886 resultados para Tissue Microarrays


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Background: Bio-conjugated nanoparticles are important analytical tools with emerging biological and medical applications. In this context, in situ conjugation of nanoparticles with biomolecules via laser ablation in an aqueous media is a highly promising one-step method for the production of functional nanoparticles resulting in highly efficient conjugation. Increased yields are required, particularly considering the conjugation of cost-intensive biomolecules like RNA aptamers. Results: Using a DNA aptamer directed against streptavidin, in situ conjugation results in nanoparticles with diameters of approximately 9 nm exhibiting a high aptamer surface density (98 aptamers per nanoparticle) and a maximal conjugation efficiency of 40.3%. We have demonstrated the functionality of the aptamer-conjugated nanoparticles using three independent analytical methods, including an agglomeration-based colorimetric assay, and solid-phase assays proving high aptamer activity. To demonstrate the general applicability of the in situ conjugation of gold nanoparticles with aptamers, we have transferred the method to an RNA aptamer directed against prostate-specific membrane antigen (PSMA). Successful detection of PSMA in human prostate cancer tissue was achieved utilizing tissue microarrays. Conclusions: In comparison to the conventional generation of bio-conjugated gold nanoparticles using chemical synthesis and subsequent bio-functionalization, the laser-ablation-based in situ conjugation is a rapid, one-step production method. Due to high conjugation efficiency and productivity, in situ conjugation can be easily used for high throughput generation of gold nanoparticles conjugated with valuable biomolecules like aptamers.

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Cancer is caused by a complex pattern of molecular perturbations. To understand the biology of cancer, it is thus important to look at the activation state of key proteins and signaling networks. The limited amount of available sample material from patients and the complexity of protein expression patterns make the use of traditional protein analysis methods particularly difficult. In addition, the only approach that is currently available for performing functional studies is the use of serial biopsies, which is limited by ethical constraints and patient acceptance. The goal of this work was to establish a 3-D ex vivo culture technique in combination with reverse-phase protein microarrays (RPPM) as a novel experimental tool for use in cancer research. The RPPM platform allows the parallel profiling of large numbers of protein analytes to determine their relative abundance and activation level. Cancer tissue and the respective corresponding normal tissue controls from patients with colorectal cancer were cultured ex vivo. At various time points, the cultured samples were processed into lysates and analyzed on RPPM to assess the expression of carcinoembryonic antigen (CEA) and 24 proteins involved in the regulation of apoptosis. The methodology displayed good robustness and low system noise. As a proof of concept, CEA expression was significantly higher in tumor compared with normal tissue (p<0.0001). The caspase 9 expression signal was lower in tumor tissue than in normal tissue (p<0.001). Cleaved Caspase 8 (p=0.014), Bad (p=0.007), Bim (p=0.007), p73 (p=0.005), PARP (p<0.001), and cleaved PARP (p=0.007) were differentially expressed in normal liver and normal colon tissue. We demonstrate here the feasibility of using RPPM technology with 3-D ex vivo cultured samples. This approach is useful for investigating complex patterns of protein expression and modification over time. It should allow functional proteomics in patient samples with various applications such as pharmacodynamic analyses in drug development.

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Gene expression of peripheral tissue antigens (PTAs) in stromal medullary thymic epithelial cells (mTECs) is a key process to the negative selection of autoreactive thymocytes. This phenomenon was termed ""promiscuous gene expression"" (PGE), which is partially controlled by the Aire gene. Nevertheless, reasons for the correlation of Aire and PTAs with the emergence of autoimmune diseases are largely unknown, though it may be a result of a chronological effect. Although the effect of Aire mutations in pathogenic autoimmunity is well know, it could not be a unique cause for autoimmunity. Independently of mutations, temporal deregulation of Aire expression may imbalance Aire-dependent PTAs and/or wide PGE. This deregulation may be an early warning sign for autoimmune diseases as it guarantees autoantigen representation in the thymus. To assess this hypothesis, we studied the expression levels of Aire, Aire-dependent (Ins2) and Aire-independent (Gad67 and Col2a1) PTAs using real-time-PCR of the thymic stromal cells of NOD mice during the development of autoimmune type 1 diabetes mellitus (DM-1). Wide PGE was studied by microarrays in which the PTA genes were identified through parallel CD80(+) mTEC 3.10 cell line expression profiling. The results show that Aire gene was down-regulated in young pre-autoimmune (pre-diabetic) NOD mice. PGE and specific PTA genes were down-regulated in adult autoimmune diabetic animals. These findings represent evidence indicating that chronological deregulation of genes important to negative selection may be associated with the development of an autoimmune disease (DM-1) in mice.

