889 resultados para Gene-expression Profile


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Laryngeal squamous cell carcinoma (LSCC) is one of the most common malignancies of the head and neck tumors Zhang et al., 2013 [1]). Previous studies have associated its occurrence with social activities, such as tobacco and alcohol consumption (Hashibe et al., 2007a [2]; Hashibe et al., 2007b [3]; Shangina et al., 2006 [4]). Here, we performed a genome-wide gene expression profiling in thirty-one patients positively diagnosed for LSCC, in order to investigate new targets involved in tumorigenesis.

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Xylella fastidiosa inhabits the plant xylem, a nutrient-poor environment, so that mechanisms to sense and respond to adverse environmental conditions are extremely important for bacterial survival in the plant host. Although the complete genome sequences of different Xylella strains have been determined, little is known about stress responses and gene regulation in these organisms. In this work, a DNA microarray was constructed containing 2,600 ORFs identified in the genome sequencing project of Xylella fastidiosa 9a5c strain, and used to check global gene expression differences in the bacteria when it is infecting a symptomatic and a tolerant citrus tree. Different patterns of expression were found in each variety, suggesting that bacteria are responding differentially according to each plant xylem environment. The global gene expression profile was determined and several genes related to bacterial survival in stressed conditions were found to be differentially expressed between varieties, suggesting the involvement of different strategies for adaptation to the environment. The expression pattern of some genes related to the heat shock response, toxin and detoxification processes, adaptation to atypical conditions, repair systems as well as some regulatory genes are discussed in this paper. DNA microarray proved to be a powerful technique for global transcriptome analyses. This is one of the first studies of Xylella fastidiosa gene expression in vivo which helped to increase insight into stress responses and possible bacterial survival mechanisms in the nutrient-poor environment of xylem vessels.

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Several biological events are controlled by Hedgehog (Hh) signaling, including osteoblast phenotype development. This study aimed at evaluating the gene expression profile of human mesenchymal stem cells (hMSCs) treated with the Hh agonist, purmorphamine, focusing on Hh signaling and osteoblast differentiation. hMSCs from bone marrow were cultured in non-osteogenic medium with or without purmorphamine (2 mu M) for periods of up to 14 days. Purmorphamine up-regulated gene expression of the mediators of Hh pathway, SMO, PTCH1, GLI1, and GLI2. The activation of Hh pathway by purmorphamine increased the expression of several genes (e.g., RUNX2 and BMPs) related to osteogenesis. Our results indicated that purmorphamine triggers Hh signaling pathway in hMSCs, inducing an increase in the expression of a set of genes involved in the osteoblast differentiation program. Thus, we conclude that Hh is a crucial pathway in the commitment of undifferentiated cells to the osteoblast lineage. J. Cell. Biochem. 113: 204208, 2012. (C) 2011 Wiley Periodicals, Inc.

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Chronic administration of glucocorticoids (GC) leads to characteristic features of type 2 diabetes in mammals. The main action of dexamethasone in target cells occurs through modulation of gene expression, although the exact mechanisms are still unknown. We therefore investigated the gene expression profile of pancreatic islets from rats treated with dexamethasone using a cDNA array screening analysis. The expression of selected genes and proteins involved in mitochondria] apoptosis was further analyzed by PCR and immunoblotting. Insulin, triglyceride and free fatty acid plasma levels, as well as glucose-induced insulin secretion, were significantly higher in dexamethasone-treated rats compared with controls. Out of 1176 genes, 60 were up-regulated and 28 were down-regulated by dexamethasone treatment. Some of the modulated genes are involved in apoptosis, stress response, and proliferation pathways. RT-PCR confirmed the cDNA array results for 6 selected genes. Bax alpha protein expression was increased, while Bcl-2 was decreased. In vivo dexamethasone treatment decreased the mitochondrial production of NAD(P)H, and increased ROS production. Concluding, our data indicate that dexamethasone modulates the expression of genes and proteins involved in several pathways of pancreatic-islet cells, and mitochondria dysfunction might be involved in the deleterious effects after long-term GC treatment.

