• MeSH
• Genome-Wide Association Study MeSH
• Cholesteatoma, Middle Ear MeSH
• Gene Expression MeSH
• Prospective Studies MeSH
• Oligonucleotide Array Sequence Analysis MeSH

• Conspectus
• Patologie. Klinická medicína
• NML Fields
• otorinolaryngologie
• genetika, lékařská genetika
• NML Publication type
• studie

Cíl práce: Zhodnotit přítomnost exprese genů PAX5 a Shb ve tkáni povrchových uroteliálních karcinomů močového měchýře, posoudit její korelaci s patologií genu p53 a uvážit prognostický význam jednotlivých faktorů. Pacienti a metodika: Do studie bylo zahrnuto 61 pacientů s histologicky prokázaným povrchovým uroteliálním karcinomem močového měchýře. Exprese mRNA genů PAX5 a Shb ve tkáni nádoru byla detekována pomocí reverzní polymerázové řetězové reakce (RT-PCR) a výsledek byl vyjádřen semikvantitativně. Přítomnost mutací p53 byla zachycena pomocí SSCP (single strand conformation polymorphism) a potvrzena sekvenováním. K imunohistochemickému vyšetření p53 byla použita protilátka DO1, k vyjádření výsledku bylo použito semikvantitativní hodnocení pomocí HSCORE (HS). Kontrolní skupinu pro posouzení PAX5 a Shb exprese tvořilo 8 mužů, u kterých byl vzorek urotelu odebrán během operace pro benigní hyperplazií prostaty. Výsledky: Přítomnost exprese PAX5 a Shb byla prokázána u 50, respektive 52 pacientů s uroteliálním nádorem, ale u žádného z kontrolní skupiny. Mutace p53 byla zachycena u jediného pacienta s tumorem pTaG2 a byla lokalizována v exonu 5 (delece prolinu 128). Jaderná imunoreaktivita p53 byla přítomna u většiny pacientů, při použití prahové hodnoty HS 200 mělo 56,9 % nemocných pozitivní nález. Kvantita imunohistochemické pozitivity p53 nekorelovala s kvantitou exprese PAX5. Při použití prahových hodnot HS 200 pro p53 a 0,2 pro PAX5 mělo z 8 progredujících pacientů 7 nadprahovou hodnotu HS a 4 nadprahovou hodnotu PAX5. Závěr: Exprese genu PAX5 je častým nálezem u povrchových uroteliálních karcinomů močového měchýře.

The objective of the work: To evaluate the presence of the PAX5 and Shb genes expression in the tissue of superficial urotelial urinary bladder cancers, to judge its correlation with the p53 gene pathology and to consider the prognostic value of individual factors. Patients and Method: 61 patients with histologically proven superficial urotelial bladder cancer were included into the study. The mRNA expression of PAX5 and Shb genes in the cancer tissue was detected by the reverse polymerase chain reaction (RT- PCR) and the result was expressed semiquantitatively. The presence of p53 mutations was recorded by SSCP (single strand conformation polymorphism) and confirmed by sequening. The immunohistological examination of p53 was made by using DO1 antibody and the result was expressed using semiquantitative evaluation by HSCORE (HS). 8 men created the control group for PAX5 and Shb expression evaluation. Their urotel sample was withdrawn during the operation of benign prostate hyperplasia. Results: The presence of PAX5 and Shb expression was proven in 50, let us say in 52 patients with urotelial cancer, but it was not proven in anybody of the control group. p53 mutation was recorded in one patient with pTaG2 tumour and it was localised in 5 exon (proline 128 deletion). Nuclear immunoreactivity of p53 was present in the majority of patients, 56,9% of patients had positive finding using the threshold value HS 200. The quantity of p53 immunohistochemical positivity did not correlate with the quantity of PAX5 expression. Using the threshold values of HS 200 for p53 and 0,2 for PAX5 the 7 of 8 progressing patients had supra-threshold HS value and 4 of them had supra-threshold PAX5 value. Conclusion: The PAX5 gene expression is an often finding in superficial urotelial urinary bladder cancers.