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The use of human brain tissue obtained at autopsy for neurochemical, pharmacological and physiological analyses is reviewed. RNA and protein samples have been found suitable for expression profiling by techniques that include RT-PCR, cDNA microarrays, western blotting, immunohistochemistry and proteomics. The rapid development of molecular biological techniques has increased the impetus for this work to be applied to studies of brain disease. It has been shown that most nucleic acids and proteins are reasonably stable post-mortem. However, their abundance and integrity can exhibit marked intra- and intercase variability, making comparisons between case-groups difficult. Variability can reveal important functional and biochemical information. The correct interpretation of neurochemical data must take into account such factors as age, gender, ethnicity, medicative history, immediate ante-mortem status, agonal state and post-mortem and post-autopsy intervals. Here we consider issues associated with the sampling of DNA, RNA and proteins using human autopsy brain tissue in relation to various ante- and post-mortem factors. We conclude that valid and practical measures of a variety of parameters may be made in human brain tissue, provided that specific factors are controlled.

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In microarray studies, the application of clustering techniques is often used to derive meaningful insights into the data. In the past, hierarchical methods have been the primary clustering tool employed to perform this task. The hierarchical algorithms have been mainly applied heuristically to these cluster analysis problems. Further, a major limitation of these methods is their inability to determine the number of clusters. Thus there is a need for a model-based approach to these. clustering problems. To this end, McLachlan et al. [7] developed a mixture model-based algorithm (EMMIX-GENE) for the clustering of tissue samples. To further investigate the EMMIX-GENE procedure as a model-based -approach, we present a case study involving the application of EMMIX-GENE to the breast cancer data as studied recently in van 't Veer et al. [10]. Our analysis considers the problem of clustering the tissue samples on the basis of the genes which is a non-standard problem because the number of genes greatly exceed the number of tissue samples. We demonstrate how EMMIX-GENE can be useful in reducing the initial set of genes down to a more computationally manageable size. The results from this analysis also emphasise the difficulty associated with the task of separating two tissue groups on the basis of a particular subset of genes. These results also shed light on why supervised methods have such a high misallocation error rate for the breast cancer data.

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DNA-binding proteins mediate a variety of crucial molecular functions, such as transcriptional regulation and chromosome maintenance, replication and repair, which in turn control cell division and differentiation. The roles of these proteins in disease are currently being investigated using microarray-based approaches. However, these assays can be difficult to adapt to routine diagnosis of complex diseases such as cancer. Here, we review promising alternative approaches involving protein-binding microarrays (PBMs) that probe the interaction of proteins from crude cell or tissue extracts with large collections of synthetic or natural DNA sequences. Recent studies have demonstrated the use of these novel PBM approaches to provide rapid and unbiased characterization of DNA-binding proteins as molecular markers of disease, for example cancer progression or infectious diseases.

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This study demonstrates that the expression profile of cholesteatoma is similar to a metastatic tumour and chronically inflamed tissue. Based on the investigated profiles we present novel protein-protein interaction and signal transduction networks, which include cholesteatoma-regulated transcripts and may be of great value for drug targeting and therapy development.

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It has been postulated that noncoding RNAs (ncRNAs) are involved in the posttranscriptional control of gene expression, and may have contributed to the emergence of the complex attributes observed in mammalians. We show here that the complement of ncRNAs expressed from intronic regions of the human and mouse genomes comprises at least 78,147 and 39,660 transcriptional units, respectively. To identify conserved intronic sequences expressed in both humans and mice, we used custom-designed human cDNA microarrays to separately interrogate RNA from mouse and human liver, kidney, and prostate tissues. An overlapping tissue expression signature was detected for both species, comprising 198 transcripts; among these, 22 RNAs map to intronic regions with evidence of evolutionary conservation in humans and mice. Transcription of selected human-mouse intronic ncRNAs was confirmed using strand-specific RT-PCR. Altogether, these results support an evolutionarily conserved role of intronic ncRNAs in human and mouse, which are likely to be involved in the fine tuning of gene expression regulation in different mammalian tissues. (C) 2008 Elsevier Inc. All rights reserved.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Abstract Background Spotted cDNA microarrays generally employ co-hybridization of fluorescently-labeled RNA targets to produce gene expression ratios for subsequent analysis. Direct comparison of two RNA samples in the same microarray provides the highest level of accuracy; however, due to the number of combinatorial pair-wise comparisons, the direct method is impractical for studies including large number of individual samples (e.g., tumor classification studies). For such studies, indirect comparisons using a common reference standard have been the preferred method. Here we evaluated the precision and accuracy of reconstructed ratios from three indirect methods relative to ratios obtained from direct hybridizations, herein considered as the gold-standard. Results We performed hybridizations using a fixed amount of Cy3-labeled reference oligonucleotide (RefOligo) against distinct Cy5-labeled targets from prostate, breast and kidney tumor samples. Reconstructed ratios between all tissue pairs were derived from ratios between each tissue sample and RefOligo. Reconstructed ratios were compared to (i) ratios obtained in parallel from direct pair-wise hybridizations of tissue samples, and to (ii) reconstructed ratios derived from hybridization of each tissue against a reference RNA pool (RefPool). To evaluate the effect of the external references, reconstructed ratios were also calculated directly from intensity values of single-channel (One-Color) measurements derived from tissue sample data collected in the RefOligo experiments. We show that the average coefficient of variation of ratios between intra- and inter-slide replicates derived from RefOligo, RefPool and One-Color were similar and 2 to 4-fold higher than ratios obtained in direct hybridizations. Correlation coefficients calculated for all three tissue comparisons were also similar. In addition, the performance of all indirect methods in terms of their robustness to identify genes deemed as differentially expressed based on direct hybridizations, as well as false-positive and false-negative rates, were found to be comparable. Conclusion RefOligo produces ratios as precise and accurate as ratios reconstructed from a RNA pool, thus representing a reliable alternative in reference-based hybridization experiments. In addition, One-Color measurements alone can reconstruct expression ratios without loss in precision or accuracy. We conclude that both methods are adequate options in large-scale projects where the amount of a common reference RNA pool is usually restrictive.

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The cDNA microarray is one technological approach that has the potential to accurately measure changes in global mRNA expression levels. We report an assessment of an optimized cDNA microarray platform to generate accurate, precise and reliable data consistent with the objective of using microarrays as an acquisition platform to populate gene expression databases. The study design consisted of two independent evaluations with 70 arrays from two different manufactured lots and used three human tissue sources as samples: placenta, brain and heart. Overall signal response was linear over three orders of magnitude and the sensitivity for any element was estimated to be 2 pg mRNA. The calculated coefficient of variation for differential expression for all non-differentiated elements was 12–14% across the entire signal range and did not vary with array batch or tissue source. The minimum detectable fold change for differential expression was 1.4. Accuracy, in terms of bias (observed minus expected differential expression ratio), was less than 1 part in 10 000 for all non-differentiated elements. The results presented in this report demonstrate the reproducible performance of the cDNA microarray technology platform and the methods provide a useful framework for evaluating other technologies that monitor changes in global mRNA expression.

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We have constructed cDNA microarrays for soybean (Glycine max L. Merrill), containing approximately 4,100 Unigene ESTs derived from axenic roots, to evaluate their application and utility for functional genomics of organ differentiation in legumes. We assessed microarray technology by conducting studies to evaluate the accuracy of microarray data and have found them to be both reliable and reproducible in repeat hybridisations. Several ESTs showed high levels (>50 fold) of differential expression in either root or shoot tissue of soybean. A small number of physiologically interesting, and differentially expressed sequences found by microarray analysis were verified by both quantitative real-time RT-PCR and Northern blot analysis. There was a linear correlation (r(2) = 0.99, over 5 orders of magnitude) between microarray and quantitative real-time RT-PCR data. Microarray analysis of soybean has enormous potential not only for the discovery of new genes involved in tissue differentiation and function, but also to study the expression of previously characterised genes, gene networks and gene interactions in wild-type, mutant or transgenic; plants.

