SEARCH · PubMed Health

Results for “Gene Expression Profiling”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 343 records · Page 19Linked to original sources

PubMed2006

Use of gene expression profiling to identify a novel glucocorticoid sensitivity determining gene, BMPRII.

Wide variation in glucocorticoid (Gc) sensitivity exists between individuals which may influence susceptibility to, and treatment response of, inflammatory diseases. To determine a genetic fingerprint of Gc sensitivity 100 healthy human volunteers were polarized into the 10% most Gc-sensitive and 10% most Gc-resistant following a low dose dexamethasone (0.25 mg) suppression test. Gene expression profiling of primary lymphocytes identified the 98 most significantly Gc regulated genes. These genes were used to build a subnetwork of Gc signaling, with 54 genes mapping as nodes, and 6 non-Gc regulated genes inferred as signaling nodes. Twenty four of the 98 genes showed a difference in Gc response in vitro dependent on the Gc sensitivity of their donor individuals in vivo. A predictive model was built using both partial least squares discriminate analysis and support vector machines that predicted donor glucocorticoid sensitivity with 87% accuracy. Discriminating genes included bone morphogenetic protein receptor, type II (BMPRII). Transfection studies showed that BMPRII modulated Gc action. These studies reveal a broad base of gene expression that predicts Gc sensitivity and determine a Gc signaling network in human primary T lymphocytes. Furthermore, this combined gene profiling, and functional analysis approach has identified BMPRII as a modulator of Gc signaling.

Adult↗

PubMed2002

Gene expression profiling of human aortic endothelial cells exposed to disturbed flow and steady laminar flow.

Subtraction cloning and cDNA arrays were used to compare steady-state mRNA levels in cultured human aortic endothelial cells (HAEC) exposed for up to 24 h to either high-shear (13 dyn/cm(2)) steady laminar flow (LF), an established representation of "atheroprotective" flow conditions, or low-shear (<1 dyn/cm(2)), pulsatile, nonsteady, non-unidirectional flow (disturbed flow, DF) that simulates conditions in the atherosclerosis-prone areas of the arterial circulation. More than 100 genes not previously known to be flow regulated were identified. Analysis of selected genes by quantitative RT-PCR confirmed the results obtained from the microarrays. These data demonstrate that DF is not simply the absence of LF but in fact represents a distinct biomechanical stimulus that has a profound impact upon the gene expression profile of HAEC in culture. In line with previous studies, many of the changes in mRNA levels induced by LF are atheroprotective. In contrast, DF upregulated the mRNA levels of a plethora of proatherosclerotic genes including proinflammatory, proapoptotic, and procoagulant molecules. For some of the genes whose expression was altered by DF and LF, corresponding changes in EC function (proliferation and monocyte adhesion) could be demonstrated. Specifically, the sustained upregulation of VCAM-1 and increased monocyte adhesion to EC exposed to DF was similar to that found in EC in vivo at atherosclerosis-prone regions, confirming the relevance of our model system for in vivo conditions. Distinct differences in the cellular response induced by TNFalpha and DF suggest that the effects of DF are not mediated entirely by the same signaling pathways that activate NF-kappaB. These studies demonstrate extensive and pathophysiologically relevant changes in sustained gene expression patterns in aortic EC exposed to DF compared with LF which are predicted to induce a proatherogenic EC phenotype.

Adolescent↗

PubMed2004

Classification and prediction of survival in hepatocellular carcinoma by gene expression profiling.

We analyzed global gene expression patterns of 91 human hepatocellular carcinomas (HCCs) to define the molecular characteristics of the tumors and to test the prognostic value of the expression profiles. Unsupervised classification methods revealed two distinctive subclasses of HCC that are highly associated with patient survival. This association was validated via 5 independent supervised learning methods. We also identified the genes most strongly associated with survival by using the Cox proportional hazards survival analysis. This approach identified a limited number of genes that accurately predicted the length of survival and provides new molecular insight into the pathogenesis of HCC. Tumors from the low survival subclass have strong cell proliferation and antiapoptosis gene expression signatures. In addition, the low survival subclass displayed higher expression of genes involved in ubiquitination and histone modification, suggesting an etiological involvement of these processes in accelerating the progression of HCC. In conclusion, the biological differences identified in the HCC subclasses should provide an attractive source for the development of therapeutic targets (e.g., HIF1a) for selective treatment of HCC patients. Supplementary material for this article can be found on the HEPATOLOGY Web site (http://interscience.wiley.com/jpages/0270-9139/suppmat/index.html)

Carcinoma, Hepatocellular↗

PubMed2004

Comprehensive gene expression profiling of anaplastic thyroid cancers with cDNA microarray of 25 344 genes.

