver l-alanine:glyoxylate aminotransferase catalyzing conversion of l-alanine and glyoxylate to pyruvate and glycine causes accumulation of oxalate salts in various tissues, especially urinary system, resulting in compromised renal function and finally end stage renal disease. As the accumulation of oxalate salts alters chemical composition of affected tissues, it makes it available for examination by bioanalytical methods. We demonstrated that the direct tissue MALDI-TOF MS combined with neural computing offers an efficient tool for diagnosis of primary hyperoxaluria type I and potentially for other metabolic disorders altering chemical composition of tissues.

• Keywords
• MALDI-TOF mass spectrometry,
• MeSH
• Liver pathology   MeSH
• Kidney pathology   MeSH
• Mice MeSH
• Neural Networks, Computer * MeSH
• Hyperoxaluria, Primary * diagnosis   pathology   MeSH
• Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization * statistics & numerical data   MeSH
• Transaminases deficiency   MeSH
• Animals MeSH
• Check Tag
• Mice MeSH
• Animals MeSH
• Publication type
• Research Support, Non-U.S. Gov't MeSH

• Publication type
• Meeting Abstract MeSH

Coronary artery disease is one of the most frequent causes of morbidity and mortality worldwide. It is even more prevalent in patients with type 2 diabetes mellitus who suffer from obesity and increased accumulation of epicardial fat with a possible contributing role in the development of coronary artery disease. We performed an MS-based lipidomic analysis of subcutaneous and epicardial adipose tissue in 23 patients with coronary artery disease stratified for the presence/absence of type 2 diabetes mellitus and a control group of 13 subjects aiming at identification of factors from epicardial fat contributing to the development of coronary artery disease. The samples of adipose tissues were obtained during elective cardiac surgery. They were extracted and analyzed with and without previous triacylglycerols separation by high-pressure liquid chromatography-mass spectrometry (HPLC-MS). Multivariate and univariate analyses were performed. Lipidomics data were correlated with biochemical parameters. We identified multiple changes in monoacylglycerols, diacylglycerols, triacylglycerols, glycerophosphatidylserines, glycerophosphatidylethanolamines, glycerophosphatidylcholines, ceramides, sphingomyelins, and derivatives of cholesterol. Observed changes included molecules with fatty acids with odd (15:0, 15:1, 17:0, 17:1) and even (10:0, 12:0, 14:0, 16:0, 16:1, 18:0, 18:1, 18:2, 20:4, 20:1, 22:0) fatty acids in both types of adipose tissue. More pronounced changes were detected in epicardial adipose tissue compared to subcutaneous adipose tissue of patients with coronary artery disease and type 2 diabetes. Lipidomic analysis of subcutaneous and epicardial adipose tissue revealed different profiles for patients with coronary artery disease and type 2 diabetes, which might be related to coronary artery disease and the presence of type 2 diabetes.

• MeSH
• Diabetes Mellitus, Type 2 * MeSH
• Humans MeSH
• Lipids MeSH
• Coronary Artery Disease * MeSH
• Pericardium MeSH
• Subcutaneous Fat MeSH
• Adipose Tissue MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH

Gene expression microarrays are being used to develop new prognostic and predictive tests for breast cancer, and might be used at the same time to confirm oestrogen-receptor status and ERBB2 status. Our goal was to establish a new method to assign oestrogen receptor and ERBB2-receptor status to breast carcinoma based on mRNA expression measured using Affymetrix U133A gene-expression profiling. METHODS: We used gene expression data of 495 breast cancer samples to assess the correlation between oestrogen receptor (ESR1) and ERBB2 mRNA and clinical status of these genes (as established by immunohistochemical [IHC] or fluorescence in-situ hybridisation [FISH], or both). Data from 195 fine-needle aspiration (FNA) samples were used to define mRNA cutoff values that assign receptor status. We assessed the accuracy of these cutoffs in two independent datasets: 123 FNA samples and 177 tissue samples (ie, resected or core-needle biopsied tissues). Profiling was done at two institutions by use of the same platform (Affymetrix U133A GeneChip). All data were uniformly normalised with dCHIP software. FINDINGS: ESR1 and ERBB2 mRNA levels correlated closely with routine measurements for receptor status in all three datasets. Spearman's correlation coefficients ranged from 0.62 to 0.77. An ESR1 mRNA cutoff value of 500 identified oestrogen-receptor-positive status with an overall accuracy of 90% (training set), 88% (first validation set), and 96% (second validation set). An ERBB2 mRNA threshold of 1150 identified ERBB2-positive status with the overall accuracy of 93% (training set), 89% (first validation set), and 90% (second validation set). Reproducibility of mRNA measurements in 34 replicate experiments was high (correlation coefficient 0.975 for ESR1, 0.984 for ERBB2). INTERPRETATION: Amounts of ESR1 and ERBB2 mRNA as measured by the Affymetrix GeneChip reliably and reproducibly establish oestrogen-receptor status and ERBB2 status, respectively.

• MeSH
• Genes, erbB-2 genetics   MeSH
• Humans MeSH
• RNA, Messenger analysis   MeSH
• Breast Neoplasms genetics   MeSH
• Receptors, Estrogen biosynthesis   genetics   MeSH
• Gene Expression Profiling MeSH
• Check Tag
• Humans MeSH

OBJECTIVE: Interest in metabolites produced by adipose tissue has increased substantially in the past several decades. Previously regarded as an inert energy storage depot, adipose tissue is now viewed as a complex metabolically active organ with considerable impact on human health. The emerging field of mass spectrometry-based metabolomics presents a powerful tool for the study of processes in complex biological matrices including adipose tissue. RESULTS: A large number of structurally distinct metabolites can be analyzed to facilitate the investigation of differences between physiological and pathophysiological metabolic profiles associated with adipose tissue. Understanding the molecular basis of adipose tissue regulation can thereby provide insight into the monitoring of obesity-related metabolic disorders and lead to the development of novel diagnostic and prognostic biomarkers. CONCLUSIONS: This review provides the current state of knowledge, recent progress, and critical evaluation of metabolomics approaches in the context of white adipose tissue and obesity. An overview of basic principles and resources describing individual groups of metabolites analyzed in white adipose tissue and biological fluids is given. The focus is on metabolites that can serve as reliable biomarkers indicative of metabolic alterations associated with obesity.

• MeSH
• Adipose Tissue, White metabolism   MeSH
• Humans MeSH
• Metabolome genetics   MeSH
• Obesity metabolism   MeSH
• Check Tag
• Humans MeSH
• Male MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Review MeSH

Analysis of bioactive lipids in adipose tissue could lead to better understanding of the pathogenesis of obesity and its complications. However, current MS methods are limited by a high content of triacylglycerols (TAGs), which markedly surpasses the amount of other lipids and suppresses their ionization. The aim of our study was thus to optimize the preanalytical phase of lipid analysis in adipose tissue, focusing in particular on less-abundant lipids. Next, the optimized method was used to describe the differences between epicardial and subcutaneous adipose tissues obtained from patients undergoing cardiac surgery. Lipids were extracted using a modified Folch method with subsequent detachment of TAGs by thin layer chromatography (TLC). The extracts with/without TAGs were analyzed by tandem LC/MS. The repeatability of the presented method expressed by the median of the coefficients of variation was 12/5% for analysis with/without TAGs separation, respectively. The difference in the relative abundance of TAGs gained with/without TLC was, on average, 19% and did not reach significance (p value > 0.05) for any identified TAG. The novel preanalytical step allowed us to detect 37 lipids, which could not have been detected without TAG separation, because their signal to noise ratio is <5 in current methods of untargeted lipidomics. These lipids belong predominately to ceramides, glycerophosphatidylserines, glycerophosphatidylinsitols, sphingomyelins, glycerophosphatidylcholines, glycerophosphatidylethanolamines, diacylglycerols. The two adipose tissue depots differed mainly in the following lipid classes: glycerophosphatidylcholines, glycerophosphatidylinositols, glycerophosphatidylethanolamine, and sphingomyelins. Moreover, other major lipids showed distinctly different distributions between the two adipose tissues. Among these, the changes in TAGs were the most striking, which correspond to previously published data describing the differences between omental and subcutaneous adipose tissue. Implementation of the TLC step for the elimination of TAGs was crucial for enhancing the MS detection limit of minor lipids in adipose tissue. The differences between the overall lipid profiles of subcutaneous and epicardial tissue reflect their different functions arising from their location.

• MeSH
• Chromatography, Liquid methods   MeSH
• Middle Aged MeSH
• Humans MeSH
• Lipids analysis   MeSH
• Intra-Abdominal Fat chemistry   MeSH
• Pericardium physiology   MeSH
• Subcutaneous Fat chemistry   MeSH
• Reproducibility of Results MeSH
• Aged MeSH
• Tandem Mass Spectrometry methods   MeSH
• Check Tag
• Middle Aged MeSH
• Humans MeSH
• Aged MeSH
• Publication type
• Journal Article MeSH

BACKGROUND/AIM: Expression profiling was performed to delineate and characterize the impact of malignancy by comparing tissues from three sites of head and neck cancer of each patient, also determining interindividual variability. MATERIALS AND METHODS: Genome-wide analysis was carried out covering the expression of 25,832 genes with quantification for each site of seven patients with tonsillar or oropharyngeal squamous cell carcinoma. Immunohistochemical analysis was performed for adhesion/growth-regulatory galectins, three pro-inflammatory chemo- and cytokines and keratins. RESULTS: Up- and down-regulation was found for 281 (tumor vs. normal) and 276 genes (transition zone vs. normal), respectively. The profile of the transition zone had its own features, with similarity to the tumor. Galectins were affected in a network manner, with differential regulation and interindividual variability between patients, also true for keratins and the chemo- and cytokines. CONCLUSION: These results underline special features at each site of specimen origin as well as the importance of analyzing galectins as a network and of defining the expression status of the individual patient prior to reaching clinically relevant conclusions.

• MeSH
• Cytokines genetics   MeSH
• Epithelium metabolism   MeSH
• Galectins genetics   metabolism   MeSH
• Genome, Human MeSH
• Keratins genetics   metabolism   MeSH
• Middle Aged MeSH
• Humans MeSH
• Oropharyngeal Neoplasms genetics   metabolism   MeSH
• Aged MeSH
• Carcinoma, Squamous Cell genetics   metabolism   MeSH
• Gene Expression Profiling MeSH
• Check Tag
• Middle Aged MeSH
• Humans MeSH
• Male MeSH
• Aged MeSH
• Female MeSH
• Publication type
• Journal Article MeSH

The aim of the present study was to evaluate the expression profile of genes potentially related to metabolic complications of obesity in the whole adipose tissue and isolated adipocytes from subcutaneous (SAT) and visceral adipose tissue (VAT) from 12 non-diabetic obese women and 12 lean women. Real-time polymerase chain reaction was used for expression analysis of 41 genes of interest and two housekeeping genes. We found increased expression of specific proinflammatory and adipogenic genes and reduced expression of specific lipogenic and insulin signaling pathway genes in obese relative to lean women with no preferable localization in SAT or VAT depot. The gene expression significantly differed between adipocytes and adipose tissue but both contributed to the proinflammatory profile in obesity. We conclude that both SAT and VAT exhibit alterations in the expression of specific genes possibly contributing to proinflammatory and insulin resistance state and consequently to metabolic complications of obesity.

• MeSH
• Adult MeSH
• Financing, Organized MeSH
• Middle Aged MeSH
• Humans MeSH
• Microarray Analysis MeSH
• Intra-Abdominal Fat physiology   MeSH
• Obesity metabolism   physiopathology   MeSH
• Subcutaneous Fat physiology   MeSH
• Gene Expression Profiling MeSH
• Adipocytes cytology   physiology   MeSH
• Check Tag
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Female MeSH