992 resultados para Gene expression vectors


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Background: Biomineralization is a process encompassing all mineral containing tissues produced within an organism. One of the most dynamic examples of this process is the formation of the mollusk shell, comprising a variety of crystal phases and microstructures. The organic component incorporated within the shell is said to dictate this architecture. However general understanding of how this process is achieved remains ambiguous. The mantle is a conserved organ involved in shell formation throughout molluscs. Specifically the mantle is thought to be responsible for secreting the protein component of the shell. This study employs molecular approaches to determine the spatial expression of genes within the mantle tissue to further the elucidation of the shell biomineralization. Results: A microarray platform was custom generated (PmaxArray 1.0) from the pearl oyster Pinctada maxima. PmaxArray 1.0 consists of 4992 expressed sequence tags (ESTs) originating from mantle tissue. This microarray was used to analyze the spatial expression of ESTs throughout the mantle organ. The mantle was dissected into five discrete regions and analyzed for differential gene expression with PmaxArray 1.0. Over 2000 ESTs were determined to be differentially expressed among the tissue sections, identifying five major expression regions. In situ hybridization validated and further localized the expression for a subset of these ESTs. Comparative sequence similarity analysis of these ESTs revealed a number of the transcripts were novel while others showed significant sequence similarities to previously characterized shell related genes.

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Background In contrast to pluripotent embryonic stem cells, adult stem cells have been considered to be multipotent, being somewhat more restricted in their differentiation capacity and only giving rise to cell types related to their tissue of origin. Several studies, however, have reported that bone marrow-derived mesenchymal stromal cells (MSCs) are capable of transdifferentiating to neural cell types, effectively crossing normal lineage restriction boundaries. Such reports have been based on the detection of neural-related proteins by the differentiated MSCs. In order to assess the potential of human adult MSCs to undergo true differentiation to a neural lineage and to determine the degree of homogeneity between donor samples, we have used RT-PCR and immunocytochemistry to investigate the basal expression of a range of neural related mRNAs and proteins in populations of non-differentiated MSCs obtained from 4 donors. Results The expression analysis revealed that several of the commonly used marker genes from other studies like nestin, Enolase2 and microtubule associated protein 1b (MAP1b) are already expressed by undifferentiated human MSCs. Furthermore, mRNA for some of the neural-related transcription factors, e.g. Engrailed-1 and Nurr1 were also strongly expressed. However, several other neural-related mRNAs (e.g. DRD2, enolase2, NFL and MBP) could be identified, but not in all donor samples. Similarly, synaptic vesicle-related mRNA, STX1A could only be detected in 2 of the 4 undifferentiated donor hMSC samples. More significantly, each donor sample revealed a unique expression pattern, demonstrating a significant variation of marker expression. Conclusion The present study highlights the existence of an inter-donor variability of expression of neural-related markers in human MSC samples that has not previously been described. This donor-related heterogeneity might influence the reproducibility of transdifferentiation protocols as well as contributing to the ongoing controversy about differentiation capacities of MSCs. Therefore, further studies need to consider the differences between donor samples prior to any treatment as well as the possibility of harvesting donor cells that may be inappropriate for transplantation strategies.

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BACKGROUND: Stromal signalling increases the lateral cell adhesions of prostate epithelial cells grown in 3D culture. The aim of this study was to use microarray analysis to identify significant epithelial signalling pathways and genes in this process. METHODS: Microarray analysis was used to identify genes that were differentially expressed when epithelial cells were grown in 3D Matrigel culture with stromal co-culture compared to without stroma. Two culture models were employed: primary epithelial cells (ten samples) and an epithelial cell line (three experiments). A separate microarray analysis was performed on each model system and then compared to identify tissue-relevant genes in a cell line model. RESULTS: TGF beta signalling was significantly ranked for both model systems and in both models the TGF beta signalling gene SOX4 was significantly down regulated. Analysis of all differentially expressed genes to identify genes that were common to both models found several morphology related gene clusters; actin binding (DIAPH2, FHOD3, ABLIM1, TMOD4, MYH10), GTPase activator activity (BCR, MYH10), cytoskeleton (MAP2, MYH10, TMOD4, FHOD3), protein binding (ITGA6, CD44), proteinaceous extracellular matrix (NID2, CILP2), ion channel/ ion transporter activity (CACNA1C, CACNB2, KCNH2, SLC8A1, SLC39A9) and genes associated with developmental pathways (POFUT1, FZD2, HOXA5, IRX2, FGF11, SOX4, SMARCC1). CONCLUSIONS: In 3D prostate cultures, stromal cells increase lateral epithelial cell adhesions. We show that this morphological effect is associated with gene expression changes to TGF beta signalling, cytoskeleton and anion activity.

