948 resultados para cDNA microarray analysis


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Using cDNA microarray analysis, we previously identified a set of differentially expressed genes in primary breast tumors based on the status of estrogen and progesterone receptors. In the present study, we performed an integrated computer-assisted and manual search of potential estrogen response element (ERE) binding sites in the promoter region of these genes to characterize their potential to be regulated by estrogen receptors (ER). Publicly available databases were used to annotate the position of these genes in the genome and to extract a 5’flanking region 2 kb upstream to 2 kb downstream of the transcription start site for transcription binding site analysis. The search for EREs and other binding sites was performed using several publicly available programs. Overall, approximately 40% of the genes analyzed were potentially able to be regulated by estrogen via ER. In addition, 17% of these genes are located very close to other genes organized in a head-to-head orientation with less than 1.0 kb between their transcript units, sharing a bidirectional promoter, and could be classified as bidirectional gene pairs. Using quantitative real-time PCR, we further investigated the effects of 17β-estradiol and antiestrogens on the expression of the bidirectional gene pairs in MCF-7 breast cancer cells. Our results showed that some of these gene pairs, such as TXNDC9/EIF5B, GALNS/TRAPPC2L, and SERINC1/PKIB, are modulated by 17β-estradiol via ER in MCF-7 breast cancer cells. Here, we also characterize the promoter region of potential ER-regulated genes and provide new information on the transcriptional regulation of bidirectional gene pairs.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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The acquisition of the metastatic melanoma phenotype is associated with increased expression of the melanoma cell adhesion molecule MCAM/MUC18 (CD146). However, the mechanism by which MUC18 contributes to melanoma metastasis remains unclear. Herein, we stably silenced MUC18 expression utilizing lentivirus-incorporated small hairpin RNA, in two metastatic melanoma cell lines, A375SM and C8161, and conducted cDNA microarray analysis. We identified and validated that the transcriptional regulator, Inhibitor of DNA Binding-1 (Id-1), previously shown to function as an oncogene in several malignancies, was downregulated by 5.6-fold following MUC18 silencing. Additionally, we found that MUC18 regulated Id-1 expression at the transcriptional level via ATF-3. Interestingly, ATF-3 was upregulated by 6.9 fold in our cDNA microarray analysis following MUC18 silencing. ChIP analysis showed increased binding of ATF-3 to the Id-1 promoter after MUC18 silencing, while mutation of the ATF-3 binding site on the Id-1 promoter increased Id-1 promoter activity in MUC18-silenced cells. These Data suggest that MUC18 silencing promotes inhibition of Id-1 expression by increasing ATF-3 expression and binding to the Id-1 promoter. Rescue of MUC18 reverted the expression of Id-1 and ATF-3, thus validating that they are not off-target effects of MUC18. To further assess the role of Id-1 in melanoma invasion and metastasis, we overexpressed Id-1 in MUC18-silenced cells. Overexpression of Id-1 in MUC18-silenced cells resulted in increased cell invasion, as well as increased expression and activity of MMP-2. Our data further reveal that Id-1 regulates MMP-2 at the transcriptional level through Sp1 and Ets-1. This is the first report to demonstrate that MUC18 does not act exclusively in cell adherence, but is also involved in cell signaling that regulates the expression of genes, such as Id-1 and ATF-3, thus contributing to the metastatic melanoma phenotype.

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Sandhoff disease is a lysosomal storage disorder characterized by the absence of β-hexosaminidase and storage of GM2 ganglioside and related glycolipids in the central nervous system. The glycolipid storage causes severe neurodegeneration through a poorly understood pathogenic mechanism. In symptomatic Sandhoff disease mice, apoptotic neuronal cell death was prominent in the caudal regions of the brain. cDNA microarray analysis to monitor gene expression during neuronal cell death revealed an upregulation of genes related to an inflammatory process dominated by activated microglia. Activated microglial expansion, based on gene expression and histologic analysis, was found to precede massive neuronal death. Extensive microglia activation also was detected in a human case of Sandhoff disease. Bone marrow transplantation of Sandhoff disease mice suppressed both the explosive expansion of activated microglia and the neuronal cell death without detectable decreases in neuronal GM2 ganglioside storage. These results suggest a mechanism of neurodegeneration that includes a vigorous inflammatory response as an important component. Thus, this lysosomal storage disease has parallels to other neurodegenerative disorders, such as Alzheimer's and prion diseases, where inflammatory processes are believed to participate directly in neuronal cell death.