• MeSH
• Research Support as Topic MeSH
• Genes, p53 genetics   MeSH
• Humans MeSH
• Mutation genetics   MeSH
• Urinary Bladder Neoplasms diagnosis   genetics   MeSH
• Gene Expression Profiling methods   utilization   MeSH
• Check Tag
• Humans MeSH

Moderní přístupy k onkologické diagnostice a léčbě jsou dnes již neodmyslitelně spjaty s využíváním nejnovějších poznatků biomedicínských věd. Jedním z hlavních trendů molekulární medicíny je rozvoj metodik umožňujících paralelní sledování exprese velkého počtu genů nebo proteinů – tzv. funkční genomika a proteomika. Tyto techniky umožňují identifikovat diferenciální genovou expresi, tj. nalézt rozdíly mezi expresí genů u dvou či více vzorků buněk nebo tkání různých typů (např. normálních a nádorových buněk) nebo kultivovaných za různých podmínek. Tak přispívají k objasnění mechanizmů maligního zvratu, mohou sloužit jako východisko pro rozvoj cílené protinádorové genové terapie, sledování odpovědi pacienta na léčbu a predikci dalšího vývoje onemocnění. Genomické metody se v posledních letech rychle rozvíjely – od diferenciální a subtraktivní hybridizace a diferenciálního displaye až po sériovou analýzu genové exprese a DNA čipy (microarrays). Uplatňují se také tkáňové a proteinové čipy a další proteomické přístupy. V současné době jsou stále více využívány DNA čipy umožňující detekci exprese celého lidského genomu, které nabízejí značné možnosti pro onkologický výzkum i klinickou praxi. U mnoha typů nádorů byly pomocí čipů nalezeny nové markery nádorového růstu a progrese onemocnění, z nichž některé jsou již úspěšně využívány v klinické praxi pro optimalizaci léčby omezující zátěž pacienta (např. u nádorů prsu).

Contemporary approaches to diagnostics and therapy in oncology are nowadays tightly coupled to novel findings of biomedical science. One of the main trends in molecular medicine is the development of methodologies enabling parallel monitoring of expression of large quantities of genes or proteins - so called functional genomics and proteomics. These techniques allow determination of differential gene expression, i.e. evaluation of differences in gene expression between two or more cell or tissue samples of different types (e.g. normal or cancer cells) or coming from different culture conditions. These approaches help in elucidating causes of malignant transformation and can serve as a base for development of targeted anticancer gene therapy, monitoring of patient response to treatment and prediction of further disease development. Genomic approaches have undergone rapid development in the last few years - from differential and subtractive hybridisation through differential display all the way to serial analysis of gene expression and DNA microarrays. Besides that, tissue and protein arrays and other proteomic approaches have been also used. Currently DNA microarrays covering expression of the whole human genome, having significant potential in oncological research and clinical praxis, have been used more and more frequently. Many new tumor growth and progression markers were found using such approaches. Some of these markers have been already successfully used in clinical practice (e.g. in breast cancer) for therapy optimisation and minimisation of patient discomfort.

• MeSH
• Protein Array Analysis methods   instrumentation   utilization   MeSH
• DNA analysis   genetics   MeSH
• Gene Expression genetics   MeSH
• Research Support as Topic MeSH
• In Situ Hybridization, Fluorescence methods   MeSH
• Humans MeSH
• Neoplasms diagnosis   genetics   therapy   MeSH
• Review Literature as Topic MeSH
• Prognosis MeSH
• RNA analysis   genetics   MeSH
• Check Tag
• Humans MeSH

Background: Microarray technologies are used to measure the simultaneous expression of a certain set of thousands of genes based on ribonucleic acid (RNA) obtained from a biological sample. We are interested in several statistical analyses such as 1) finding differentially expressed genes between or among several experimental groups, 2) finding a small number of genes allowing for the correct classification of a sample in a certain group, and 3) finding relations among genes. Objectives: Gene expression data are high dimensional, and this fact complicates their analysis because we are able to perform only a few samples (e.g. the peripheral blood from a limited number of patients) for a certain set of thousands of genes. The main purpose of this paper is to present the shrinkage estimator and show its application in different statistical analyses. Methods: The shrinkage approach relates to the shift of a certain value of a classic estimator towards a certain value of a specified target estimator. More precisely, the shrinkage estimator is the weighted average of the classic estimator and the target estimator. Results: The benefit of the shrinkage estimator is that it improves the mean squared error (MSE) as compared to a classic estimator. The MSE combines the measure of an estimator’s bias away from its true unknown value and the measure of the estimator’s variability. The shrinkage estimator is a biased estimator but has a lower variability. Conclusions: The shrinkage estimator can be considered as a promising estimator for analyzing high dimensional gene expression data.

