Browsing by Subject "DNA microarray"
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Item Open Access Application of a customized pathway-focused microarray for gene expression profiling of cellular homeostasis upon exposure to nicotine in PC12 cells(2004) Konu Ö.; Xu X.; Ma J.Z.; Kane J.; Wang J.; Shi, S.J.; Li, M.D.Maintenance of cellular homeostasis is integral to appropriate regulation of cellular signaling and cell growth and division. In this study, we report the development and quality assessment of a pathway-focused microarray comprising genes involved in cellular homeostasis. Since nicotine is known to have highly modulatory effects on the intracellular calcium homeostasis, we therefore tested the applicability of the homeostatic pathway-focused microarray on the gene expression in PC-12 cells treated with 1 mM nicotine for 48 h relative to the untreated control cells. We first provided a detailed description of the focused array with respect to its gene and pathway content and then assessed the array quality using a robust regression procedure that allows for the exclusion of unreliable measurements while decreasing the number of false positives. As a result, the mean correlation coefficient between duplicate measurements of the arrays used in this study (control vs. nicotine treatment, three samples each) has increased from 0.974±0.017 to 0.995±0.002. Furthermore, we found that nicotine affected various structural and signaling components of the AKT/PKB signaling pathway and protein synthesis and degradation processes in PC-12 cells. Since modulation of intracellular calcium concentrations ([Ca2+]i) and phosphatidylinositol signaling are important in various biological processes such as neurotransmitter release and tissue pathogenesis including tumor formation, we expect that the homeostatic pathway-focused microarray potentially can be used for the identification of unique gene expression profiles in comparative studies of drugs of abuse and diverse environmental stimuli, such as starvation and oxidative stress. © 2003 Elsevier B.V. All rights reserved.Item Open Access Identification of endogenous reference genes for qRT-PCR analysis in normal matched breast tumor tissues(Cognizant Communication Corporation, 2009) Gur-Dedeoglu, B.; Konu, O.; Bozkurt, B.; Ergul, G.; Seckin, S.; Yulug, I. G.Quantitative gene expression measurements from tumor tissue are frequently compared with matched normal and/or adjacent tumor tissue expression for diagnostic marker gene selection as well as assessment of the degree of transcriptional deregulation in cancer. Selection of an appropriate reference gene (RG) or an RG panel, which varies depending on cancer type, molecular subtypes, and the normal tissues used for interindividual calibration, is crucial for the accurate quantification of gene expression. Several RG panels have been suggested in breast cancer for making comparisons among tumor subtypes, cell lines, and benign/malignant tumors. In this study, expression patterns of 15 widely used endogenous RGs (ACTB, TBP, GAPDH, SDHA, HPRT, HMBS, B2M, PPIA, GUSB, YWHAZ2, PGK1, RPLP0, PUM1, MRPL19, and RPL41), and three candidate genes that were selected through analysis of two independent microarray datasets (IL22RA1, TTC22, ZNF224) were determined in 23 primary breast tumors and their matched normal tissues using qRTPCR. Additionally, 18S rRNA, ACTB, and SDHA were tested using randomly primed cDNAs from 13 breast tumor pairs to assess the rRNA/mRNA ratio. The tumors exhibited significantly lower rRNA/mRNA ratio when compared to their normals, on average. The expression of the studied RGs in breast tumors did not exhibit differences in terms of grade, ER, or PR status. The stability of RGs was examined based on two different statistical models, namely GeNorm and NormFinder. Among the 18 tested endogenous reference genes, ACTB and SDHA were identified as the most suitable reference genes for the normalization of qRTPCR data in the analysis of normal matched tumor breast tissue pairs by both programs. In addition, the expression of the gelsolin (GSN) gene, a well-known downregulated target in breast tumors, was analyzed using the two most suitable genes and different RG combinations to validate their effectiveness as a normalization factor (NF). The GSN expression of the tumors used in this study was significantly lower than that of normals showing the effectivity of using ACTB and SDHA as suitable RGs in this set of tumor–normal tissue panel. The combinational use of the best performing two RGs (ACTB and SDHA) as a normalization factor can be recommended to minimize sample variability and to increase the accuracy and resolution of gene expression normalization in tumor–normal paired breast cancer qRT-PCR studies.Item Open Access PATIKA: an integrated visual environment for collaborative construction and analysis of cellular pathways(Oxford University Press, 2002-06) Demir, Emek; Babur, Özgün; Doğrusöz, Uğur; Gürsoy, Atilla; Nişancı, Gürkan; Çetin Atalay, Rengül; Öztürk, MehmetMotivation: Availability of the sequences of entire genomes shifts the scientific curiosity towards the identification of function of the genomes in large scale as in genome studies. In the near future, data produced about cellular processes at molecular level will accumulate with an accelerating rate as a result of proteomics studies. In this regard, it is essential to develop tools for storing, integrating, accessing, and analyzing this data effectively. Results: We define an ontology for a comprehensive representation of cellular events. The ontology presented here enables integration of fragmented or incomplete pathway information and supports manipulation and incorporation of the stored data, as well as multiple levels of abstraction. Based on this ontology, we present the architecture of an integrated environment named PATIKA (Pathway Analysis Tool for Integration and Knowledge Acquisition). PATIKA is composed of a server-side, scalable, object-oriented database and client-side editors to provide an integrated, multi-user environment for visualizing and manipulating network of cellular events. This tool