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It is generally agreed that the mechanical environment of intervertebral disc cells plays an important role in maintaining a balanced matrix metabolism. The precise mechanism by which the signals are transduced into the cells is poorly understood. Osmotic changes in the extracellular matrix (ECM) are thought to be involved. Current in-vitro studies on this topic are mostly short-term and show conflicting data on the reaction of disc cells subjected to osmotic changes which is partially due to the heterogenous and often substantially-reduced culture systems. The aim of the study was therefore to investigate the effects of cyclic osmotic loading for 4 weeks on metabolism and matrix gene expression in a full-organ intervertebral disc culture system. Intervertebral disc/endplate units were isolated from New Zealand White Rabbits and cultured either in iso-osmotic media (335 mosmol/kg) or were diurnally exposed for 8 hours to hyper-osmotic conditions (485 mosmol/kg). Cell viability, metabolic activity, matrix composition and matrix gene expression profile (collagen types I/II and aggrecan) were monitored using Live/Dead cell viability assay, tetrazolium reduction test (WST 8), proteoglycan and DNA quantification assays and quantitative PCR. The results show that diurnal osmotic stimulation did not have significant effects on proteoglycan content, cellularity and disc cell viability after 28 days in culture. However, hyperosmolarity caused increased cell death in the early culture phase and counteracted up-regulation of type I collagen gene expression in nucleus and annulus cells. Moreover, the initially decreased cellular dehydrogenase activity recovered with osmotic stimulation after 4 weeks and aggrecan gene down-regulation was delayed, although the latter was not significant according to our statistical criteria. In contrast, collagen type II did not respond to the osmotic changes and was down-regulated in both groups. In conclusion, diurnal hyper-osmotic stimulation of a whole-organ disc/endplate culture partially inhibits a matrix gene expression profile as encountered in degenerative disc disease and counteracts cellular metabolic hypo-activity.

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Infection with Shiga-toxin producing Escherichia coli (STEC) may result in the development of the haemolytic-uremic syndrome (HUS), the main cause of acute renal failure in children. While O157:H7 STEC are associated with large outbreaks of HUS, it is difficult to predict whether a non-O157:H7 isolate can be pathogenic for humans. The mucosal innate immune response plays a central role in the pathogenesis of HUS; therefore, we compared the induction of IL-8 and CCL20 in human colon epithelial cells infected with strains belonging to different serotypes, isolated from cattle or from HUS patients. No correlation was observed between strain virulence and chemokine gene expression. Rather, the genetic background of the strains seems to determine the chemokine gene expression profile. Investigating the contribution of different bacterial factors in this process, we show that the type III secretion system of O157:H7 bacteria, but not the intimate adhesion, is required to stimulate the cells. In addition, H7, H10, and H21 flagellins are potent inducers of chemokine gene expression when synthesized in large amount.

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The endometrium contains a distinct population of immune cells that undergo cyclic changes during the menstrual cycle and implantation. The majority of these leucocytes are uterine NK (uNK) cells, however how these cells interact with uterine stromal fibroblasts remains unclear. We therefore investigated the paracrine effect of medium conditioned by uterine decidual leucocytes (which are enriched for uNK cells) on the gene expression profile of endometrial stromal fibroblasts in vitro using a cDNA microarray. Our results, verified by real-time PCR, ELISA and FACS analysis, reveal that soluble factors from uterine leucocytes substantially alter endometrial stromal fibroblast gene expression. The largest group of up-regulated genes found was chemokines and cytokines. These include IL-8, CCL8 and CXCL1, which have also been shown to be stimulated by contact of stromal fibroblasts with trophoblast, suggesting that uNK cells work synergistically to support trophoblast migration during implantation. The decidual leucocytes also up-regulated IL-15 and IL-15Ralpha in stromal fibroblasts which could produce a niche for uNK cells allowing proliferation within and recruitment into the uterus, as seen in bone marrow. Overall this study demonstrates, for the first time, the paracrine communication between uterine leucocytes and uterine stromal fibroblasts, and adds to the understanding of how the uterine immune system contributes to the changes seen within the cycling endometrium.

