SEARCH · PubMed Health

Results for “Expression profile”

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 235 records · Page 13Linked to original sources

PubMed2006

Preliminary analysis of gene expression profiles in HepG2 cell line induced by different genotype core proteins of HCV.

In present investigation, we constructed recombinants expressing the HCV genotypes 1b, 2a, and 4d core proteins, and established human hepatocellular carcinoma (HepG2) cell line that expressed various genotype core proteins. The gene expression profiles in the cells expressing different HCV genotype core proteins were compared with those in the control by microarray analysis. In data analysis, a threshold was set to eliminate all genes that were not increased or decreased by 2.5-fold change in a comparison between the transfected cells and control cells. The preliminary microarray analysis suggests that the gene expression profiles regulated by three kinds of genotype core proteins are mainly involved in transport, signal transduction, regulation of transcription, protease activity, etc., and that some pathogenesis/oncogenesis gene expressions are up/down- regulated simultaneously in the HepG2 cell line. The data suggest that each core protein has its gene expressions profile and that the profiles are implicated in HCV replication and pathogenesis, which may open up a novel way to understand the function of the HCV variant core proteins biological and their pathogenic mechanism.

Blotting, Western↗

PubMed2004

Gene expression profiling in breast cancer research.

The gene expression profiles of breast cancers can now be determined with microarray technologies which measure the expression of tens of thousands of genes. By applying statistical and bioinformatics tools to gene expression data, tumors can be classified into biologically and clinically relevant categories. In addition to improving tumor classification, gene expression signatures have been identified which are related to BRCA1 and BRCA2 mutation status, ER status, and patient prognosis. Beyond its impact on research into the basic mechanisms of breast tumor progression, continued progress in tumor gene expression profiling appears likely to lead to clinically useful gene expression tests.

Journal Article↗

PubMed2003

Arabidopsis gene expression changes during cyst nematode parasitism revealed by statistical analyses of microarray expression profiles.

With the availability of microarray technology, the expression profiles of thousands of genes can be monitored simultaneously to help determine the mechanisms of these biological processes. We conducted Affymetrix GeneChip microarray analyses of the Arabidopsis-cyst nematode interaction and employed a statistical procedure to analyze the resultant data, which allowed us to identify significant gene expression changes. Quantitative real-time RT-PCR assays were used to confirm the microarray analyses. The results of the expression profiling revealed 128 genes with altered steady-state mRNA levels following infection by the sugar beet cyst nematode (Heterodera schachtii; BCN), in contrast to only 12 genes that had altered expression following infection by the soybean cyst nematode (H. glycines; SCN). The expression of these 12 genes also changed following infection by BCN, i.e. we did not identify any genes regulated exclusively by SCN. The identification of 116 genes whose expression changes during successful cyst nematode parasitism by BCN suggests a potential involvement of these genes in the infection events starting with successful syncytium induction. Further characterization of these genes will permit the formulation of testable hypotheses to explain successful cyst nematode parasitism.

Animals↗

PubMed2005

Peripheral blood gene expression profiling in rheumatoid arthritis.

We carried out gene expression profiling of peripheral blood mononuclear cells (PBMCs) in 29 patients with active rheumatoid arthritis (RA) and 21 control subjects using Affymetrix U95Av2 arrays. Using cluster analysis, we observed a significant alteration in the expression pattern of 81 genes (P<0.001) in the PBMCs of RA patients compared with controls. Many of these genes correlated with differences in monocyte counts between the two study populations, and we show that a large fraction of these genes are specifically expressed at high levels in monocytes. In addition, a logistic regression analysis was performed to identify genes that performed best in the categorization of RA and control samples. Glutaminyl cyclase, IL1RA, S100A12 (also known as calgranulin or EN-RAGE) and Grb2-associated binding protein (GAB2) were among the top discriminators. Along with previous data, the overexpression of S100A12 in RA patients emphasizes the likely importance of RAGE pathways in disease pathogenesis. The altered expression of GAB2, an intracellular adaptor molecule involved in regulating phosphatase function, is of particular interest given the recent identification of the intracellular phosphatase PTPN22 as a risk gene for RA. These data suggest that a detailed study of gene expression patterns in peripheral blood can provide insight into disease pathogenesis. However, it is also clear that substantially larger sample sizes will be required in order to evaluate fully gene expression profiling as a means of identifying disease subsets, or defining biomarkers of outcome and response to therapy in RA.