features automated pathway layout, functional computation support, advanced querying and a user-friendly graphical interface. We expect that PATIKA will be a valuable tool for rapid knowledge acquisition, microarray generated large-scale data interpretation, disease gene identification, and drug development.Item Open Access PATIKA: an integrated visual environment for collaborative construction and analysis of cellular pathways(American Society for Biochemistry and Molecular Biology(ASBMB), 2002-09) Demir, Emek; Babur, Özgün; Doğrusöz, Uğur; Gürsoy, Atilla; Nişancı, Gürkan; Çetin Atalay, Rengül; Öztürk, MehmetItem Open Access PATIKAmad: putting microarray data into pathway context(Wiley - V C H Verlag GmbH & Co. KGaA, 2008-06) Babur, Özgün; Colak, Recep; Demir, Emek; Doğrusöz, UğurHigh-throughput experiments, most significantly DNA microarrays, provide us with system-scale profiles. Connecting these data with existing biological networks poses a formidable challenge to uncover facts about a cell's proteome. Studies and tools with this purpose are limited to networks with simple structure, such as protein-protein interaction graphs, or do not go much beyond than simply displaying values on the network. We have built a microarray data analysis tool, named PATIKAmad, which can be used to associate microarray data with the pathway models in mechanistic detail, and provides facilities for visualization, clustering, querying, and navigation of biological graphs related with loaded microarray experiments. PATIKAmad is freely available to noncommercial users as a new module of PATIKAweb at http://web.patika.org. © 2008 Wiley-VCH Verlag GmbH & Co. KGaA.Item Open Access A resampling-based meta-analysis for detection of differential gene expression in breast cancer(BioMed Central, 2008) Gur-Dedeoglu, B.; Konu, O.; Kir, S.; Ozturk, A. R.; Bozkurt, B.; Ergul, G.; Yulug, I.G.Background: Accuracy in the diagnosis of breast cancer and classification of cancer subtypes has improved over the years with the development of well-established immunohistopathological criteria. More recently, diagnostic gene-sets at the mRNA expression level have been tested as better predictors of disease state. However, breast cancer is heterogeneous in nature; thus extraction of differentially expressed gene-sets that stably distinguish normal tissue from various pathologies poses challenges. Meta-analysis of high-throughput expression data using a collection of statistical methodologies leads to the identification of robust tumor gene expression signatures. Methods: A resampling-based meta-analysis strategy, which involves the use of resampling and application of distribution statistics in combination to assess the degree of significance in differential expression between sample classes, was developed. Two independent microarray datasets that contain normal breast, invasive ductal carcinoma (IDC), and invasive lobular carcinoma (ILC) samples were used for the meta-analysis. Expression of the genes, selected from the gene list for classification of normal breast samples and breast tumors encompassing both the ILC and IDC subtypes were tested on 10 independent primary IDC samples and matched non-tumor controls by real-time qRT-PCR. Other existing breast cancer microarray datasets were used in support of the resampling-based meta-analysis. Results: The two independent microarray studies were found to be comparable, although differing in their experimental methodologies (Pearson correlation coefficient, R = 0.9389 and R = 0.8465 for ductal and lobular samples, respectively). The resampling-based meta-analysis has led to the identification of a highly stable set of genes for classification of normal breast samples and breast tumors encompassing both the ILC and IDC subtypes. The expression results of the selected genes obtained through real-time qRT-PCR supported the meta-analysis results. Conclusion: The proposed meta-analysis approach has the ability to detect a set of differentially expressed genes with the least amount of within-group variability, thus providing highly stable gene lists for class prediction. Increased statistical power and stringent filtering criteria used in the present study also make identification of novel candidate genes possible and may provide further insight to improve our understanding of breast cancer development.Item Open Access Strain-and region-specific gene expression profiles in mouse brain in response to chronic nicotine treatment(Wiley-Blackwell Publishing, 2008) Wang, J.; Gutala, R.; Hwang, Y. Y.; Kim J. -M.; Konu, O.; Ma, J. Z.; Li, M. D.A pathway-focused complementary DNA microarray and gene ontology analysis were used to investigate gene expression profiles in the amygdala, hippocampus, nucleus accumbens, prefrontal cortex (PFC) and ventral tegmental area of C3H/HeJ and C57BL/6J mice receiving nicotine in drinking water (100 μg/ml in 2% saccharin for 2 weeks). A balanced experimental design and rigorous statistical analysis have led to the identification of 3.5-22.1% and 4.1-14.3% of the 638 sequence-verified genes as significantly modulated in the aforementioned brain regions of the C3H/HeJ and C57BL/6J strains, respectively. Comparisons of differential expression among brain tissues showed that only a small number of genes were altered in multiple brain regions, suggesting presence of a brain region-specific transcriptional response to nicotine. Subsequent principal component analysis and Expression Analysis Systematic Explorer analysis showed significant enrichment of biological processes both in C3H/HeJ and C57BL/6J mice, i.e. cell cycle/proliferation, organogenesis and transmission of nerve impulse. Finally, we verified the observed changes in expression using real-time reverse transcriptase polymerase chain reaction for six representative genes in the PFC region, providing an independent replication of our microarray results. Together, this report represents the first comprehensive gene expression profiling investigation of the changes caused by nicotine in brain tissues of the two mouse strains known to exhibit differential behavioral and physiological responses to nicotine.