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We have previously tested the effects of high dose AA supplements on human volunteers in terms of reducing DNA damage, as a possible mechanism of the vitamin’s proposed protective effect against cancer and detected a transient, pro-oxidant effect at high doses (500 mg/day). Herein, we present evidence of a pro-oxidant effect of the vitamin when added to CCRF cells at extracellular concentrations which mimic those present in human serum in vivo (50–150AM). The activation of the transcription factor AP-1 was optimal at 100 AM AA following 3h exposure at 37jC. A minimum dose of 50 AM of AA activated NFnB but there appeared to be no dose-dependent effect. Increases of 2–3 fold were observed for both transcription factors when cells were exposed to 100 AM AA for 3h, comparing well with the pro-oxidant effect of H2O2 at similar concentrations. In parallel experiments the activation of AP-1 (binding to DNA) was potentiated when cells were pre-incubated with AA prior to exposure with H2O2. Cycloheximide pretreatment (10 Ag/ml for 15min) caused a 50% inhibition of AP-1 binding to DNA suggesting that it was due to a combination of increasing the binding of pre-existing Fos and Jun and an increase in their de novo synthesis. Cellular localisation was confirmed by immunocytochemistry using antibodies specific for c-Fos and c-Jun proteins. These results suggest that extracellular AA can elicit an intracellular stress response resulting in the activation of the oxidative stress-responsive transcription factors AP-1 and NFnB. These transcription factors are involved in the induction of genes associated with an oxidative stress response, cell cycle arrest and DNA repair confirmed by our cDNA microarray analysis (Affymetrix). This may explain the abilty for AA to appear to inhibit 8-oxodG, yet simultaneously generate another oxidative stress biomarker, 8-oxo-dA. These results suggest a completely novel DNA repair action for AA. Whether this action is relevant to our in vivo findings will be the subject of our future research.

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Improvements in the analysis of microarray images are critical for accurately quantifying gene expression levels. The acquisition of accurate spot intensities directly influences the results and interpretation of statistical analyses. This dissertation discusses the implementation of a novel approach to the analysis of cDNA microarray images. We use a stellar photometric model, the Moffat function, to quantify microarray spots from nylon microarray images. The inherent flexibility of the Moffat shape model makes it ideal for quantifying microarray spots. We apply our novel approach to a Wilms' tumor microarray study and compare our results with a fixed-circle segmentation approach for spot quantification. Our results suggest that different spot feature extraction methods can have an impact on the ability of statistical methods to identify differentially expressed genes. We also used the Moffat function to simulate a series of microarray images under various experimental conditions. These simulations were used to validate the performance of various statistical methods for identifying differentially expressed genes. Our simulation results indicate that tests taking into account the dependency between mean spot intensity and variance estimation, such as the smoothened t-test, can better identify differentially expressed genes, especially when the number of replicates and mean fold change are low. The analysis of the simulations also showed that overall, a rank sum test (Mann-Whitney) performed well at identifying differentially expressed genes. Previous work has suggested the strengths of nonparametric approaches for identifying differentially expressed genes. We also show that multivariate approaches, such as hierarchical and k-means cluster analysis along with principal components analysis, are only effective at classifying samples when replicate numbers and mean fold change are high. Finally, we show how our stellar shape model approach can be extended to the analysis of 2D-gel images by adapting the Moffat function to take into account the elliptical nature of spots in such images. Our results indicate that stellar shape models offer a previously unexplored approach for the quantification of 2D-gel spots. ^

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We present statistical methods for analyzing replicated cDNA microarray expression data and report the results of a controlled experiment. The study was conducted to investigate inherent variability in gene expression data and the extent to which replication in an experiment produces more consistent and reliable findings. We introduce a statistical model to describe the probability that mRNA is contained in the target sample tissue, converted to probe, and ultimately detected on the slide. We also introduce a method to analyze the combined data from all replicates. Of the 288 genes considered in this controlled experiment, 32 would be expected to produce strong hybridization signals because of the known presence of repetitive sequences within them. Results based on individual replicates, however, show that there are 55, 36, and 58 highly expressed genes in replicates 1, 2, and 3, respectively. On the other hand, an analysis by using the combined data from all 3 replicates reveals that only 2 of the 288 genes are incorrectly classified as expressed. Our experiment shows that any single microarray output is subject to substantial variability. By pooling data from replicates, we can provide a more reliable analysis of gene expression data. Therefore, we conclude that designing experiments with replications will greatly reduce misclassification rates. We recommend that at least three replicates be used in designing experiments by using cDNA microarrays, particularly when gene expression data from single specimens are being analyzed.

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Gene expression studies from hematopoietic stem cell (HSC) populations purified to variable degrees have defined a set of sternness genes. Unexpectedly, results also hinted toward a HSC chromatin poised in a wide-open state. With the aim of providing a robust tool for further studies into the molecular biology of HSCs, the studies herein describe the construction and comparative molecular analysis of A-phage cDNA libraries from highly purified HSCs that retained their long-term repopulating activities (long-term HSCs [LT-HSCs]) and from short-term repopulating HSCs that were largely depleted of these activities. Microarray analysis of the libraries confirmed the previous results but also revealed an unforeseen preferential expression of translation- and metabolism-associated genes in the LT-HSCs. Therefore, these data indicate that HSCs are quiescent only in regard of proliferative activities but are in a state of readiness to provide the metabolic and translational activities required after induction of proliferation and exit from the HSC pool.

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Background: Microarray transcript profiling has the potential to illuminate the molecular processes that are involved in the responses of cattle to disease challenges. This knowledge may allow the development of strategies that exploit these genes to enhance resistance to disease in an individual or animal population. Results: The Bovine Innate Immune Microarray developed in this study consists of 1480 characterised genes identified by literature searches, 31 positive and negative control elements and 5376 cDNAs derived from subtracted and normalised libraries. The cDNA libraries were produced from 'challenged' bovine epithelial and leukocyte cells. The microarray was found to have a limit of detection of 1 pg/mu g of total RNA and a mean slide-to-slide correlation co-efficient of 0.88. The profiles of differentially expressed genes from Concanavalin A ( ConA) stimulated bovine peripheral blood lymphocytes were determined. Three distinct profiles highlighted 19 genes that were rapidly up-regulated within 30 minutes and returned to basal levels by 24 h; 76 genes that were upregulated between 2 - 8 hours and sustained high levels of expression until 24 h and 10 genes that were down-regulated. Quantitative real-time RT-PCR on selected genes was used to confirm the results from the microarray analysis. The results indicate that there is a dynamic process involving gene activation and regulatory mechanisms re-establishing homeostasis in the ConA activated lymphocytes. The Bovine Innate Immune Microarray was also used to determine the cross-species hybridisation capabilities of an ovine PBL sample. Conclusion: The Bovine Innate Immune Microarray has been developed which contains a set of well-characterised genes and anonymous cDNAs from a number of different bovine cell types. The microarray can be used to determine the gene expression profiles underlying innate immune responses in cattle and sheep.

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The current approach to prostate cancer diagnosis has major limitations including the inability of prostate-specific antigen (PSA) assays to accurately differentiate between prostate cancer and benign prostate hyperplasia (BPH) and the imprecision of transrectal ultrasound (TRUS) biopsy sampling. We have employed cDNA microarray screening to compare gene expression patterns in BPH and tumour samples to identify expression markers that may be useful in discriminating between these conditions. Screening of 3 individual cDNA arrays identified 8 genes with expression 3-fold greater in 6 tumour tissues than in 1 nontumour sample and I BPH sample. Real-time PCR was used to confirm the overexpression of these 8 genes and 12 genes selected from the literature against a panel of 17 tumours and I 1 BPH samples. Two genes, delta-catenin (delta-catenin; CTNND2) and prostate-specific membrane antigen (PSMA; FOLH1), were significantly overexpressed in prostate cancer compared to BPH. Prostate epithelial cells stained positively for S-catenin and PSMA in our prostate cancer tissues, whereas the majority of our BPH tissues were negative for both markers. Thus we have identified delta-catenin (not previously associated with prostatic adenocarcinoma) and confirmed the potential of PSMA as potential candidates for the diagnosis and management of prostate cancer. (C) 2002 Wiley-Liss. Inc.

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Microarray allow to monitoring simultaneously thousands of genes, where the abundance of the transcripts under a same experimental condition at the same time can be quantified. Among various available array technologies, double channel cDNA microarray experiments have arisen in numerous technical protocols associated to genomic studies, which is the focus of this work. Microarray experiments involve many steps and each one can affect the quality of raw data. Background correction and normalization are preprocessing techniques to clean and correct the raw data when undesirable fluctuations arise from technical factors. Several recent studies showed that there is no preprocessing strategy that outperforms others in all circumstances and thus it seems difficult to provide general recommendations. In this work, it is proposed to use exploratory techniques to visualize the effects of preprocessing methods on statistical analysis of cancer two-channel microarray data sets, where the cancer types (classes) are known. For selecting differential expressed genes the arrow plot was used and the graph of profiles resultant from the correspondence analysis for visualizing the results. It was used 6 background methods and 6 normalization methods, performing 36 pre-processing methods and it was analyzed in a published cDNA microarray database (Liver) available at http://genome-www5.stanford.edu/ which microarrays were already classified by cancer type. All statistical analyses were performed using the R statistical software.