Adult↗

PubMedDate not supplied

[DNA microarrays and papillary thyroid carcinoma gene expression profile].

The paper presents gene expression profile analysis with DNA microarrays and compares two core technological platforms used for this purpose - high density oligonucleotide microarrays and cDNA microarrays. With this background recent results of papillary thyroid carcinoma analysis with DNA microarrays are presented.

Animals↗

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↗

PubMed2005

Comparison of supervised clustering methods to discriminate genotoxic from non-genotoxic carcinogens by gene expression profiling.

Prediction of the toxic properties of chemicals based on modulation of gene expression profiles in exposed cells or animals is one of the major applications of toxicogenomics. Previously, we demonstrated that by Pearson correlation analysis of gene expression profiles from treated HepG2 cells it is possible to correctly discriminate and predict genotoxic from non-genotoxic carcinogens. Since to date many different supervised clustering methods for discrimination and prediction tests are available, we investigated whether application of the methods provided by the Whitehead Institute and Stanford University improved our initial prediction. Four different supervised clustering methods were applied for this comparison, namely Pearson correlation analysis (Pearson), nearest shrunken centroids analysis (NSC), K-nearest neighbour analysis (KNN) and Weighted voting (WV). For each supervised clustering method, three different approaches were followed: (1) using all the data points for all treatments, (2) exclusion of the samples with marginally affected gene expression profiles and (3) filtering out the gene expression signals that were hardly altered. On the complete data set, NSC, KNN and WV outperformed the Pearson test, but on the reduced data sets no clear difference was observed. Exclusion of samples with marginally affected profiles improved the prediction by all methods. For the various prediction models, gene sets of different compositions were selected; in these 27 genes appeared three times or more. These 27 genes are involved in many different biological processes and molecular functions, such as apoptosis, cell cycle control, regulation of transcription, and transporter activity, many of them related to the carcinogenic process. One gene, BAX, was selected in all 10 models, while ZFP36 was selected in 9, and AHR, MT1E and TTR in 8. Summarising, this study demonstrates that several supervised clustering methods can be used to discriminate certain genotoxic from non-genotoxic carcinogens by gene expression profiling in vitro in HepG2 cells. None of the methods clearly outperforms the others.

Carcinogens↗

PubMed2003

Gene expression profiles at different stages of human esophageal squamous cell carcinoma.

AIM: To characterize the gene expression profiles in different stages of carcinogenesis of esophageal epithelium. METHODS: A microarray containing 588 cancer related genes was employed to study the gene expression profile at different stages of esophageal squamous cell carcinoma including basal cell hyperplasia, high-grade dysplasia, carcinoma in situ, early and late cancer. Principle component analysis was performed to search the genes which were important in carcinogenesis. RESULTS: More than 100 genes were up or down regulated in esophageal epithelial cells during the stages of basal cell hyperplasia, high-grade dysplasia, carcinoma in situ, early and late cancer. Principle component analysis identified a set of genes which may play important roles in the tumor development. Comparison of expression profiles between these stages showed that some genes, such as P160ROCK, JNK2, were activated and may play an important role in early stages of carcinogenesis. CONCLUSION: These findings provided an esophageal cancer-specific and stage-specific expression profiles, showing that complex alterations of gene expression underlie the development of malignant phenotype of esophageal cancer cells.

Carcinoma, Squamous Cell↗

PubMed2005

Relationship between hepatic gene expression profiles and hepatotoxicity in five typical hepatotoxicant-administered rats.