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BACKGROUND: Broccoli consumption has been associated with a reduced risk of prostate cancer. Isothiocyanates (ITCs) derived from glucosinolates that accumulate in broccoli are dietary compounds that may mediate these health effects. Sulforaphane (SF, 4-methylsulphinylbutyl ITC) derives from heading broccoli (calabrese) and iberin (IB, 3-methylsulphinypropyl ITC) from sprouting broccoli. While there are many studies regarding the biological activity of SF, mainly undertaken with cancerous cells, there are few studies associated with IB. METHODS: Primary epithelial and stromal cells were derived from benign prostatic hyperplasia tissue. Affymetrix U133 Plus 2.0 whole genome arrays were used to compare global gene expression between these cells, and to quantify changes in gene expression following exposure to physiologically appropriate concentrations of SF and IB. Ontology and pathway analyses were used to interpret results. Changes in expression of a subset of genes were confirmed by real-time RT-PCR. RESULTS: Global gene expression profiling identified epithelial and stromal-specific gene expression profiles. SF induced more changes in epithelial cells, whereas IB was more effective in stromal cells. Although IB and SF induced different changes in gene expression in both epithelial and stromal cells, these were associated with similar pathways, such as cell cycle and detoxification. Both ITCs increased expression of PLAGL1, a tumor suppressor gene, in stromal cells and suppressed expression of the putative tumor promoting genes IFITM1, CSPG2, and VIM in epithelial cells. CONCLUSION: These data suggest that IB and SF both alter genes associated with cancer prevention, and IB should be investigated further as a potential chemopreventative agent.

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Destruction of cancer cells by genetically modified viral and nonviral vectors has been the aim of many research programs. The ability to target cytotoxic gene therapies to the cells of interest is an essential prerequisite, and the treatment has always had the potential to provide better and more long-lasting therapy than existing chemotherapies. However, the potency of these infectious agents requires effective testing systems, in which hypotheses can be explored both in vitro and in vivo before the establishment of clinical trials in humans. The real prospect of off-target effects should be eliminated in the preclinical stage, if current prejudices against such therapies are to be overcome. In this review we have set out, using adenoviral vectors as a commonly used example, to discuss some of the key parameters required to develop more effective testing, and to critically assess the current cellular models for the development and testing of prostate cancer biotherapy. Only by developing models that more closely mirror human tissues will we be able to translate literature publications into clinical trials and hence into acceptable alternative treatments for the most commonly diagnosed cancer in humans.

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Background Accumulated biological research outcomes show that biological functions do not depend on individual genes, but on complex gene networks. Microarray data are widely used to cluster genes according to their expression levels across experimental conditions. However, functionally related genes generally do not show coherent expression across all conditions since any given cellular process is active only under a subset of conditions. Biclustering finds gene clusters that have similar expression levels across a subset of conditions. This paper proposes a seed-based algorithm that identifies coherent genes in an exhaustive, but efficient manner. Methods In order to find the biclusters in a gene expression dataset, we exhaustively select combinations of genes and conditions as seeds to create candidate bicluster tables. The tables have two columns: (a) a gene set, and (b) the conditions on which the gene set have dissimilar expression levels to the seed. First, the genes with less than the maximum number of dissimilar conditions are identified and a table of these genes is created. Second, the rows that have the same dissimilar conditions are grouped together. Third, the table is sorted in ascending order based on the number of dissimilar conditions. Finally, beginning with the first row of the table, a test is run repeatedly to determine whether the cardinality of the gene set in the row is greater than the minimum threshold number of genes in a bicluster. If so, a bicluster is outputted and the corresponding row is removed from the table. Repeating this process, all biclusters in the table are systematically identified until the table becomes empty. Conclusions This paper presents a novel biclustering algorithm for the identification of additive biclusters. Since it involves exhaustively testing combinations of genes and conditions, the additive biclusters can be found more readily.