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Powdery mildew is an important disease of wheat caused by the obligate biotrophic fungus Blumeria graminis f. sp. tritici. This pathogen invades exclusively epidermal cells after penetrating directly through the cell wall. Because powdery mildew colonizes exclusively epidermal cells, it is of importance not only to identify genes which are activated, but also to monitor tissue specificity of gene activation. Acquired resistance of wheat to powdery mildew can be induced by a previous inoculation with the non-host pathogen B. graminis f. sp. hordei, the causal agent of barley powdery mildew. The establishment of the resistant state is accompanied by the activation of genes. Here we report the tissue-specific cDNA-AFLP analysis and cloning of transcripts accumulating 6 and 24 h after the resistance-inducing inoculation with B. graminis f. sp. hordei. A total of 25,000 fragments estimated to represent about 17,000 transcripts were displayed. Out of these, 141 transcripts, were found to accumulate after Bgh inoculation using microarray hybridization analysis. Forty-four accumulated predominantly in the epidermis whereas 76 transcripts accumulated mostly in mesophyll tissue.

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PURPOSE: Because desmoid tumors exhibit an unpredictable clinical course, translational research is crucial to identify the predictive factors of progression in addition to the clinical parameters. The main issue is to detect patients who are at a higher risk of progression. The aim of this work was to identify molecular markers that can predict progression-free survival (PFS). EXPERIMENTAL DESIGN: Gene-expression screening was conducted on 115 available independent untreated primary desmoid tumors using cDNA microarray. We established a prognostic gene-expression signature composed of 36 genes. To test robustness, we randomly generated 1,000 36-gene signatures and compared their outcome association to our define 36-genes molecular signature and we calculated positive predictive value (PPV) and negative predictive value (NPV). RESULTS: Multivariate analysis showed that our molecular signature had a significant impact on PFS while no clinical factor had any prognostic value. Among the 1,000 random signatures generated, 56.7% were significant and none was more significant than our 36-gene molecular signature. PPV and NPV were high (75.58% and 81.82%, respectively). Finally, the top two genes downregulated in no-recurrence were FECH and STOML2 and the top gene upregulated in no-recurrence was TRIP6. CONCLUSIONS: By analyzing expression profiles, we have identified a gene-expression signature that is able to predict PFS. This tool may be useful for prospective clinical studies. Clin Cancer Res; 21(18); 4194-200. ©2015 AACR.

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Background: We use an approach based on Factor Analysis to analyze datasets generated for transcriptional profiling. The method groups samples into biologically relevant categories, and enables the identification of genes and pathways most significantly associated to each phenotypic group, while allowing for the participation of a given gene in more than one cluster. Genes assigned to each cluster are used for the detection of pathways predominantly activated in that cluster by finding statistically significant associated GO terms. We tested the approach with a published dataset of microarray experiments in yeast. Upon validation with the yeast dataset, we applied the technique to a prostate cancer dataset. Results: Two major pathways are shown to be activated in organ-confined, non-metastatic prostate cancer: those regulated by the androgen receptor and by receptor tyrosine kinases. A number of gene markers (HER3, IQGAP2 and POR1) highlighted by the software and related to the later pathway have been validated experimentally a posteriori on independent samples. Conclusion: Using a new microarray analysis tool followed by a posteriori experimental validation of the results, we have confirmed several putative markers of malignancy associated with peptide growth factor signalling in prostate cancer and revealed others, most notably ERRB3 (HER3). Our study suggest that, in primary prostate cancer, HER3, together or not with HER4, rather than in receptor complexes involving HER2, could play an important role in the biology of these tumors. These results provide new evidence for the role of receptor tyrosine kinases in the establishment and progression of prostate cancer.

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Currently, numerous high-throughput technologies are available for the study of human carcinomas. In literature, many variations of these techniques have been described. The common denominator for these methodologies is the high amount of data obtained in a single experiment, in a short time period, and at a fairly low cost. However, these methods have also been described with several problems and limitations. The purpose of this study was to test the applicability of two selected high-throughput methods, cDNA and tissue microarrays (TMA), in cancer research. Two common human malignancies, breast and colorectal cancer, were used as examples. This thesis aims to present some practical considerations that need to be addressed when applying these techniques. cDNA microarrays were applied to screen aberrant gene expression in breast and colon cancers. Immunohistochemistry was used to validate the results and to evaluate the association of selected novel tumour markers with the outcome of the patients. The type of histological material used in immunohistochemistry was evaluated especially considering the applicability of whole tissue sections and different types of TMAs. Special attention was put on the methodological details in the cDNA microarray and TMA experiments. In conclusion, many potential tumour markers were identified in the cDNA microarray analyses. Immunohistochemistry could be applied to validate the observed gene expression changes of selected markers and to associate their expression change with patient outcome. In the current experiments, both TMAs and whole tissue sections could be used for this purpose. This study showed for the first time that securin and p120 catenin protein expression predict breast cancer outcome and the immunopositivity of carbonic anhydrase IX associates with the outcome of rectal cancer. The predictive value of these proteins was statistically evident also in multivariate analyses with up to a 13.1- fold risk for cancer specific death in a specific subgroup of patients.