SEARCH · PubMed Health

Results for “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 811 records · Page 45Linked to original sources

PubMed2006

Activity and gene expression profile of certain antioxidant enzymes to microcystin-LR induced oxidative stress in mice.

Microcystins are cyclic heptapeptide toxins produced by certain strains of Microcystis aeruginosa and microcystin-LR (MC-LR) is the most toxic among the 70 variants isolated so far. These toxins have been implicated in both human and livestock mortality. In the present study we investigated the microcystin-LR induced oxidative stress in mice in terms of its effect on activity and gene expression profile of certain antioxidant enzymes and expression of heat shock protein-70 (HSP-70). Mice were treated with 0.5 LD50 (38.31 microg/kg) and 1 LD50 (76.62 microg/kg) and the biochemical variables were determined at 1, 3, 7 days and 15, 30, 60 and 120 min post-exposure for 0.5 and 1 LD50 dose, respectively. A significant time-dependent increase in HSP-70 expression over control was observed at 1 LD50 dose. The toxin induced significant increase in liver body weight index, hepatic lipid peroxidation and depletion of GSH levels at 1 LD50 compared to control group. There was significant decrease in the activity of antioxidant enzymes glutathione peroxidase (GPX), superoxide dismutase (SOD), catalase (CAT), glutathione reductase (GR) and glutathione-S-transferase (GST) at 1 LD50. Except catalase, there was no effect on other antioxidant enzymes at 0.5 LD50 dose. In contrast to activity of antioxidant enzymes the gene expression profile did not show any significant difference compared to control at 1 LD50. GR showed significant decrease in expression at 1, 3 and 7 days in animals dosed with 0.5 LD50 MC-LR. The results of our in vivo study clearly show the oxidative stress induced by MC-LR, and a correlation with activity and regulation at gene expression level of antioxidant enzymes.

Animals↗

PubMed2005

Expression profiles of apoptosis genes in mammary epithelial cells.

To investigate apoptosis in HC11 mammary epithelial cells, we compared the gene expression profiles of actively growing and serum-starved apoptotic cells using a mouse apoptosis gene array and 33P-labeled cDNA prepared from the RNA of the two cultures. Analysis of the arrays showed that expression of several genes such as clusterin, secreted frizzled related protein mRNA (sFRP-1), CREB-binding protein (CBP), and others was higher in the apoptotic cells whereas expression of certain genes including survivin, cell division cycle 2 homolog A (CDC2), and cyclin A was lower. These expression patterns were confirmed by RT-PCR and/or Northern analyses. We compared the expression of some of these genes in the mouse mammary gland under various physiological conditions. The expression levels of genes (clusterin, CBP, and M6P-R) up-regulated in apoptotic conditions were higher at involution than during lactation. On the other hand, genes (Pin, CDC2) downregulated in apoptotic conditions were relatively highly expressed in virgin and pregnant mice. We conclude that certain genes such as clusterin, sFRP-1, GAS1 and CBP are induced in apoptotic mammary epithelial cells, and others are repressed. Moreover, the apoptosis array is an efficient technique for comparing gene expression profiles in different states of the same cell type.

Animals↗

PubMed2006

A gene expression profile for vascular invasion can predict the recurrence after resection of hepatocellular carcinoma: a microarray approach.

BACKGROUND: Recurrence after hepatocellular carcinoma (HCC) resection is the major obstacle to improved survival. The presence of vascular invasion (VI) in pathology specimens is a well-known unfavorable prognostic factor for HCC recurrence. Though some VI-related genes have been reported, their association with recurrence-free survival is not known. We hypothesized that a gene expression profile for VI can predict the recurrence of HCC after liver resection. METHODS: Eighteen patients receiving complete HCC resection were included as a "training group". Genome-wide gene expression profile was obtained for each tumor using a microarray technique. Datasets were subjected to clustering analysis supervised by the presence or absence of VI to obtain 14 discriminative genes. We then applied those genes to execute pattern recognition using the k-Nearest Neighbor (KNN) classification method, and the best model for this VI gene signature to predict recurrence-free survival in the training group was obtained. The resulting model was then tested in an independent "test group" of 35 patients. RESULTS: A 14-gene profile was extracted which could accurately separate ten patients with VI and eight patients without VI in the "training group". In the "test group", significant difference in disease-free survival was found between patients predicted to have and not to have recurrence (P = .02823). In patients with stage_I disease, this model can also predict outcomes (P = .000205). CONCLUSIONS: Using the 14-gene expression profile extracted from microarrays based on the presence of VI can effectively predict recurrence after HCC resection. This approach might facilitate "personalized medicine" for HCC patients after surgical resection.

Aged↗

PubMed2005

Microarray analysis reveals pivotal divergent mRNA expression profiles early in the development of either compensated ventricular hypertrophy or heart failure.

Myocardial right ventricular (RV) hypertrophy due to pulmonary hypertension is aimed at normalizing ventricular wall stress. Depending on the degree of pressure overload, RV hypertrophy may progress to a state of impaired contractile function and heart failure, but this cannot be discerned during the early stages of ventricular remodeling. We tested whether critical differences in gene expression profiles exist between ventricles before the ultimate development of either a compensated or decompensated hypertrophic phenotype. Both phenotypes were selectively induced in Wistar rats by a single subcutaneous injection of either a low or a high dose of the pyrrolizidine alkaloid monocrotaline (MCT). Spotted oligonucleotide microarrays were used to investigate pressure-dependent cardiac gene expression profiles at 2 wk after the MCT injections, between control rats and rats that would ultimately develop either compensated or decompensated hypertrophy. Clustering of significantly regulated genes revealed specific expression profiles for each group, although the degree of hypertrophy was still similar in both. The ventricles destined to progress to failure showed activation of pro-apoptotic pathways, particularly related to mitochondria, whereas the group developing compensated hypertrophy showed blocked pro-death effector signaling via p38-MAPK, through upregulation of MAPK phosphatase-1. In summary, we show that, already at an early time point, pivotal differences in gene expression exist between ventricles that will ultimately develop either a compensated or a decompensated phenotype, depending on the degree of pressure overload. These data reveal genes that may provide markers for the early prediction of clinical outcome as well as potential targets for early intervention.

Animals↗

PubMed2004

Genome-wide expression profiling; a panel of mouse tissues discloses novel biological functions of liver X receptors in adrenals.

The liver X receptors alpha and beta (LXRalpha and LXRbeta ) are members of the nuclear receptor superfamily of proteins which are highly expressed in metabolically active tissues. They regulate gene expression of critical genes involved in cholesterol catabolism and transport, lipid and triglyceride biosynthesis and carbohydrate metabolism in response to distinct oxysterols and intermediates in the cholesterol metabolic pathway. The biological roles of the LXRs in tissues other than liver, intestine and adipose tissue are poorly elucidated. In this study we used global gene-expression profiling analysis to detect differences in expression patterns in several tissues from mice fed an LXR agonist or vehicle. Our results show that LXR plays an important role in the kidney, lung, adrenals, brain, testis and heart where several putative LXR target genes were found. The effects of the LXRs were further analysed in adrenals where treatment with an LXR agonist induced expression of adrenocorticotrophic hormone receptor, suppressed expression of uncoupling protein (UCP)-1 and UCP-3 as well as several glycolytic enzymes and led to increased serum corticosterone levels. These results indicate novel biological roles of the LXR including regulation of energy metabolism, glycolysis and steroidogenesis in the adrenals via alteration of expression profiles of putative target genes.

Adrenal Glands↗

PubMed2005

Gene expression profiling predicts survival in conventional renal cell carcinoma.

BACKGROUND: Conventional renal cell carcinoma (cRCC) accounts for most of the deaths due to kidney cancer. Tumor stage, grade, and patient performance status are used currently to predict survival after surgery. Our goal was to identify gene expression features, using comprehensive gene expression profiling, that correlate with survival. METHODS AND FINDINGS: Gene expression profiles were determined in 177 primary cRCCs using DNA microarrays. Unsupervised hierarchical clustering analysis segregated cRCC into five gene expression subgroups. Expression subgroup was correlated with survival in long-term follow-up and was independent of grade, stage, and performance status. The tumors were then divided evenly into training and test sets that were balanced for grade, stage, performance status, and length of follow-up. A semisupervised learning algorithm (supervised principal components analysis) was applied to identify transcripts whose expression was associated with survival in the training set, and the performance of this gene expression-based survival predictor was assessed using the test set. With this method, we identified 259 genes that accurately predicted disease-specific survival among patients in the independent validation group (p < 0.001). In multivariate analysis, the gene expression predictor was a strong predictor of survival independent of tumor stage, grade, and performance status (p < 0.001). CONCLUSIONS: cRCC displays molecular heterogeneity and can be separated into gene expression subgroups that correlate with survival after surgery. We have identified a set of 259 genes that predict survival after surgery independent of clinical prognostic factors.

Adult↗

PubMed2006

Class prediction from time series gene expression profiles using dynamical systems kernels.

We present a kernel-based approach to the classification of time series of gene expression profiles. Our method takes into account the dynamic evolution over time as well as the temporal characteristics of the data. More specifically, we model the evolution of the gene expression profiles as a Linear Time Invariant (LTI) dynamical system and estimate its model parameters. A kernel on dynamical systems is then used to classify these time series. We successfully test our approach on a published dataset to predict response to drug therapy in Multiple Sclerosis patients. For pharmacogenomics, our method offers a huge potential for advanced computational tools in disease diagnosis, and disease and drug therapy outcome prognosis.

Artificial Intelligence↗

PubMed2007

Gene expression profile as a prognostic factor in high-grade gliomas.

Some clinical factors have been useful in predicting prognosis in high-grade gliomas, however, unexpected differences in survival time have generated attempts to search for more precise parameters. It is clear that tumour behaviour depends mostly on gene alterations. Known single gene alterations failed to accurately define survival time, however, recently, the gene profiling based on microarray technology has raised hopes. Our aim was to assess whether the genetic predictor exceeds clinical parameters in the prognosis of malignant gliomas. We performed gene expression analysis of 28 gliomas (3 grade II, 10 grade III and 15 grade IV, according to WHO classification), and 5 control, normal brain samples, using Clontech oligonucleotide arrays with 3,757 known genes. The signal-to-noise statistics was used to separate classes, and the leave-one-out method was used to assess the smallest number of genes make it clear with a minimal cross-validation error. All gliomas, or only high-grade tumours, were clearly separated from the normal brain samples using 7 or 9 most differentially expressed genes. Hierarchical clustering failed, but the fuzzy c-means method was useful in high-grade gliomas to find a gene prediction model, which, with clinical factors, was assessed in survival analysis. Univariate analysis demonstrated that age, WHO grade (IV vs. III), radiation dose (> or = 50 Gy vs. 42 Gy), postoperative KPS score (100 points vs. others), neurological deficit as the first sign of the disease vs. others, and gene expression profile were significant predictors of survival. In multivariate analysis, the gene expression profile remained the only independent predictor (p = 0.007). Thus, our conclusion is that gene expression pattern predicts outcome in high-grade gliomas independently of other factors.

Adult↗

PubMed2005

Functional genomic relationships in HIV-1 disease revealed by gene-expression profiling of primary human peripheral blood mononuclear cells.

BACKGROUND: An assessment of biomarkers from an analysis of human peripheral blood mononuclear cell gene-expression profiles was made, to acquire an understanding of transcriptional changes associated with human immunodeficiency virus type 1 (HIV-1) infection in vivo. METHODS: Supervised learning algorithms were used to create signature gene sets that could be used to distinguish seropositive from seronegative samples and delineate changes in disease status during the early stages of infection. Bioinformatic tools were used to classify persons and to functionally characterize groups of differentially expressed genes, to elucidate the impact of viral infection on host cell gene-expression patterns. RESULTS: A 10-gene signature set that could be used to accurately determine the HIV-1 serostatus was identified. A 6-gene signature set was used to distinguish seropositive persons exhibiting differential changes in CD4(+) T cell counts, with 93% accuracy. Functional classification of differentially expressed genes in HIV-1 indicated a preponderance of down-regulated genes with functions related to the immune response and apoptosis. Hierarchical cluster analysis in persons whose CD4(+) T cell counts increased, compared with that in persons whose CD4(+) T cell counts decreased, was characterized by the down-regulation of genes associated with apoptosis, mitochondrial function, protein biosynthesis, and RNA binding. CONCLUSIONS: Gene-expression profile analysis of a complex infectious virus, such as HIV-1, may be useful to elucidate the functional genomic relationships associated with viral infection.

CD4-Positive T-Lymphocytes↗

PubMed2006

Alteration of hTERT full-length variant expression level showed different gene expression profiles and genomic copy number changes in breast cancer.

We analyzed hTERT splicing patterns with respect to telomerase activity in breast cancer. Using a cDNA microarray in 22 cell lines, we observed the difference in expression profiling based on the different levels of full-length variant expression with 71 selected genes. Using 33 known genes that act with the telomerase complex, we performed unsupervised clustering with all cell lines, and found a clustering tendency related to the full-length variant expression level. Using array-based CGH, highly altered genomic copy number changes were found more often in MCF-7 (159 genes) than in MDA-MB-231 (109 genes) and MDA-MB-435 (49 genes), suggesting more genomic changes in MCF-7 cells. On comparing MCF-7 with MDA-MB231 and MDA-MB-435 cell lines, we identified 8 genes with different copy numbers, including dystroglycan, which is located in the p12-21.2 area of chromosome 3. In conclusion, alterations in the level of the full-length variant of hTERT showed different gene expression profiles and genomic copy number changes in breast cancer, which require further study into their cause-and-effect relationship.

Alternative Splicing↗

PubMed2005

Gene expression profiles of HeLa Cells impacted by hepatitis C virus non-structural protein NS4B.

By a cDNA array representing 2308 signal transduction-related genes, we studied the expression profiles of HeLa cells stably transfected by Hepatitis C virus nonstructural protein 4B (HCV-NS4B). The alterations of the expression of four genes were confirmed by real-time quantitative RTPCR; and the aldo-keto reductase family 1, member C1 (AKR1C1) enzyme activity was detected in HCV-NS4B transiently transfected HeLa cells and Huh-7, a human hepatoma cell line. Of the 2,308 genes we examined, 34 were up-regulated and 56 were down-regulated. These 90 genes involved oncogenes, tumor suppressors, cell receptors, complements, adhesions, transcription and translation, cytoskeleton and cellular stress. The expression profiling suggested that multiple regulatory pathways were affected by HCV-NS4B directly or indirectly. And since these genes are related to carcinogenesis, host defense system and cell homeostatic mechanism, we can conclude that HCV-NS4B could play some important roles in the pathogenesis mechanism of HCV.

Gene Expression Profiling↗

PubMed2003

Expression profiling of osteosarcoma cells transfected with MDR1 and NEO genes: regulation of cell adhesion, apoptosis, and tumor suppression-related genes.

The expression patterns of the osteosarcoma cell line U-2 OS, and three derived subclones containing stably transfected MDR1, NEO and MDR1/NEO genes were compared using cDNA microarrays comprising 8976 known genes and expressed sequenced tags. Data provided new insights into three critical issues. First, MDR1 overexpression was associated with altered expression of genes related to several cellular pathways, including (a). drug influx/efflux (eg, dynamin 3), (b). metabolic enzymes (eg, monoamine oxidase A), (c). cell adhesion (eg, EPCAM), (d). apoptotic signaling (eg, I-TRAF), (e). senescence (eg, telomerase RNA binding protein staufen), (f). tumor suppression-related genes (eg, KISS-1 and ephrin B3), and (g). immune system receptors (eg, LENG2). MDR1, EPCAM, and ephrin B3 expression was confirmed by immunohistochemistry. Second, MDR1 transfected cells selected with either doxorubicin or neomycin showed distinct expression profiles that could be related to differential selection. Moreover, hierarchical clustering indicated that cells transfected with MDR1 alone, or cotransfected with NEO, displayed more closely related expression profiles than cells transfected only with NEO. Third, transfection with NEO and selection with neomycin produced a considerable number of expression changes within the cell. This study further elucidates the genetic events associated with MDR1 expression and identifies novel targets associated with multidrug resistance.

ATP Binding Cassette Transporter, Subfamily B, Mem↗

PubMed2006

Gene-expression profiling of systemic anaplastic large-cell lymphoma reveals differences based on ALK status and two distinct morphologic ALK+ subtypes.

With the use of microarray gene-expression profiling, we analyzed a homogeneous series of 32 patients with systemic anaplastic large-cell lymphoma (ALCL) and 5 ALCL cell lines. Unsupervised analysis classified ALCL in 2 clusters, corresponding essentially to morphologic subgroups (ie, common type vs small cell and "mixed" variants) and clinical variables. Patients with a morphologic variant of ALCL had advanced-stage disease. This group included a significant number of patients who experienced early relapse. Supervised analysis showed that ALK+ALCL and ALK- ALCL have different gene-expression profiles, further confirming that they are different entities. Among the most significantly differentially expressed genes between ALK+ and ALK- samples, we found BCL6, PTPN12, CEBPB, and SERPINA1 genes to be overexpressed in ALK+ ALCL. This result was confirmed at the protein level for BCL-6, C/EBPbeta and serpinA1 through tissue microarrays. The molecular signature of ALK- ALCL included overexpression of CCR7, CNTFR, IL22, and IL21 genes but did not provide any obvious clues to the molecular mechanism underlying this tumor subtype. Once confirmed on a larger number of patients, the results of the present study could be used for clinical and therapeutic management of patients at the time of diagnosis.

Anaplastic Lymphoma Kinase↗

PubMed2001

Prediction of sensitivity of esophageal tumors to adjuvant chemotherapy by cDNA microarray analysis of gene-expression profiles.

We applied cDNA microarray analyses of 9216 genes to establish a genetic method for predicting the outcome of adjuvant chemotherapy to esophageal cancers. We analyzed expression profiles of 20 esophageal cancer tissues from patients who were treated with the same adjuvant chemotherapy after removal of tumor by operation, and we attempted to find genes associated with the duration of survival after surgery. By comparing expression profiles of those cancer tissues, we identified by statistical analysis 52 genes that were likely to be correlated with prognosis and possibly with sensitivity/resistance to the anticancer drugs. We also developed a drug response score based on the differential expression of these genes, and we found a significant correlation between the drug response score and individual patients' prognoses. Our results indicated that this scoring system, based on microarray analysis of selected genes, is likely to have great potential for predicting the prognosis of individual cancer patients with the adjuvant chemotherapy.

Aged↗

PubMed2002

Maspin expression profile in human prostate cancer (CaP) and in vitro induction of Maspin expression by androgen ablation.

PURPOSE: Expression of tumor suppressor gene, MASPIN, is associated with inhibition of tumor cell invasion and metastasis. Loss of or decreased expression of Maspin is found frequently in breast and prostate cancer cells. The objective of this study is to investigate Maspin expression in prostate tumor specimens and explore the mechanisms of hormonal regulation of Maspin expression in prostate tumors. EXPERIMENTAL DESIGN: Immunohistochemical staining of Maspin expression was performed on surgical whole-mounted prostate specimens. The expression of Maspin was scored on individual tumors. Correlation of Maspin expression with clinicopathological features was analyzed for statistical significance. Androgen ablation-induced Maspin expression was analyzed by Maspin promoter luciferase reporter assay and quantitative reverse transcription-PCR analysis of endogenous Maspin expression in LNCaP cells in vitro and in animal model. RESULTS: Comprehensive evaluation of Maspin expression profile in multiple tumor foci from whole mounted prostate specimens of prostate cancer patients revealed absence of Maspin expression in a significant fraction (63%). However, Maspin expression is significantly higher in tumor specimens (92%) of patients treated with neoadjuvant androgen ablation therapy before radical prostatectomy. LNCaP cells cultured in androgen-depleted medium show induction of Maspin promoter activity in a promoter luciferase reporter assay. In addition, Maspin expression is increased after castration in LNCaP prostate cancer cells derived tumors in nude mice. CONCLUSIONS: Maspin expression is frequently absent in primary prostate cancers. Up-regulation of MASPIN in response to androgen ablation strongly suggests a physiological role of Maspin in growth inhibition and/or apoptosis of prostate cancer cells during androgen ablation.

Aged↗

PubMed2006

Expression profile of immune-associated genes in nasal polyps.

OBJECTIVES: We performed this study to investigate the expression profile of immune-associated genes and to probe the role of related genes in the immune pathogenesis of nasal polyps. METHODS: Microarray analysis was used to find the expression profile of 491 immune-associated genes in nasal polyps. In validation studies, immunohistochemical staining and Western blot analysis were used to detect interleukin (IL)-17 and IL-17 receptor (IL-17R) in nasal polyps and controls. RESULTS: Eighty-seven genes were differentially expressed in the immune-associated gene profile of nasal polyps, and 15 genes showed differential expression in both chips. In nasal polyp tissues, IL-17 was expressed mainly in the cytoplasm of plasma cells and to a lesser degree in the prickle cell layer of the epithelium and the acinus of the serous gland. In turbinates, IL-17 was also expressed in the same location, but the expression of IL-17 in nasal polyps and that in turbinates differed significantly (p < .05). Both IL-17 and IL-17R displayed specific bands in nasal polyps and turbinates, but the bands of IL-17 and IL-17R in nasal polyps were stronger than those in turbinates. CONCLUSIONS: The differentially expressed genes in immune-associated gene chips will provide clues about, and a theoretical foundation for, the pathogenesis of nasal polyps. Furthermore, IL-17 may play an important role in the occurrence of nasal polyps by overexpression.

Adult↗

PubMed2006

HeatMapper: powerful combined visualization of gene expression profile correlations, genotypes, phenotypes and sample characteristics.

BACKGROUND: Accurate interpretation of data obtained by unsupervised analysis of large scale expression profiling studies is currently frequently performed by visually combining sample-gene heatmaps and sample characteristics. This method is not optimal for comparing individual samples or groups of samples. Here, we describe an approach to visually integrate the results of unsupervised and supervised cluster analysis using a correlation plot and additional sample metadata. RESULTS: We have developed a tool called the HeatMapper that provides such visualizations in a dynamic and flexible manner and is available from http://www.erasmusmc.nl/hematologie/heatmapper/. CONCLUSION: The HeatMapper allows an accessible and comprehensive visualization of the results of gene expression profiling and cluster analysis.

Antigens, CD34↗

PubMed2004

Serum protein-expression profiling using the ProteinChip biomarker system.

Protein-expression profiling of serum is a common approach to the discovery of potential diagnostic and therapeutic markers of disease. Like any other proteome, the serum proteome is characterized by protein expression across a large dynamic range. This single facet requires the employment of fractionation procedures prior to detection of protein. The authors use a combination of conventional column chromatography with array-based chromatography to simplify the serum proteome into subproteomes, thus providing a greater representation of the serum proteome. Robotics is employed to increase the throughput of sample processing. These procedures result in large amounts of data that are analyzed through a series of preprocessing and postprocessing steps. A well-designed serum profiling project can therefore result in the discovery of statistically sound, clinically meaningful protein biomarkers.

Anion Exchange Resins↗