Little is known about the genetic mechanisms of anaplastic thyroid cancer (ATC). This is the most virulent of all human malignancies, and it is believed to result from transformation of differentiated thyroid cancers. To identify a set of genes involved in the development of ATC, we investigated expression profiles of 11 cell lines derived from ATC using a cDNA microarray representing 25 344 genes. Semi-quantitative RT-PCR experiments carried out for some genes that had shown altered expression on the microarray verified frequent over-expression of destrin, HSPA8, stathmin, LDH-A, ATP5A1, PSMB6, B23, HDP-1 and LDH-B, and frequent under-expression of thyroglobulin, PBP and c-FES/FPS genes among the cell lines and also among ten primary ATCs. In addition to mRNA expression studies, up-regulation of GDI2, destrin and stathmin were confirmed with immunohistochemical analysis. The extensive list of genes identified provides valuable information towards understanding the development of ATC, and provides a source of possible biomarkers for diagnosis and/or molecular targets for the development of novel drugs to treat ATC.

Biomarkers, Tumor↗

PubMed2005

[Preliminary analysis of retinal gene expression profile of diabetic rat].

OBJECTIVE: Establishing the retinal gene expression profiles of non-diabetic rat and diabetic rat and comparing the profiles in order to analyze the possible genes related with diabetic retinopathy. METHODS: The whole retinal transcriptional fragments of non-diabetic rat and 8-week diabetic rat were obtained by restriction fragments differential display-PCR (RFDD-PCR). Bioinformatic analysis of retinal gene expression was performed using soft wares, including Fragment Analysis. After comparison of the expression profiles, the related gene fragments of diabetic retinopathy were initially selected as the target gene of further approach. RESULTS: A total of 3639 significant fragments were obtained. By means of more than 3-fold contrast of fluorescent intensity as the differential expression standard, the authors got 840 differential fragments, accounting for 23.08% of the expressed numbers and including 5 visual related genes, 13 excitatory neruotransmitter genes and 3 inhibitory neurotransmitter genes. At the 8th week, the expression of Rhodopsin kinase, beta-arrestin, Phosducinìrod photoreceptor cGMP-gated channel and Rpe65 as well as iGlu R1-4 were down-regulated. mGluRs and GABA-Rs were all up-regulated, whereas the expression of GlyR was unchanged. CONCLUSION: These results prompt again that the changes in retinal nervous layer of rat have occurred at an early stage of diabetes. The genes expression pattern of visual related genes and excitatory and inhibitory neurotransmitters in rat diabetic retina have been involved in neuro-dysfunctions of diabetic retina.

Animals↗

PubMed2004

Constrained clusters of gene expression profiles with pathological features.

MOTIVATION: Gene expression profiles should be useful in distinguishing variations in disease, since they reflect accurately the status of cells. The primary clustering of gene expression reveals the genotypes that are responsible for the proximity of members within each cluster, while further clustering elucidates the pathological features of the individual members of each cluster. However, since the first clustering process and the second classification step, in which the features are associated with clusters, are performed independently, the initial set of clusters may omit genes that are associated with pathologically meaningful features. Therefore, it is important to devise a way of identifying gene expression clusters that are associated with pathological features. RESULTS: We present the novel technique of 'itemset constrained clustering' (IC-Clustering), which computes the optimal cluster that maximizes the interclass variance of gene expression between groups, which are divided according to the restriction that only divisions that can be expressed using common features are allowed. This constraint automatically labels each cluster with a set of pathological features which characterize that cluster. When applied to liver cancer datasets, IC-Clustering revealed informative gene expression clusters, which could be annotated with various pathological features, such as 'tumor' and 'man', or 'except tumor' and 'normal liver function'. In contrast, the k-means method overlooked these clusters.

Algorithms↗

PubMed2004

A gene regulatory network model for cell-fate determination during Arabidopsis thaliana flower development that is robust and recovers experimental gene expression profiles.

Flowers are icons in developmental studies of complex structures. The vast majority of 250,000 angiosperm plant species have flowers with a conserved organ plan bearing sepals, petals, stamens, and carpels in the center. The combinatorial model for the activity of the so-called ABC homeotic floral genes has guided extensive experimental studies in Arabidopsis thaliana and many other plant species. However, a mechanistic and dynamical explanation for the ABC model and prevalence among flowering plants is lacking. Here, we put forward a simple discrete model that postulates logical rules that formally summarize published ABC and non-ABC gene interaction data for Arabidopsis floral organ cell fate determination and integrates this data into a dynamic network model. This model shows that all possible initial conditions converge to few steady gene activity states that match gene expression profiles observed experimentally in primordial floral organ cells of wild-type and mutant plants. Therefore, the network proposed here provides a dynamical explanation for the ABC model and shows that precise signaling pathways are not required to restrain cell types to those found in Arabidopsis, but these are rather determined by the overall gene network dynamics. Furthermore, we performed robustness analyses that clearly show that the cell types recovered depend on the network architecture rather than on specific values of the model's gene interaction parameters. These results support the hypothesis that such a network constitutes a developmental module, and hence provide a possible explanation for the overall conservation of the ABC model and overall floral plan among angiosperms. In addition, we have been able to predict the effects of differences in network architecture between Arabidopsis and Petunia hybrida.

Arabidopsis↗

PubMed2005

Differential gene expression profiling of short and long term denervated muscle.

Skeletal muscle function and viability are dependent upon intact innervation. Peripheral nerve injury and muscle denervation cause muscle atrophy. Time to re-innervation is one of the most important determinants of functional outcome. While short-term denervation can result in nearly fully reversible changes in muscle mass, prolonged denervation leads to irreversible muscle impairment from profound atrophy, myocyte death and fibrosis. We performed transcriptional profiling to identify genes that were altered in expression in short-term (1 month) and long-term (3 month) denervated muscle and validated the microarray data by RT-PCR and Western blotting. Genes controlling cell death, metabolism, proteolysis, stress responses and protein synthesis/translation were altered in expression in the denervated muscle. A differential pattern of expression of genes encoding cell cycle regulators and extracellular matrix components was identified that correlated with the development of irreversible post-denervation changes. Genes encoding mediators of protein degradation were differentially expressed between 1 and 3 month denervated muscle suggesting different signaling networks are recruited over time to induce and maintain muscle atrophy. Understanding of the timing and type of pathological processes that are triggered by denervation may allow the design of interventions that delay or protect muscle from loss of nerve function.

Animals↗

PubMed2005

Gene expression profiling in lymphoma diagnosis and research.

Gene expression profiling in the past 5 years has generated a large amount of data on a variety of malignancies. Unique gene expression signatures have been identified for the more common types of non-Hodgkin lymphoma (NHL), including clinically and biologically important subsets that have not been defined before. In addition, molecularly defined prognosticators have also been constructed for the major types of NHL and these prognosticators provide added value to the widely used International Prognostic Index. The new information should be included in our evaluation of NHL patients, especially when conducting clinical trials. Studies are ongoing to validate and refine these diagnostic and prognostic signatures and to develop platforms that are suitable for routine clinical applications. Similar studies will be performed on the less common types of NHL to complete the molecular classification of NHLs. It is also anticipated that gene expression profiling studies will lead to the identification of novel targets for the development of new therapeutic agents for NHL.

Gene Expression Profiling↗

PubMed2006

Multi-level gene expression profiles affected by thymidylate synthase and 5-fluorouracil in colon cancer.

BACKGROUND: Thymidylate synthase (TS) is a critical target for cancer chemotherapy and is one of the most extensively studied biomarkers for fluoropyrimidine-based chemotherapy. In addition to its critical role in enzyme catalysis, TS functions as an RNA binding protein to regulate the expression of its own mRNA translation and other cellular mRNAs, such as p53, at the translational level. In this study, a comprehensive gene expression analysis at the levels of both transcriptional and post-transcriptional regulation was conducted to identify response markers using human genome array with TS-depleted human colon cancer HCT-C18 (TS-) cells and HCT-C18 (TS+) cells stably transfected with the human TS cDNA expression plasmid. RESULTS: A total of 38 genes were found to be significantly affected by TS based on the expression profiles of steady state mRNA transcripts. However, based on the expression profiles of polysome associated mRNA transcripts, over 149 genes were affected by TS overexpression. This indicates that additional post-transcriptionally controlled genes can be captured with profiling polysome associated mRNA population. This unique approach provides a comprehensive overview of genes affected by TS. Additional novel post-transcriptionally regulated genes affected by 5-fluorouracil (5-FU) treatment were also discovered via similar approach. CONCLUSION: To our knowledge, this is the first time that a comprehensive gene expression profile regulated by TS and 5-FU was analyzed at the multiple steps of gene regulation. This study will provide candidate markers that can be potentially used for predicting therapeutic outcomes for fluoropyrimidine-based cancer chemotherapy.

Antimetabolites, Antineoplastic↗

PubMed2003

Gene expression profiling in prostate cancer cells with Akt activation reveals Fra-1 as an Akt-inducible gene.

To determine which genes may be regulated by Akt and participate in the transformation of cells, we have examined by microarray analyses genes turned on in the prostate cancer cell line, PC3, when Akt activity was induced. PC3 cells, which lack the lipid phosphatase PTEN, were treated overnight with a reversible inhibitor of the phosphatidylinositol 3-kinase, LY294002 (a treatment which was found to reversibly decrease Akt enzymatic activity). The inhibitor was then washed out and mRNA collected 2, 6, and 10 h later and compared by microarray analyses with mRNAs present immediately after removal of the inhibitor. One of the identified induced mRNAs, Fra-1, was further studied by transient transfections of a reporter construct containing its 5' regulatory region. This construct was found to be directly induced 4- to 5-fold by co-transfection with constitutively active Akt3 but not kinase dead Akt. The regulation by Akt3 was found to be due to two specific regions in the Fra-1 regulatory sequence which match Sp1 consensus sites. Finally, gel shift studies showed that the binding of Sp1 to one of these sites was dependent on the PI 3-kinase pathway. These results indicate that LY294002 treatment and washout is a useful method to study the activation of Akt in the context of a tumor cell. Moreover, the identification of Fra-1 as an Akt-regulated gene may have implications for the ability of Akt to transform cells since Fra-1 has been implicated in cell growth and the aggressiveness of tumors.

Aryl Hydrocarbon Hydroxylases↗

PubMed2001

Differential gene expression profiling in human brain tumors.

Gene expression profiling of three human temporal lobe brain tissue samples (normal) and four primary glioblastoma multiforme (GBM) tumors using oligonucleotide microarrays was done. Moreover, confirmation of altered expression was performed by whole cell patch clamp, immunohistochemical staining, and RT-PCR. Our results identified several ion and solute transport-related genes, such as N-methyl-d-aspartate (NMDA) receptors, alpha-amino-3-hydroxy-5-methyl-4-isoxazole propionate (AMPA)-2 receptors, GABA(A) receptor subunits alpha3, beta1, beta2, and beta3, the glutamate transporter, the glutamate/aspartate transporter II, the potassium channel K(V)2.1, hK(V)beta3, and the sodium/proton exchanger 1 (NHE-1), that are all downregulated in the tumors compared with the normal tissues. In contrast, aquaporin-1, possibly aquaporins-3 and -5, and GLUT-3 message appeared upregulated in the tumors. Our results also confirmed previous work showing that osteopontin, nicotinamide N-methyltransferase, murine double minute 2 (MDM2), and epithelin (granulin) are upregulated in GBMs. We also demonstrate for the first time that the cytokine and p53 binding protein, macrophage migration inhibitory factor (MIF), appears upregulated in GBMs. These results indicate that the modulation of ion and solute transport genes and heretofore unsuspected cytokines (i.e., MIF) may have profound implications for brain tumor cell biology and thus may identify potential useful therapeutic targets in GBMs.

Aquaporin 1↗

PubMed2003

Multiclass cancer classification using gene expression profiling and probabilistic neural networks.

Gene expression profiling by microarray technology has been successfully applied to classification and diagnostic prediction of cancers. Various machine learning and data mining methods are currently used for classifying gene expression data. However, these methods have not been developed to address the specific requirements of gene microarray analysis. First, microarray data is characterized by a high-dimensional feature space often exceeding the sample space dimensionality by a factor of 100 or more. In addition, microarray data exhibit a high degree of noise. Most of the discussed methods do not adequately address the problem of dimensionality and noise. Furthermore, although machine learning and data mining methods are based on statistics, most such techniques do not address the biologist's requirement for sound mathematical confidence measures. Finally, most machine learning and data mining classification methods fail to incorporate misclassification costs, i.e. they are indifferent to the costs associated with false positive and false negative classifications. In this paper, we present a probabilistic neural network (PNN) model that addresses all these issues. The PNN model provides sound statistical confidences for its decisions, and it is able to model asymmetrical misclassification costs. Furthermore, we demonstrate the performance of the PNN for multiclass gene expression data sets. Here, we compare the performance of the PNN with two machine learning methods, a decision tree and a neural network. To assess and evaluate the performance of the classifiers, we use a lift-based scoring system that allows a fair comparison of different models. The PNN clearly outperformed the other models. The results demonstrate the successful application of the PNN model for multiclass cancer classification.

Artificial Intelligence↗

PubMed2006

Gene expression profile differences in left and right liver lobes from mid-gestation fetal baboons: a cautionary tale.

Interpretation of gene array data presents many potential pitfalls in adult tissues. Gene array techniques applied to fetal tissues present additional confounding pitfalls. The left lobe of the fetal liver is supplied with blood containing more oxygen than the right lobe. Since synthetic activity and cell function are oxygen dependent, we hypothesized major differences in mRNA expression between the fetal right and left liver lobes. Our aim was to demonstrate the need to evaluate RNA samples from both lobes. We performed whole genome expression profiling on left and right liver lobe RNA from six 90-day gestation baboon fetuses (term 180 days). Comparing right with left, we found 875 differentially expressed genes - 312 genes were up-regulated and 563 down-regulated. Pathways for damaged DNA binding, endonuclease activity, interleukin binding and receptor activity were up-regulated in right lobe; ontological pathways related to cell signalling, cell organization, cell biogenesis, development, intracellular transport, phospholipid metabolism, protein biosynthesis, protein localization, protein metabolism, translational regulation and vesicle mediated transport were down-regulated in right lobe. Molecular pathway analysis showed down-regulation of pathways related to heat shock protein binding, ion channel and transporter activities, oxygen binding and transporter activities, translation initiation and translation regulator activities. Genes involved in amino acid biosynthesis, lipid biosynthesis and oxygen transport were also differentially expressed. This is the first demonstration of RNA differences between the two lobes of the fetal liver. The data support the argument that a complete interpretation of gene expression in the developing liver requires data from both lobes.

Animals↗

PubMed2002

[cDNA libraries construction and screening in gene expression profiling of disease resistance in wheat].

A wheat line, Bai Nong 3217/Mardler BC5F4 with resistance to powdery mildew, was used to construct a conventional cDNA library and a suppression subtractive hybridization (SSH) cDNA library from wheat leaves inoculated by Erysiphe graminis DC. Three hundred and eighty-seven non-redundant ESTs from the conventional cDNA library and 760 ESTs from the SSH cDNA library were obtained, and the ESTs similarity analysis using BLASTn and BLASTx were conducted by comparing these ESTs with sequences in GenBank. The results showed that the redundancy of some kinds of genes such as photosynthesis related genes and ribosome related genes was higher in the conventional cDNA library but the varieties and quantities of disease resistance genes were less than those in the SSH cDNA library. The SSH cDNA library was found to have obvious advantages in gene expression profiling of disease resistance such as simple library construction procedure, rich specific DRR (disease-resistance-related) genes and decreased sequencing amount. To acquire genes that were involved in the powdery mildew resistance of wheat, hybridization with high-density dots membranes was used to screen the two libraries. The result showed that the method was relatively simple in operation, and the membranes could be used for many times. But some problems also existed with this screening method. For instance, a large amount of mRNA and radioactive isotope were needed and the hybridization procedure must be repeated several times to obtain stable hybridization results. About 54.1% function-known ESTs in the SSH cDNA library were identified to be DRR genes by screening. There were 247 clones of the SSH cDNA library that had positive signal in the repeated hybridizations with the pathogen uninfected probe. The identified DRR genes distributed in the whole procedure of powdery mildew resistance, but mainly focused on the SAR (systemic of acquired resistance).

Ascomycota↗

PubMedDate not supplied

Hepatic temporal gene expression profiling in Helicobacter hepaticus-infected A/JCr mice.

Helicobacter hepaticus infection of A/JCr mice is a model of infectious liver cancer. We monitored hepatic global gene expression profiles in H. hepaticus infected and control male A/JCr mice at 3 months, 6 months, and 1 year of age using an Affymetrix-based oligonucleotide microarray platform on the premise that a specific genetic expression signature at isolated time points would be indicative of disease status. Model based expression index comparisons generated by dChip yielded consistent profiles of differential gene expression for H. hepaticus infected male mice with progressive liver disease versus uninfected control mice within each age group. Linear discriminant analysis and principal component analysis allowed segregation of mice based on combined age and lesion status, or age alone. Up-regulation of putative tumor markers correlated with advancing hepatocellular dysplasia. Transcriptionally down-regulated genes in mice with liver lesions included those related to peroxisome proliferator, fatty acid, and steroid metabolism pathways. In conclusion, transcriptional profiling of hepatic genes documented gene expression signatures in the livers of H. hepaticus infected male A/JCr mice with chronic progressive hepatitis and preneoplastic liver lesions, complemented the histopathological diagnosis, and suggested molecular targets for the monitoring and intervention of disease progression prior to the onset of hepatocellular neoplasia.

Aging↗

PubMed2002

Prediction of compound signature using high density gene expression profiling.

DNA microarrays, used to measure the gene expression of thousands of genes simultaneously, hold promise for future application in efficient screening of therapeutic drugs. This will be aided by the development and population of a database with gene expression profiles corresponding to biological responses to exposures to known compounds whose toxicological and pathological endpoints are well characterized. Such databases could then be interrogated, using profiles corresponding to biological responses to drugs after developmental or environmental exposures. A positive correlation with an archived profile could lead to some knowledge regarding the potential effects of the tested compound or exposure. We have previously shown that cDNA microarrays can be used to generate chemical-specific gene expression profiles that can be distinguished across and within compound classes, using clustering, simple correlation, or principal component analyses. In this report, we test the hypothesis that knowledge can be gained regarding the nature of blinded samples, using an initial training set comprised of gene expression profiles derived from rat liver exposed to clofibrate, Wyeth 14,643, gemfibrozil, or phenobarbital for 24 h or 2 weeks of exposure. Highly discriminant genes were derived from our database training set using approaches including linear discriminant analysis (LDA) and genetic algorithm/K-nearest neighbors (GA/KNN). Using these genes in the analysis of coded liver RNA samples derived from 24-h, 3-day, or 2-week exposures to phenytoin, diethylhexylpthalate, or hexobarbital led to successful prediction of whether these samples were derived from livers of rats exposed to enzyme inducers or to peroxisome proliferators. This validates our initial hypothesis and lends credibility to the concept that the further development of a gene expression database for chemical effects will greatly enhance the hazard identification processes.

Algorithms↗

PubMed2005

Gene expression profiling in human cardiovascular disease.

Gene expression profiling studies in human diseases have allowed better understanding of pathophysiological processes. In addition, they may lead to the development of new clinical tools to improve diagnosis and prognosis of patients. Most of these studies have been successfully performed for human cancers. Inspired by these results, researchers in the cardiovascular field have also started using large-scale transcriptional analysis to better understand and classify human cardiovascular disease. Here we provide an overview of the literature revealing new cardiac disease markers and encouraging results for further development of the expression profiling strategy for future clinical applications in cardiology.

Calcium Signaling↗