• MeSH
• Gene Expression * genetics   MeSH
• Humans MeSH
• Microarray Analysis * methods   statistics & numerical data   MeSH
• RNA * genetics   MeSH
• Models, Statistical MeSH
• Check Tag
• Humans MeSH
• Publication type
• Research Support, Non-U.S. Gov't MeSH

OBJECTIVES: MicroRNAs (miRNAs) play key roles in a wide variety of normal and pathological cellular processes. A number of studies identified hematopoietic-specific miRNAs that are necessary for correct function of blood cells. Out of our microarray data, we chose 13 miRNAs that showed differential expression in peripheral blood cells (miR-15b, miR-16, miR-24, miR-30c, miR-106b, miR-142-3p, miR-142-5p, miR-150, miR-155, miR-181, miR-223, miR-342, and miR-451) and examined their expression in separated hematopoietic cell lineages. METHODS: Using quantitative real-time polymerase chain reaction, we measured relative expression of the miRNAs in fractions of reticulocytes, platelets, granulocytes, monocytes, B- and T-lymphocytes as well as in several hematopoietic cell lines. RESULTS: We observed that miR-16 and miR-142-3p were highly expressed in all native cell lineages, miR-451 reached the maximal expression in reticulocytes, miR-223 in platelets, granulocytes and monocytes, and miR-150 in B- and T-lymphocytes. Hierarchical clustering analysis grouped the lineage samples according to their origin based on the expression of these miRNAs. To validate discrimination power of the miRNAs, we quantified expression of the 13 miRNAs in several immortalized cell lines. Although the cell lines showed miRNA expression patterns considerably different from those of native cell lineages, clustering analysis distinguished between myeloid, lymphoid and non-hematopoietic cells. CONCLUSIONS: In conclusion, the study reports the expression levels of 13 miRNAs in particular blood cell lineages as well as immortalized cell lines. We demonstrate that the expression profiles of these miRNAs may be used for discrimination of the hematopoietic cell lineages.

• MeSH
• Cell Differentiation physiology   MeSH
• K562 Cells MeSH
• Financing, Organized MeSH
• HeLa Cells MeSH
• Leukocytes cytology   metabolism   MeSH
• Humans MeSH
• Lymphoid Progenitor Cells cytology   metabolism   MeSH
• MicroRNAs biosynthesis   MeSH
• Granulocyte Precursor Cells cytology   metabolism   MeSH
• Gene Expression Regulation physiology   MeSH
• Reticulocytes cytology   metabolism   MeSH
• Oligonucleotide Array Sequence Analysis methods   MeSH
• Gene Expression Profiling methods   MeSH
• Blood Platelets cytology   metabolism   MeSH
• Check Tag
• Humans MeSH

OBJECTIVES: Umbilical cord blood (UCB) has become a useful alternative source of hematopoietic stem cells for clinical and research applications. UCB represents neonatal blood and differs from adult blood in many aspects, displaying different cell composition and various features of cellular immaturity. To understand molecular basis of phenotypic differences between neonatal and adult blood, we studied variations in transcriptome of UCB and maternal peripheral blood (PB). METHODS: Using Illumina microarrays, we determined gene expression profiles of UCB and PB samples obtained from 30 mothers giving birth to living baby. RESULTS: Out of 20,589 tested genes, 424 genes were down-regulated and 417 genes were up-regulated in UCB compared with PB. Reduced expression of many immunity-related pathways (e.g. TLR pathway, Jak-STAT pathway, cytokine-cytokine receptor interaction) in neonatal blood cells may contribute to the poor response to antigens, increasing susceptibility to infections at the time of disappearance of protective maternal antibodies. On the other hand, overexpression of erythropoiesis-related genes (glycophorins, fetal hemoglobins, enzymes catalysing heme synthesis and erythrocyte differentiation) in UCB probably enforces red cell production in newborns. CONCLUSIONS: Our study demonstrates that neonatal and maternal bloods show specific gene expression profiles, likely reflecting differences in phenotypes of immunologically immature and fully evolved hematopoietic cells.

• MeSH
• Phenotype MeSH
• Fetal Blood cytology   MeSH
• Immune System MeSH
• Humans MeSH
• Mothers MeSH
• Infant, Newborn MeSH
• Umbilical Cord pathology   MeSH
• Gene Expression Regulation MeSH
• Oligonucleotide Array Sequence Analysis MeSH
• Cluster Analysis MeSH
• Gene Expression Profiling methods   MeSH
• Pregnancy MeSH
• Pregnancy Outcome MeSH
• Check Tag
• Humans MeSH
• Infant, Newborn MeSH
• Pregnancy MeSH
• Female MeSH
• Publication type
• Research Support, Non-U.S. Gov't MeSH