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Brain tumor is one of the most aggressive types of cancer in humans, with an estimated median survival time of 12 months and only 4% of the patients surviving more than 5 years after disease diagnosis. Until recently, brain tumor prognosis has been based only on clinical information such as tumor grade and patient age, but there are reports indicating that molecular profiling of gliomas can reveal subgroups of patients with distinct survival rates. We hypothesize that coupling molecular profiling of brain tumors with clinical information might improve predictions of patient survival time and, consequently, better guide future treatment decisions. In order to evaluate this hypothesis, the general goal of this research is to build models for survival prediction of glioma patients using DNA molecular profiles (U133 Affymetrix gene expression microarrays) along with clinical information. First, a predictive Random Forest model is built for binary outcomes (i.e. short vs. long-term survival) and a small subset of genes whose expression values can be used to predict survival time is selected. Following, a new statistical methodology is developed for predicting time-to-death outcomes using Bayesian ensemble trees. Due to a large heterogeneity observed within prognostic classes obtained by the Random Forest model, prediction can be improved by relating time-to-death with gene expression profile directly. We propose a Bayesian ensemble model for survival prediction which is appropriate for high-dimensional data such as gene expression data. Our approach is based on the ensemble "sum-of-trees" model which is flexible to incorporate additive and interaction effects between genes. We specify a fully Bayesian hierarchical approach and illustrate our methodology for the CPH, Weibull, and AFT survival models. We overcome the lack of conjugacy using a latent variable formulation to model the covariate effects which decreases computation time for model fitting. Also, our proposed models provides a model-free way to select important predictive prognostic markers based on controlling false discovery rates. We compare the performance of our methods with baseline reference survival methods and apply our methodology to an unpublished data set of brain tumor survival times and gene expression data, selecting genes potentially related to the development of the disease under study. A closing discussion compares results obtained by Random Forest and Bayesian ensemble methods under the biological/clinical perspectives and highlights the statistical advantages and disadvantages of the new methodology in the context of DNA microarray data analysis.

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Prostate cancer is the second leading cause of male cancer-related deaths in the United States. Interestingly, prostate cancer preferentially metastasizes to skeletal tissue. Once in the bone microenvironment, advanced prostate cancer becomes highly resistant to therapeutic modalities. Several factors, such as extracellular matrix (ECM) components, have been implicated in the spread and propagation of prostatic carcinoma. In these studies, we have utilized the PC3 cell line, derived from a human bone metastasis, to investigate the influence of the predominant bone ECM protein, type I collagen, on prostate cancer cell proliferation and gene expression. We have also initiated the design and production of ribozymes to specific gene targets that may influence prostate cancer bone metastasis. ^ Our results demonstrate that PC3 cells rapidly adhere and spread on collagen I to a greater degree than on fibronectin (FN) or poly-L-lysine (PLL). Flow cytometry analysis reveals the presence of the α1, α2 and α3 collagen binding integrin subunits. The use of antibody function blocking studies reveals that PC3 cells can utilize α2β 1 and α3β1 integrins to adhere to collagen I. Once plated on collagen I, the cells exhibit increased rates of proliferation compared with cells plated on FN or tissue culture plastic. Additionally, cells plated on collagen I show increased expression of proteins associated with progression through G1 phase of the cell cycle. Inhibitor studies point to a role for phosphatidylinositol 3-kinase (PI3K), MAP kinase (MAPK), and p70 S6 kinase in collagen I-mediated PC3 cell proliferation and cyclin D1 expression. To further characterize the effect of type I collagen on prostate cancer bone metastasis, we utilized a cDNA microarray strategy to monitor type I collagen-mediated changes in gene expression. Results of this analysis revealed a gene expression profile reflecting the increased proliferation occurring on type I collagen. Microarray analysis also revealed differences in the expression of specific gene targets that may impact on prostate cancer metastasis to bone. ^ As a result of our studies on the interaction of prostate cancer cells and the skeletal ECM, we sought to develop novel molecular tools for future gene therapy of functional knockdown experiments. To this end, we developed a series of ribozymes directed against the α2 integrin and at osteopontin, a protein implicated in the metastasis of various cancers, including prostate. These ribozymes should facilitate the future study of the mechanism of prostate cancer cell proliferation, and disease progression occurring at sites of skeletal metastasis where a type I collagen-based environment predominates. ^ Together these studies demonstrate the involvement of bone ECM proteins on prostate cancer cell proliferation and suggest that they may play a significant role on the growth of prostate metastases once in the bone microenvironment. ^

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Helper-dependent adenoviral vectors deleted of all viral coding sequences have shown an excellent gene expression profile in a variety of animal models, as well as a reduced toxicity after systemic delivery. What is still unclear is whether long-term expression and therapeutic dosages of these vectors can be obtained also in the presence of a preexisting immunity to adenovirus, a condition found in a high proportion of the adult human population. In this study we performed intramuscular delivery of helper-dependent vectors carrying mouse erythropoietin as a marker transgene. We found that low doses of helper-dependent adenoviral vectors can direct long-lasting gene expression in the muscles of fully immunocompetent mice. The best performance—i.e., 100% of treated animals showing sustained expression after 4 months—was achieved with the latest generation helper-dependent backbones, which replicate and package at high efficiency during vector propagation. Moreover, efficient and prolonged transgene expression after intramuscular injection was observed with limited vector load also in animals previously immunized against the same adenovirus serotype. These data suggest that human gene therapy by intramuscular delivery of helper-dependent adenoviral vectors is feasible.

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Plant reproduction depends on the concerted activation of many genes to ensure correct communication between pollen and pistil. Here, we queried the whole transcriptome of Arabidopsis (Arabidopsis thaliana) in order to identify genes with specific reproductive functions. We used the Affymetrix ATH1 whole genome array to profile wild-type unpollinated pistils and unfertilized ovules. By comparing the expression profile of pistils at 0.5, 3.5, and 8.0 h after pollination and applying a number of statistical and bioinformatics criteria, we found 1,373 genes differentially regulated during pollen-pistil interactions. Robust clustering analysis grouped these genes in 16 time-course clusters representing distinct patterns of regulation. Coregulation within each cluster suggests the presence of distinct genetic pathways, which might be under the control of specific transcriptional regulators. A total of 78% of the regulated genes were expressed initially in unpollinated pistil and/or ovules, 15% were initially detected in the pollen data sets as enriched or preferentially expressed, and 7% were induced upon pollination. Among those, we found a particular enrichment for unknown transcripts predicted to encode secreted proteins or representing signaling and cell wall-related proteins, which may function by remodeling the extracellular matrix or as extracellular signaling molecules. A strict regulatory control in various metabolic pathways suggests that fine-tuning of the biochemical and physiological cellular environment is crucial for reproductive success. Our study provides a unique and detailed temporal and spatial gene expression profile of in vivo pollen-pistil interactions, providing a framework to better understand the basis of the molecular mechanisms operating during the reproductive process in higher plants.

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Microarray data analysis is one of data mining tool which is used to extract meaningful information hidden in biological data. One of the major focuses on microarray data analysis is the reconstruction of gene regulatory network that may be used to provide a broader understanding on the functioning of complex cellular systems. Since cancer is a genetic disease arising from the abnormal gene function, the identification of cancerous genes and the regulatory pathways they control will provide a better platform for understanding the tumor formation and development. The major focus of this thesis is to understand the regulation of genes responsible for the development of cancer, particularly colorectal cancer by analyzing the microarray expression data. In this thesis, four computational algorithms namely fuzzy logic algorithm, modified genetic algorithm, dynamic neural fuzzy network and Takagi Sugeno Kang-type recurrent neural fuzzy network are used to extract cancer specific gene regulatory network from plasma RNA dataset of colorectal cancer patients. Plasma RNA is highly attractive for cancer analysis since it requires a collection of small amount of blood and it can be obtained at any time in repetitive fashion allowing the analysis of disease progression and treatment response.

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One of the putative causative genes for juvenile myoclonic epilepsy (JME) is EFHC1. We report here the expression profile and distribution of Efhc1 messenger RNA (mRNA) during mouse and rat brain development. Real-time polymerase chain reaction revealed that there is no difference in the expression of Efhc1 mRNA between right and left hemispheres in both species. In addition, the highest levels of Efhc1 mRNA were found at intra-uterine stages in mouse and in adulthood in rat. In common, there was a progressive decrease in Efhc1 expression from 1-day-old neonates to 14-day-old animals in both species. In situ hybridization studies showed that rat and mouse Efhc1 mRNAs are expressed in ependymal cells of ventricle walls. Our findings suggest that Efhc1 expression is more important during initial phases of brain development and that at this stage it could be involved in key developmental mechanisms underlying JME.