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Background: Although there is evidence that post-mortem interval (PMI) is not a major contributor to reduced overall RNA integrity, it may differentially affect a subgroup of gene transcripts that are susceptible to PMI-related degradation. This would particularly have ramifications for microarray studies that include a broad spectrum of genes. Method: Brain tissue was removed from adult mice at 0, 6, 12, 18, 24,36 and 48 h post-mortem. RNA transcript abundance was measured by hybridising RNA from the zero time point with test RNA from each PMI time point, and differential gene expression was assessed using cDNA microarrays. Sequence and ontological analyses were performed on the group of RNA transcripts showing greater than two-fold reduction. Results: Increasing PMI was associated with decreased tissue pH and increased RNA degradation as indexed by 28S/18S ribosomal RNA ratio. Approximately 12% of mRNAs detected on the arrays displayed more than a two-fold decrease in abundance by 48 It post-mortem. An analysis of nucleotide composition provided evidence that transcripts with the AUUUA motif in the 3' untranslated region (3'UTR) were more susceptible to PMI-related RNA degradation, compared to transcripts not carrying the 3'UTR AUUUA motif. Consistent with this finding, ontological analysis showed transcription factors and elements to be over-represented in the group of transcripts susceptible to degradation. Conclusion: A subgroup of mammalian mRNA transcripts are particularly susceptible to PMI-related degradation, and as a group, they are more likely to carry the YUTR AUUUA motif. PMI should be controlled for in human and animal model post-mortem brain studies, particularly those including a broad spectrum of mRNA transcripts. (c) 2005 Elsevier B.V. All rights reserved.

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This paper considers a model-based approach to the clustering of tissue samples of a very large number of genes from microarray experiments. It is a nonstandard problem in parametric cluster analysis because the dimension of the feature space (the number of genes) is typically much greater than the number of tissues. Frequently in practice, there are also clinical data available on those cases on which the tissue samples have been obtained. Here we investigate how to use the clinical data in conjunction with the microarray gene expression data to cluster the tissue samples. We propose two mixture model-based approaches in which the number of components in the mixture model corresponds to the number of clusters to be imposed on the tissue samples. One approach specifies the components of the mixture model to be the conditional distributions of the microarray data given the clinical data with the mixing proportions also conditioned on the latter data. Another takes the components of the mixture model to represent the joint distributions of the clinical and microarray data. The approaches are demonstrated on some breast cancer data, as studied recently in van't Veer et al. (2002).

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Crohn's disease (CD) is associated with complex pathogenic pathways involving defects in apoptosis mechanisms. Recently, mesenteric adipose tissue (MAT) has been associated with CD ethiopathology, since adipose thickening is detected close to the affected intestinal area. However, the potential role of altered apoptosis in MAT of CD has not been addressed. To evaluate apoptosis in the intestinal mucosa and MAT of patients with CD. Samples of intestinal mucosa and MAT from patients with ileocecal CD and from non-inflammatory bowel diseases patients (controls) were studied. Apoptosis was assessed by TUNEL assay and correlated with the adipocytes histological morphometric analysis. The transcriptional and protein analysis of selected genes and proteins related to apoptosis were determined. TUNEL assay showed fewer apoptotic cells in CD, when compared to the control groups, both in the intestinal mucosa and in MAT. In addition, the number of apoptotic cells (TUNEL) correlated significantly with the area and perimeter of the adipose cells in MAT. Transcriptomic and proteomic analysis reveal a significantly lower transcript and protein levels of Bax in the intestinal mucosa of CD, compared to the controls; low protein levels of Bax were found localized in the lamina propria and not in the epithelium of this tissue. Furthermore, higher level of Bcl-2 and low level of Caspase 3 were seen in the MAT of CD patients. The defective apoptosis in MAT may explain the singular morphological characteristics of this tissue in CD, which may be implicated in the pathophysiology of the disease.