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Genetic and Proteomic Screening in Patients with Cardiovascular Disease.
Šímová, Jana ; Škvor, Jiří (advisor) ; Gregor, Pavel (referee) ; Čurila, Karol (referee)
The aim of this study is to analyse a genetic and proteomic aspects that could play an important role in development of chosen cardiovascular disease. Matrix metalloproteinases are enzymes that contribute strongly to the degradation of extracellular matrix components. In this study the serological levels of MMP-2 and MMP-9 were investigated using immunological testing in patients with aortic valve disease and in patients with myocardial infarction. Significantly higher levels of MMP-2 and MMP-9 were determined in both above mentioned groups of patients. Association of serum levels of MMP-2 and MMP-9 and development of concomitant aortic dilatation was not confirmed in patients with aortic valve disease. Changes in serum levels within 24 hours and after 6 months post myocardial infarction were characterized. About 10 % of patients operated for aortic valve disease suffer simultaneously from ascending aortic dilatation. The current study did not reveal any significant genetic variation in TGFBR2 gene and in chosen exons of FBN1 gene in these patients. Further genetic research is needed to identify the cause of the pathology in aortic wall. Gene expression of selected genes was measured by microarray screening in patients with myocardial infarction. These genes were related to MMPs and did not show...
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DIFFERENTIAL RESISTANCE OF MELANOMA TO VINCA - ALKALOIDS
Rozkydalová, Lucie ; Štaud, František (advisor) ; Čečková, Martina (referee)
Charles University in Prague Faculty of Pharmacy in Hradec Králové Department of Pharmacology and toxicology Student: Lucie Rozkydalová Supervisor of Diploma thesis: Prof. PharmDr. František Štaud, PhD. Specialized supervisor: Pr. Pierre Cuq PharmD. PhD., Laure-Anaïs Vincent Title of diploma thesis: Differential resistance of melanoma to vinca-alkaloids Malignant melanoma (MM) represents the most dangerous and very aggressive skin tumor with fast development of drug resistance which is the main obstacle in successful treatment of MM. According to previous studies (microarray data analysis), KIT gene, which plays key role in melanoma pathophysiology, was chosen as one of the potential causes of failure of treatment by vinca alkaloids (VAs) because of its complete underexpression in melanoma CAL1 resistant cells (CAL1R-VAs) in comparison with parental cells (CAL1-wt). Moreover, KIT also interacted with NF-κB and cyclin D1-2 proteins involved in chemoresistance of melanoma - inside molecular network built using IPA software. Although KIT underexpression in resistant CAL1 R-VAs cell lines were confirmed (qRTPCR), KIT repression using specific siRNA transfection did not show any effect on in vitro sensibility of CAL1-wt cells to VAs. It signifies that KIT is not directly involved in melanoma resistance...
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Microarray Data Interpretation
Ludwig, Petr ; Šilhavá, Jana (referee) ; Smrž, Pavel (advisor)
This Bachelor thesis explains the basics of biochip or microarray data interpretation, starting with short introduction to genetics, especially genetic information significance evaluating. The focus was set mainly on the set of scripts transforming and analyzing the sample data. The data used in this thesis are a result of biochip analysis of the Colon Tumor tissues. The secondary result represents disclosing the main marker for this particular type of cancer, the primary result is evaluation of marker significance in the context of signaling pathways. The resulting pathways are sorted by relevance.
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Classification Methods for Micriarrays Data
Hudec, Vladimír ; Bartík, Vladimír (referee) ; Burgetová, Ivana (advisor)
This paper discusses about the data obtained from gene chips and methods of their analysis. Analyzes some methods for analyzing these data and focus on the method of "Random Forests". Shows dataset that is used for specific experiments. Methods are realized in R language environment. Than they are tested, and the results are presented and compared. Results with method "Random Forests" are compared with other experiments on same dataset.
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Molecular Signature as Optima of Multi-Objective Function with Applications to Prediction in Oncogenomics
Aligerová, Zuzana ; Maděránková, Denisa (referee) ; Provazník, Ivo (advisor)
Náplní této práce je teoretický úvod a následné praktické zpracování tématu Molekulární signatura jako optimální multi-objektivní funkce s aplikací v predikci v onkogenomice. Úvodní kapitoly jsou zaměřeny na téma rakovina, zejména pak rakovina prsu a její podtyp triple negativní rakovinu prsu. Následuje literární přehled z oblasti optimalizačních metod, zejména se zaměřením na metaheuristické metody a problematiku strojového učení. Část se odkazuje na onkogenomiku a principy microarray a také na statistiku a s důrazem na výpočet p-hodnoty a bimodálního indexu. Praktická část je pak zaměřena na konkrétní průběh výzkumu a nalezené závěry, vedoucí k dalším krokům výzkumu. Implementace vybraných metod byla provedena v programech Matlab a R, s využitím dalších programovacích jazyků a to konkrétně programů Java a Python.
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