BACKGROUND: Myelodysplastic syndrome with isolated chromosome 5q deletion (5q- syndrome) is a clonal stem cell disorder characterized by ineffective hematopoiesis. MicroRNAs (miRNAs) are important regulators of hematopoiesis and their aberrant expression was detected in some clonal hematopoietic disorders. We thus analyzed miRNA expressions in bone marrow CD34+ cells of 5q- syndrome patients. Further, we studied gene expressions of miR-143, miR-145, miR-378 and miR-146a mapped within the 5q deletion. RESULTS: Using microarrays we identified 21 differently expressed miRNAs in 5q- patients compared to controls. Especially, miR-34a was markedly overexpressed in 5q- patients, suggesting its role in an increased apoptosis of bone marrow progenitors. Out of four miRNAs at del(5q), only miR-378 and miR-146a showed reduced gene expression in the patients. An integrative analysis of mRNA profiles and predicted putative targets defined potential downstream targets of the deregulated miRNAs. The list of targets included several genes that play an important role in the regulation of hematopoiesis (e.g. KLF4, LEF1, SPI1). CONCLUSIONS: The study demonstrates global overexpression of miRNAs is associated with 5q- phenotype. Identification of hematopoiesis-relevant target genes indicates that the deregulated miRNAs may be involved in the pathogenesis of 5q- syndrome by a modulation of these targets. The expression data on miRNAs at del(5q) suggest the presence of mechanisms for compensation of a gene dosage.

• MeSH
• Antigens, CD34 biosynthesis   genetics   MeSH
• Chromosome Deletion MeSH
• Humans MeSH
• Chromosomes, Human, Pair 5 genetics   metabolism   MeSH
• Anemia, Macrocytic genetics   metabolism   MeSH
• MicroRNAs biosynthesis   genetics   MeSH
• Myelodysplastic Syndromes genetics   metabolism   MeSH
• Gene Expression Profiling MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH

This study aimed to provide a molecular signature for enriched adult human stem/progenitor spermatogonia during short-term (<2 weeks) and long-term culture (up to more than 14 months) in comparison to human testicular fibroblasts and human embryonic stem cells. Human spermatogonia were isolated by CD49f magnetic activated cell sorting and collagen(-)/laminin(+) matrix binding from primary testis cultures obtained from ten adult men. For transcriptomic analysis, single spermatogonia-like cells were collected based on their morphology and dimensions using a micromanipulation system from the enriched germ cell cultures. Immunocytochemical, RT-PCR and microarray analyses revealed that the analyzed populations of cells were distinct at the molecular level. The germ- and pluripotency-associated genes and genes of differentiation/spermatogenesis pathway were highly expressed in enriched short-term cultured spermatogonia. After long-term culture, a proportion of cells retained and aggravated the "spermatogonial" gene expression profile with the expression of germ and pluripotency-associated genes, while in the majority of long-term cultured cells this molecular profile, typical for the differentiation pathway, was reduced and more genes related to the extracellular matrix production and attachment were expressed. The approach we provide here to study the molecular status of in vitro cultured spermatogonia may be important to optimize the culture conditions and to evaluate the germ cell plasticity in the future.

• MeSH
• Cell Differentiation genetics   MeSH
• Cell Culture Techniques methods   MeSH
• Adult MeSH
• Embryonic Stem Cells physiology   MeSH
• Fibroblasts physiology   MeSH
• Cells, Cultured MeSH
• Middle Aged MeSH
• Humans MeSH
• Young Adult MeSH
• Cell Separation methods   MeSH
• Spermatogenesis genetics   MeSH
• Spermatogonia physiology   MeSH
• Gene Expression Profiling methods   MeSH
• Testis physiology   MeSH
• Transcriptome genetics   MeSH
• Check Tag
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Young Adult MeSH
• Male MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH

• MeSH
• Acaridae genetics   immunology   MeSH
• Allergens genetics   immunology   MeSH
• Gene Expression * MeSH
• Microbiota * MeSH
• Gene Expression Profiling MeSH
• Transcriptome MeSH
• Animals MeSH
• Check Tag
• Animals MeSH
• Publication type
• Letter MeSH
• Research Support, Non-U.S. Gov't MeSH

Normalizations of gene expression data are commonly used in practice. They are used for removing systematic variation which affects the measure of gene expression levels. But one can object to the using of normalized data for testing hypotheses. By using normalized data, tests can break nominal level of multiple testing on which we would like to test the hypotheses. It could bring a lot of false positives, which we would like to prevent. In this chapter, by simulating data with similar correlation structure as real data, we try to find out how quantile, global, and δ-sequence normalizations hold the nominal level of Bonferroni multiple testing procedure.

• MeSH
• Algorithms MeSH
• Data Interpretation, Statistical * MeSH
• Humans MeSH
• Normal Distribution MeSH
• Computer Simulation MeSH
• Oligonucleotide Array Sequence Analysis methods   MeSH
• Gene Expression Profiling methods   MeSH
• Models, Statistical MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH