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PubMed2006

Comparative expression profiling in primary and immortalized endothelial cells: changes in gene expression in response to hydroxy methylglutaryl-coenzyme A reductase inhibition.

Immortalized cell lines offer significant logistical advantages over primary cells when used for in-vitro studies. Immortalized cells may, however, exhibit important differences relative to their primary cell counterparts. In this study, microarrays were used to make a genome-wide comparison between primary human umbilical vein endothelial cells (HUVECs) and EA.hy926, an immortalized HUVEC cell line, in their baseline properties and in their response to inhibition of the mevalonate pathway with an inhibitor of hydroxy methylglutaryl-coenzyme A reductase (statin). HUVECs and EA.hy926 were incubated with control medium, atorvastatin, mevalonate, or a combination of atorvastatin and mevalonate for 24 h. Gene expression profiles were obtained in duplicates using Affymetrix Human Genome U133A 2.0 arrays (Santa Clara, California, USA). Probe-sets were selected according to the following criteria: a twofold or greater increase/decrease in atorvastatin-treated cells compared with untreated cells; a twofold or greater reversal of the effect of atorvastatin by combined treatment with atorvastatin and mevalonate; no significant change in gene expression in cells treated with mevalonate alone compared with untreated cells. Most genes that were expressed by untreated HUVECs, were also expressed by untreated EA.hy926 cells. EA.hy926 cells, however, constitutively expressed a large number of additional genes, many of which were related to cell cycle control and apoptosis. Atorvastatin induced differential expression (> or = twofold) of 103 genes in HUVECs (10 up, 93 down) and 466 genes in EA.hy926 cells (198 up, 268 down). Applying the above selection criteria, thrombomodulin and tissue plasminogen activator were up-regulated in both cell types, whereas, connective tissue growth factor, thrombospondin-1, and cysteine-rich angiogenic inducer 61 were down-regulated. In conclusion, EA.hy926 cells retain most of the characteristics of endothelial cells under baseline conditions as well as after treatment with atorvastatin. It is necessary, however, to carefully select and validate changes in genes that are the focus of studies when using EA.hy926 cells. While this cell line is highly useful in studies on some genes, including genes encoding molecules involved in regulating thrombohemorrhagic homeostasis, they appear to be less suited for studies focused on other genes, particularly those involved in the regulation of cell proliferation and apoptosis.

Apoptosis↗

PubMed2006

Genome-wide expression profiling reveals EBV-associated inhibition of MHC class I expression in nasopharyngeal carcinoma.

To identify the molecular mechanisms by which EBV-associated epithelial cancers are maintained, we measured the expression of essentially all human genes and all latent EBV genes in a collection of 31 laser-captured, microdissected nasopharyngeal carcinoma (NPC) tissue samples and 10 normal nasopharyngeal tissues. Global gene expression profiles clearly distinguished tumors from normal healthy epithelium. Expression levels of six viral genes (EBNA1, EBNA2, EBNA3A, EBNA3B, LMP1, and LMP2A) were correlated among themselves and strongly inversely correlated with the expression of a large subset of host genes. Among the human genes whose inhibition was most strongly correlated with increased EBV gene expression were multiple MHC class I HLA genes involved in regulating immune response via antigen presentation. The association between EBV gene expression and inhibition of MHC class I HLA expression implies that antigen display is either directly inhibited by EBV, facilitating immune evasion by tumor cells, and/or that tumor cells with inhibited presentation are selected for their ability to sustain higher levels of EBV to take maximum advantage of EBV oncogene-mediated tumor-promoting actions. Our data clearly reflect such tumor promotion, showing that deregulation of key proteins involved in apoptosis (BCL2-related protein A1 and Fas apoptotic inhibitory molecule), cell cycle checkpoints (AKIP, SCYL1, and NIN), and metastasis (matrix metalloproteinase 1) is closely correlated with the levels of EBV gene expression in NPC.

Biopsy↗

PubMedDate not supplied

Gene expression profiling of human diseases by serial analysis of gene expression.

Until recently, the approach to understanding the molecular basis of complex syndromes such as cancer, coronary artery disease, and diabetes was to study the behavior of individual genes. However, it is generally recognized that expression of a number of genes is coordinated both spatially and temporally and that this coordination changes during the development and progression of diseases. Newly developed functional genomic approaches, such as serial analysis of gene expression (SAGE) and DNA microarrays have enabled researchers to determine the expression pattern of thousands of genes simultaneously. One attractive feature of SAGE compared to microarrays is its ability to quantify gene expression without prior sequence information or information about genes that are thought to be expressed. SAGE has been successfully applied to the gene expression profiling of a number of human diseases. In this review, we will first discuss SAGE technique and contrast it to microarray. We will then highlight new biological insights that have emerged from its application to the study of human diseases.

Gene Expression↗

PubMed2005

Comparison of the expression profiles induced by genotoxic and nongenotoxic carcinogens in rat liver.

Application of recently developed gene expression techniques using microarrays in toxicological studies (toxicogenomics) facilitate the interpretation of a toxic compound's mode of action and may also allow the prediction of selected toxic effects based on gene expression changes. In order to test this hypothesis, we investigated whether carcinogens at doses known to induce liver tumors in the 2-year rat bioassay deregulate characteristic sets of genes in a short term in vivo study and whether these deregulated genes represent defined biological pathways. Male Wistar rats were dosed with the four nongenotoxic hepatocarcinogens methapyrilene (MPy, 60 mg/kg/day), diethylstilbestrol (DES, 10 mg/kg/day), Wy-14643 (Wy, 60 mg/kg/day), and piperonylbutoxide (PBO, 1200 mg/kg/day). After 1, 3, 7, and 14 days, the livers were taken for histopathological evaluation and for analysis of the gene expression profiles on Affymetrix RG_U34A arrays. The expression profile of the four nongenotoxic carcinogens were compared to the profiles of the four genotoxic carcinogens 2-nitrofluorene (2-NF), dimethylnitrosamine (DMN), 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK), and aflatoxin B1 (AB1) from a similar study reported previously. By using statistical and clustering tools characteristically deregulated genes were extracted and functionally classified. Distinct cellular pathways were affected by the nongenotoxic carcinogens compared to the genotoxic carcinogens which at least partly correlated with the two-stage model of carcinogenesis. Characteristic to genotoxic carcinogens were a DNA damage response and the activation of proliferative and survival signaling. Nongenotoxic carcinogens showed responses to oxidative DNA or protein damage, as well as cell cycle progression and signs of regeneration. Many of the gene alterations found with the nongenotoxic carcinogens imply compound-specific mechanisms. Although neither a single gene nor a single pathway will be sufficient to discriminate the two classes of carcinogens, it became evident that combinations of pathway-associated gene expression profiles may be used to predict a genotoxic or nongenotoxic carcinogenic potential of a compound in short-term studies.

Animals↗

PubMed2005

Efficient determination of cluster boundaries for analysis of gene expression profile data using hierarchical clustering and wavelet transform.

The existing methods for clustering of gene expression profile data either require manual inspection and other biological knowledge or require some cut-off value which can not be directly calculated from the given data set. Thus, the problem of systematic and efficient determination of cluster boundaries of clusters in gene expression profile data still remains demanding. In this context, we have developed a procedure for automatic and systematic determination of the boundaries of clusters in the hierarchical clustering of gene expression data based on the ratio of with-in class variance and between-class variance, which can be fully calculated from the given expression data. After the determination of dendrogram based on agglomerative hierarchical clustering, this ratio is used to determine the cluster boundary. Except this ratio which can be completely calculated from the given expression profile data, unlike other existing approaches, our approach does not require any manual inspection or biological knowledge. Our results are favorably comparable and in some of cases better than existing method which does not utilize prior information or manual inspection. Moreover, gene expression profile data are often contaminated with various type of noise and in order to reduce this noise content, we have also applied image enhancing technique called discrete wavelet transform. We tested a number of mother wavelet functions to smooth the noise in the gene expression data set and obtained some improvements in the quality of the results.

Algorithms↗

PubMed2003

Gene expression profiling: will it complement or replace immunophenotyping?

Gene expression profiling using DNA microarrays represents a major advance in the diagnosis of haematological malignancies; it enables the analysis of RNA expression by clonal populations of leukaemia and lymphoma cells on a genome-wide scale. Currently, flow cytometric analysis of differentiation-linked surface antigens expressed by malignant cells is essential for the accurate diagnosis and optimal therapeutic planning for patients with leukaemias and lymphomas. Given the astonishing pace of research in microarray technology, a key question for the haematopathologist is: will gene expression profiling using DNA microarrays replace immunophenotyping, or will these two technologies evolve together as complementary approaches to improve diagnosis and therapy? In this chapter, we review the technical advantages and pitfalls of each of these two approaches and provide an assessment of their differences and potentially synergistic applications.

Flow Cytometry↗

PubMed2003

Assessment of two methods for handling blood in collection tubes with RNA stabilizing agent for surveillance of gene expression profiles with high density microarrays.

Genome-wide expression studies of human blood samples in the context of epidemiologic surveillance are confronted by numerous challenges-one of the foremost being the capability to produce reliable detection of transcript levels. This led us to consider the Paxgene Blood RNA System, which consists of a stabilizing additive in an evacuated blood collection tube (PAX tube) and a sample processing kit (PAX kit). The PAX tube contains a solution that inhibits RNA degradation and gene induction as blood is drawn into the tube. The stability of RNA in PAX tubes under conditions for practical clinical applications has been determined by RT-PCR, but has not been assessed at the transcriptome level on Affymetrix microarrays. Here, we report a quality assured and controlled protocol that is capable of producing reliable gene expression profiles using the GeneChip system with RNA isolated from PAX tubes. Using this protocol, we compared quality metrics and gene-expression profiles of RNA, extracted from blood in PAX tubes that sat at room temperature for 2 h, with that of blood in PAX tubes incubated at room temperature for 9 h followed by storage at -20 degrees C for 6 days. Of numerous metrics, differences between the two handling methods were detected for the level of DNA contamination, RNA yield, and double stranded cDNA yield. Analysis of variance of gene-expression revealed small but significant differences between the handling methods. These results contribute to the determination of protocols for clinical studies and progress us towards the goal of using the transcriptome in diagnosis and surveillance.

Blood Specimen Collection↗

PubMed2000

Expression profile viewer (ExProView): a software tool for transcriptome analysis.

A software tool, Expression Profile Viewer (ExProView), for analysis of gene expression profiles derived from expressed sequence tags (ESTs) and SAGE (serial analysis of gene expression) is presented. The software visualizes a complete set of classified transcript data in a two-dimensional array of dots, a "virtual chip," in which each dot represents a known gene as characterized in the transcript databases Expressed Gene Anatomy Database or UniGene. The virtual chip display can be changed between representations of different conceptual systems for gene/protein classification and grouping. Four alternative projections are currently available: (i) cellular role, (ii) subcellular compartment, (iii) chromosome localization, and (iv) total UniGene display. However, the chip can be adapted to any other desired layout. By selecting dots, further information about the represented genes is obtained from the local database and WWW links. The software thus provides a visualization of global mRNA expression at the descriptive level and guides in the exploration of patterns of functional expression, while maintaining direct access to detailed information on each individual gene. To evaluate the software, public EST and SAGE gene expression data obtained from the Cancer Genome Anatomy Project at the National Center for Biotechnology Information were analyzed and visualized. A demonstration of the software is available at http://www.biochem.kth. se/exproview/.

Data Display↗

PubMed2004

Expression profiling in Medicago truncatula identifies more than 750 genes differentially expressed during nodulation, including many potential regulators of the symbiotic program.

In this study, we describe a large-scale expression-profiling approach to identify genes differentially regulated during the symbiotic interaction between the model legume Medicago truncatula and the nitrogen-fixing bacterium Sinorhizobium meliloti. Macro- and microarrays containing about 6,000 probes were generated on the basis of three cDNA libraries dedicated to the study of root symbiotic interactions. The experiments performed on wild-type and symbiotic mutant material led us to identify a set of 756 genes either up- or down-regulated at different stages of the nodulation process. Among these, 41 known nodulation marker genes were up-regulated as expected, suggesting that we have identified hundreds of new nodulation marker genes. We discuss the possible involvement of this wide range of genes in various aspects of the symbiotic interaction, such as bacterial infection, nodule formation and functioning, and defense responses. Importantly, we found at least 13 genes that are good candidates to play a role in the regulation of the symbiotic program. This represents substantial progress toward a better understanding of this complex developmental program.

Biological Transport↗

PubMed2006

Use of immuno-LCM to identify the in situ expression profile of cellular constituents of the tumor microenvironment.

Expression profiling using microarrays has become an essential tool for interrogating tumor biology. However, profiling of whole tumor RNA reflects both tumor and host cells, making it difficult to dissect molecular events within specific cellular compartments in the tumor microenvironment. We developed and optimized a simple, rapid technique combining immunohistochemistry and laser-capture microdissection (immuno-LCM) to purify specific cell populations from the tumor microenvironment followed by RNA isolation and amplification for microarray analysis. Using this methodology, we were able to elucidate the in situ expression profile of pure tumor cells and tumor endothelial cells from ovarian tumors with brisk immune infiltrates. This technique not only increased the specificity of profiling isolated cell populations, eliminating genes expressed by surrounding cells, but also increased the sensitivity of analysis, allowing for the detection of low expression genes that were not detected in whole tumor arrays. Pathway analysis of tumor cells in situ identified distinct activation of signaling pathways converging on NF-kappaB, as compared to pathways identified in cultured tumor cell lines, which were primarily metabolic. Profiling of tumor vascular cells revealed most known panendothelial and tumor endothelial-specific markers, and unveiled genes specific to the myeloid-monocytic lineage. We propose that immuno-LCM coupled with transcriptional profiling is a convenient tool for dissecting molecular and cellular events in complex biological systems such as the tumor microenvironment.

Computational Biology↗

PubMed2001

An expression profile of active genes in human conjunctival epithelium.

The purpose of this study was to describe the quantitatively and qualitatively genes expressed in in vivo human conjunctival epithelium. A cDNA library was created from human conjunctival epithelial cells obtained from 38 normal eyes by brush cytology. Poly A(+)RNA isolated from these cells was used as a template for cDNA synthesis by the vector-priming method. A 3'-directed cDNA library consisting of the cDNA moiety covering the poly A(+)RNA tail through the nearest Mbo I site was constructed and transformed into Escherichia coli. Inserts in 933 randomly chosen clones were sequenced. The resulting sequences were compared to determine frequency of appearance in the library, and to establish an expression profile of genes in the conjunctival epithelium. The sequences were sent to GenBank for gene identification. The result was an expression profile of active genes reflecting their relative abundance in the conjunctival epithelial mRNA population. The expression profile of human conjunctival epithelium showed that the most abundant gene transcript in human conjunctival epithelium was that for cytokeratin 13. Altogether 102 genes were found to be very active, including beta-2 microglobulin, lipocortin I and insulin-like growth factor binding protein-3. The gene expression profile of the conjunctival epithelium reflects the unique properties and functions of this tissue. Comparison of this expression profile with that obtained from corneal epithelium discloses clear differences and helps us better understand the physiology and pathophysiology of the ocular surface in humans.

Adult↗

PubMed2004

Gene expression profile in liver of hB1F transgenic mice.

AIM: To analyze the tissue morphologic phenotype and liver gene expression profile of hB1F transgenic mice. METHODS: Transgene expression was analyzed with RT-PCR and Western blotting. For one of the transgenic mouse lines, tissue expression pattern of the transgene was also examined with immunochemical methods. Pathological analysis was used to examine the tissue morphologic phenotype of established transgenic mice. The liver gene expression profile of transgenic mice was analyzed with microchip, and some of the differentially expressed genes were verified with RT-PCR. RESULTS: The expressions of hB1F were shown in livers from 6 of 7 transgenic mouse lines. The overexpression of hB1F transgene did not cause pathological changes. Expressions of three genes were up-regulated, while down-regulation was observed for 25 genes. CONCLUSION: The overexpression of hB1F transgene may cause changes of gene expression profiles in the liver of transgenic mice.

Animals↗

PubMed2005

Strain-specific expression profiles of virulence genes in Helicobacter pylori during infection of gastric epithelial cells and granulocytes.

Helicobacter pylori expresses a variety of known virulence-associated factors, whose expression is likely to be dependent on the ecological niche of this pathogen. Here, we compared the temporal changes in the level of virulence-associated gene transcription in H. pylori strains isolated from patients with different pathology. Our aim was to study the coordinated gene expression profiles of these virulence factors during infection of AGS gastric epithelial cells and granulocytes. Using real-time quantitative (TaqMan) RT-PCR, we determined the mRNA expression of cagA, ureA, napA, katA, vacAs1 and vacAs2 alleles in a time course up to 6 h. The expression profiles of the investigated genes vary according to the strain, and were mainly either upregulated or unchanged upon bacterial contact with AGS cells. In contrast, upon contact with granulocytes, the majority of the genes were repressed in H. pylori. The following major results were obtained: (i) genetically diverse H. pylori exhibit different mRNA expression profiles, (ii) the expression patterns were strain-specific and time-dependent and (iii) the regulation of expression profiles was host cell dependent. These data were statistically significant and suggest that contact with target cells leads to an active cross-talk between the pathogen and its host. The use of Taqman-PCR to analyse the expression of mRNA of a bacterial pathogen in response to a changing host environment enabled us to identify variable and strain-specific transcription profiles in a sensitive and reproducible manner.

Adenocarcinoma↗

PubMed2005

Microarray-based gene expression profiling of benign, atypical and anaplastic meningiomas identifies novel genes associated with meningioma progression.

To identify gene expression profiles associated with human meningiomas of different World Health Organization (WHO) malignancy grades, we analyzed 30 tumors (13 benign meningiomas, WHO grade I; 12 atypical meningiomas, WHO grade II; 5 anaplastic meningiomas, WHO grade III) for the expression of 2,600 genes using cDNA-microarray technology. Receiver operator curve (ROC) analysis with a cutoff value of 45% selection probability identified 37 genes with decreased and 27 genes with increased expression in atypical and anaplastic meningiomas, compared to benign meningiomas. Supervised classification of the tumors did not reveal specific expression patterns representative of each WHO grade. However, anaplastic meningiomas could be distinguished from benign meningiomas by differential expression of a distinct set of genes, including several ones associated with cell cycle regulation and proliferation. Investigation of potential correlations between microarray expression data and genomic aberrations, detected by comparative genomic hybridization (CGH), demonstrated that losses on chromosomes 10 and 14 were associated with distinct expression profiles, including increased expression of several genes related to the insulin-like growth factor (IGF) (IGF2, IGFBP3 and AKT3) or wingless (WNT) (CTNNB1, CDK5R1, ENC1 and CCND1) pathways. Taken together, our microarray-based expression profiling revealed interesting novel candidate genes and pathways that may contribute to meningioma progression.

Chromosome Mapping↗

PubMed2005

Gene expression profiling of muscle tissue in Brahman steers during nutritional restriction.

Expression profiling using microarrays allows for the detailed characterization of the gene networks that regulate an animal's response to environmental stresses. During nutritional restriction, processes such as protein turnover, connective tissue remodeling, and muscle atrophy take place in the skeletal muscle of the animal. These processes and their regulation are of interest in the context of managing livestock for optimal production efficiency and product quality. Here we expand on recent research applying complementary DNA (cDNA) microarray technology to the study of the effect of nutritional restriction on bovine skeletal muscle. Using a custom cDNA microarray of 9,274 probes from cattle muscle and s.c. fat libraries, we examined the differential gene expression profile of the LM from 10 Brahman steers under three different dietary treatments. The statistical approach was based on mixed-model ANOVA and model-based clustering of the BLUP solutions for the gene x diet interaction effect. From the results, we defined a transcript profile of 156 differentially expressed array elements between the weight loss and weight gain diet substrates. After sequence and annotation analyses, the 57 upregulated elements represented 29 unique genes, and the 99 downregulated elements represented 28 unique genes. Most of these co-regulated genes cluster into groups with distinct biological function related to protein turnover and cytoskeletal metabolism and contribute to our mechanistic understanding of the processes associated with remodeling of muscle tissue in response to nutritional stress.

Analysis of Variance↗

PubMed2002

Classification, subtype discovery, and prediction of outcome in pediatric acute lymphoblastic leukemia by gene expression profiling.

Treatment of pediatric acute lymphoblastic leukemia (ALL) is based on the concept of tailoring the intensity of therapy to a patient's risk of relapse. To determine whether gene expression profiling could enhance risk assignment, we used oligonucleotide microarrays to analyze the pattern of genes expressed in leukemic blasts from 360 pediatric ALL patients. Distinct expression profiles identified each of the prognostically important leukemia subtypes, including T-ALL, E2A-PBX1, BCR-ABL, TEL-AML1, MLL rearrangement, and hyperdiploid >50 chromosomes. In addition, another ALL subgroup was identified based on its unique expression profile. Examination of the genes comprising the expression signatures provided important insights into the biology of these leukemia subgroups. Further, within some genetic subgroups, expression profiles identified those patients that would eventually fail therapy. Thus, the single platform of expression profiling should enhance the accurate risk stratification of pediatric ALL patients.

Algorithms↗

PubMed2003

Kernel Cox regression models for linking gene expression profiles to censored survival data.

In functional genomics, one important problem is to relate the microarray gene expression profiles to various clinical phenotypes from patients. The success has been demonstrated in molecular classification of cancer in which gene expression data serve as predictors and different types of cancer are the binary or multi-categorical outcome variable. However, there has been less research in linking gene expression profiles to other types of phenotypes, in particular, the censored survival data such as patients' overall survival or cancer relapse times. In the paper, we develop a kernel Cox regression model for relating gene expression profiles to censored phenotypes in the framework the penalization method in terms of function estimation in reproducing kernel Hilbert spaces. To circumvent the problem of censoring, we use the negative partial likelihood as a loss function in the estimation procedure. The functional combinations of the original gene expression data identified by the method are highly correlated with the patients' survival times and at the same time account for the variability in the gene expression levels. We apply our method to data sets from diffuse large B-cell lymphoma, lung adenocarcinoma and breast carcinoma studies to verify its effectiveness. The results from these analyses indicate that the proposed method works very well in identifying subgroups of patients with different risks of death or relapse and in predicting the risk of relapse or death based on the gene expression profiles measured from the tumor samples taken from the patients.

Artificial Intelligence↗

PubMed2006

Temporal gene expression profiles of target-ablated olfactory epithelium in mice with disrupted expression of scavenger receptor A: impact on macrophages.

Target ablation [removal of the olfactory bulb (OBX)] induces apoptotic death of olfactory sensory neurons (OSNs) and an immune response in which activation and recruitment of macrophages (ms) into the olfactory epithelium (OE) occupy a central role. Ms phagocytose apoptotic neurons and secrete cytokines/growth factors that regulate subsequent progenitor cell proliferation and neurogenesis. Scavenger receptor A (SR-A) is a pattern recognition receptor that mediates binding of ms to apoptotic cells and other relevant immune response functions. The aim of this study was to determine the impact of the absence of SR-A on the immune response to OBX. The immune response to OBX was evaluated in mice in which functional expression of the m scavenger receptor (MSR) was eliminated by gene disruption (MSR-/-) and wild-type (wt) mice of the same genetic background. OBX induced significant apoptotic death of mature OSNs in the two strains. However, subsequent m infiltration and activation and progenitor cell proliferation were significantly reduced in MSR-/- vs. wt mice. Gene expression profiling at short intervals after OBX demonstrated significant differences in temporal patterns of expression of several gene categories, including immune response genes. Many immune response genes that showed different temporal patterns of expression are related to m function, including cytokine and chemokine secretion, phagocytosis, and m maturation and activation. These studies suggest that impairment of the immune response to OBX in the OE of MSR-/- mice most likely resulted from decreased m adhesion and subsequent reduced infiltration and activation, with a resultant decrease in neurogenesis.

Animals↗