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The goal of improving systemic treatment of breast cancers is to evolve from treating every patient with non-specific cytotoxic chemotherapy/hormonal therapy, to a more individually-tailored direct treatment. Although anatomic staging and histological grade are important prognostic factors, they often fail to predict the clinical course of this disease. This study aimed to develop a gene expression profile associated with breast cancers of differing grades. We extracted mRNA from FFPE archival breast IDC tissue samples (Grades I–III), including benign tumours. Affymetrix GeneChip� Human Genome U133 Plus 2.0 Arrays were used to determine gene expression profiles and validated by Q-PCR. IHC was used to detect the AXIN2 protein in all tissues. From the array data, an independent group t-test revealed that 178 genes were significantly (P B 0.01) differentially expressed between three grades of malignant breast tumours when compared to benign tissues. From these results, eight genes were significantly differentially expressed in more than one comparison group and are involved in processes implicated in breast cancer development and/or progression. The two most implicated candidates genes were CLD10 and ESPTI1 as their gene expression profile from the microarray analysis was replicated in Q-PCR analyses of the original tumour samples as well as in an extended population. The IHC revealed a significant association between AXIN2 protein expression and ER status. It is readily acknowledged and established that significant differences exist in gene expression between different cancer grades. Expansion of this approach may lead to an improved ability to discriminate between cancer grade and other pathological factors.

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Migraine is a debilitating neurovascular disorder, with a substantial genetic component. The exact cause of a migraine attack is unknown; however cortical hyperexcitability is thought to play a role. As Gamma-aminobutyric Acid (GABA) is the major inhibitory neurotransmitter in the brain, malfunctioning of this system may be a cause of the hyperexcitability. To date, there has been limited research examining the gene expression or genetics of GABA receptors in relation to migraine. The aim of our study was to determine if GABA receptors play a role in migraine by investigating their gene expression using profile in migraine affected individuals and non-affected controls by Q-PCR. Gene expression of GABA(A) receptor subunit isoforms (GABRA3, GABRB3, GABRQ) and GABA(B) receptor 2 (GABBR2) was quantified in mRNA obtained from peripheral blood leukocytes from 28 migraine subjects and 22 healthy control subjects. Analysis of results showed that two of the tested genes, GABRA3 and GABBR2, were significantly down regulated in migraineurs (P=0.018; P=0.017), compared to controls. Results from the other tested genes did not show significant gene expression variation. The results indicate that there may be specific GABA receptor gene expression variation in migraine, particularly involving the GABRA3 and GABBR2 genes. This study also identifies GABRA3 and GABBR2 as potential biomarkers to select migraineurs that may be more responsive to GABA agonists with future investigations in this area warranted.

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This thesis developed and applied Bayesian models for the analysis of survival data. The gene expression was considered as explanatory variables within the Bayesian survival model which can be considered the new contribution in the analysis of such data. The censoring factor that is inherent of survival data has also been addressed in terms of its impact on the fitting of a finite mixture of Weibull distribution with and without covariates. To investigate this, simulation study were carried out under several censoring percentages. Censoring percentage as high as 80% is acceptable here as the work involved high dimensional data. Lastly the Bayesian model averaging approach was developed to incorporate model uncertainty in the prediction of survival.

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Multiple sclerosis (MS) is a serious neurological disorder affecting young Caucasian individuals, usually with an age of onset at 18 to 40 years old. Females account for approximately 60x of MS cases and the manifestation and course of the disease is highly variable from patient to patient. The disorder is characterised by the development of plaques within the central nervous system (CNS). Many gene expression studies have been undertaken to look at the specific patterns of gene transcript levels in MS. Human tissues and experimental mice were used in these gene-profiling studies and a very valuable and interesting set of data has resulted from these various expression studies. In general, genes showing variable expression include mainly immunological and inflammatory genes, stress and antioxidant genes, as well as metabolic and central nervous system markers. Of particular interest are a number of genes localised to susceptible loci previously shown to be in linkage with MS. However due to the clinical complexity of the disease, the heterogeneity of the tissues used in expression studies, as well as the variable DNA chips/membranes used for the gene profiling, it is difficult to interpret the available information. Although this information is essential for the understanding of the pathogenesis of MS, it is difficult to decipher and define the gene pathways involved in the disorder. Experiments in gene expression profiling in MS have been numerous and lists of candidates are now available for analysis. Researchers have investigated gene expression in peripheral mononuclear white blood cells (PBMCs), in MS animal models Experimental Allergic Encephalomyelitis (EAE) and post mortem MS brain tissues. This review will focus on the results of these studies.

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Background Members of the matrix metalloproteinase (MMP) family of proteases are required for the degradation of the basement membrane and extracellular matrix in both normal and pathological conditions. In vitro, MT1-MMP (MMP-14, membrane type-1-MMP) expression is higher in more invasive human breast cancer (HBC) cell lines, whilst in vivo its expression has been associated with the stroma surrounding breast tumours. MMP-1 (interstitial collagenase) has been associated with MDA-MB-231 invasion in vitro, while MMP-3 (stromelysin-1) has been localised around invasive cells of breast tumours in vivo. As MMPs are not stored intracellularly, the ability to localise their expression to their cells of origin is difficult. Methods We utilised the unique in situ-reverse transcription-polymerase chain reaction (IS-RT-PCR) methodology to localise the in vitro and in vivo gene expression of MT1-MMP, MMP-1 and MMP-3 in human breast cancer. In vitro, MMP induction was examined in the MDA-MB-231 and MCF-7 HBC cell lines following exposure to Concanavalin A (Con A). In vivo, we examined their expression in archival paraffin embedded xenografts derived from a range of HBC cell lines of varied invasive and metastatic potential. Mouse xenografts are heterogenous, containing neoplastic human parenchyma with mouse stroma and vasculature and provide a reproducible in vivo model system correlated to the human disease state. Results In vitro, exposure to Con A increased MT1-MMP gene expression in MDA-MB-231 cells and decreased MT1-MMP gene expression in MCF-7 cells. MMP-1 and MMP-3 gene expression remained unchanged in both cell lines. In vivo, stromal cells recruited into each xenograft demonstrated differences in localised levels of MMP gene expression. Specifically, MDA-MB-231, MDA-MB-435 and Hs578T HBC cell lines are able to influence MMP gene expression in the surrounding stroma. Conclusion We have demonstrated the applicability and sensitivity of IS-RT-PCR for the examination of MMP gene expression both in vitro and in vivo. Induction of MMP gene expression in both the epithelial tumour cells and surrounding stromal cells is associated with increased metastatic potential. Our data demonstrate the contribution of the stroma to epithelial MMP gene expression, and highlight the complexity of the role of MMPs in the stromal-epithelial interactions within breast carcinoma.

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To examine matrix metalloproteinase (MMP) and tissue inhibitor of metalloproteinases (TIMP) mRNA levels in archival breast cancer biopsies, we employed microdissection to separate tumour tissue from the surrounding breast tissue, or stroma and RT-PCR to determine gross qualitative and small quantitative differences in the patterns of expression. In this study, a significant correlation (p < 0.05, by Mann-Whitney U analysis) between TIMP-2 expression and lymph node involvement was identified, while MMP-11 and TIMP-1 expression patterning also significantly (p < 0.05) differed between those tumours showing calcification and those that did not. When compared by Spearmans’ ρ correlation analysis, a significant association (p < 0.05, ρ = 0.404) was identified in the pattern of MMP-2 and MMP-9 gene expression. In this study, the use of microdissection and a systematic strategy of RT-PCR analysis have allowed us to investigate localized MMP and MMP inhibitor expression within breast tumours. We have identified patterns of gene expression that may further reveal aspects of breast carcinogenesis, and a robust method for examining changes in clinically important genes using archival biopsies and across stroma-tumour boundaries.

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Multiple sclerosis (MS) is a complex autoimmune disorder of the CNS with both genetic and environmental contributing factors. Clinical symptoms are broadly characterized by initial onset, and progressive debilitating neurological impairment. In this study, RNA from MS chronic active and MS acute lesions was extracted, and compared with patient matched normal white matter by fluorescent cDNA microarray hybridization analysis. This resulted in the identification of 139 genes that were differentially regulated in MS plaque tissue compared to normal tissue. Of these, 69 genes showed a common pattern of expression in the chronic active and acute plaque tissues investigated (Pvalue<0.0001, ρ=0.73, by Spearman's ρ analysis); while 70 transcripts were uniquely differentially expressed (≥1.5-fold) in either acute or chronic active tissues. These results included known markers of MS such as the myelin basic protein (MBP) and glutathione S-transferase (GST) M1, nerve growth factors, such as nerve injury-induced protein 1 (NINJ1), X-ray and excision DNA repair factors (XRCC9 and ERCC5) and X-linked genes such as the ribosomal protein, RPS4X. Primers were then designed for seven array-selected genes, including transferrin (TF), superoxide dismutase 1 (SOD1), glutathione peroxidase 1 (GPX1), GSTP1, crystallin, alpha-B (CRYAB), phosphomannomutase 1 (PMM1) and tubulin β-5 (TBB5), and real time quantitative (Q)-PCR analysis was performed. The results of comparative Q-PCR analysis correlated significantly with those obtained by array analysis (r=0.75, Pvalue<0.01, by Pearson's bivariate correlation). Both chronic active and acute plaques shared the majority of factors identified suggesting that quantitative, rather than gross qualitative differences in gene expression pattern may define the progression from acute to chronic active plaques in MS.