In the field of gene expression analysis, DNA microarray technology has a major impact on many different areas including toxicogenomics, such as in predicting the adverse effects of new drug candidates and improving the process of risk assessment and safety evaluation. In this study, we investigated whether there is relationship between the hepatotoxic phenotypes and gene expression profiles of hepatotoxic chemicals measured by DNA microarray analyses. Sprague-Dawley rats (6 weeks old) were administered five hepatotoxicants: acetaminophen (APAP), bromobenzene, carbon tetrachloride, dimethylnitrosamine, and thioacetamide. Serum biochemical markers for liver toxicity were measured to estimate the maximal toxic time of each chemical. Hepatic mRNA was isolated, and the gene expression profiles were analyzed by DNA microarray containing 1,097 drug response genes, such as cytochrome P450s, other phase I and phase II enzymes, nuclear receptors, signal transducers, and transporters. All the chemicals tested generated specific gene expression patterns. APAP was sorted to a different cluster from the other four chemicals. From the gene expression profiles and maximal toxic time estimated by serum biochemical markers, we identified 10 up-regulated genes and 10 down-regulated genes as potential markers of hepatotoxicity. By Quality-Threshold (QT) clustering analysis, we identified major up- and down-regulated expression patterns in each group. Interestingly, the average gene expression patterns from the QT clustering were correlated with the mean value profiles from the biochemical markers. Furthermore, this correlation was observed at any extent of hepatotoxicity. In this study, we identified 17 potential toxicity markers, and those expression profiles could estimate the maximal toxic time independently of the hepatotoxicity levels. This expression profile analysis could be one of the useful tools for evaluating a potential hepatotoxicant in the drug development process.

Acetaminophen↗

PubMed2002

DNA microarray analysis of the expression profiles of luteinized granulosa cells as a function of ovarian reserve.

OBJECTIVE: To examine the expression profiles of luteinized granulosa cells isolated from women with normal or diminished ovarian reserve undergoing in vitro fertilization. DESIGN: Expression profiling by complementary DNA microarray analysis. SETTING: Women undergoing in vitro fertilization-embryo transfer in a university-based fertility clinic. PATIENT(S): Eighteen women with normal or decreased ovarian reserve. INTERVENTION(S): All patients were given gonadotropin stimulation in preparation for IVF with granulosa cells isolated at the time of follicular aspiration. MAIN OUTCOME MEASURE(S): Expression profiles of luteinized granulosa cells isolated from each woman were determined by using DNA microarray analysis. RESULT(S): Changes in patterns of gene expression in granulosa cells were observed between women with normal and diminished ovarian reserve. These genes included several anonymous expressed sequence tags and also expressed sequence tags that correspond to known genes. CONCLUSION(S): Expression profiling of granulosa cells by DNA microarray may yield signature patterns that reflect the status of ovarian reserve and the competence of granulosa cells.

Adult↗

PubMed2005

Assessment of a systematic expression profiling approach in ENU-induced mouse mutant lines.

Comparative genomewide expression profiling is a powerful tool in the effort to annotate the mouse genome with biological function. The systematic analysis of RNA expression data of mouse lines from the Munich ENU mutagenesis screen might support the understanding of the molecular biology of such mutants and provide new insights into mammalian gene function. In a direct comparison of DNA microarray experiments of individual versus pooled RNA samples of organs from ENU-induced mouse mutants, we provide evidence that individual RNA samples may outperform pools in some aspects. Genes with high biological variability in their expression levels (noisy genes) are identified as false positives in pooled samples. Evidence suggests that highly stringent housing conditions and standardized procedures for the isolation of organs significantly reduce biological variability in gene expression profiling experiments. Data on wild-type individuals demonstrate the positive effect of controlling variables such as social status, food intake before organ sampling, and stress with regard to reproducibility of gene expression patterns. Analyses of several organs from various ENU-induced mutant lines in general show low numbers of differentially expressed genes. We demonstrate the feasibility to detect transcriptionally affected organs employing RNA expression profiling as a tool for molecular phenotyping.

Animals↗

PubMed2001

Gene expression profiling of two related maize inbred lines with contrasting root-lodging traits.

To assist breeding for increased resistance to root lodging in maize, an attempt was made to identify genes that are associated with root lodging by profiling mRNA expression from two inbreds with contrasting root-related traits. These two inbreds were derived from a common F(2) pool, selfed for several generations and showed 75% relatedness based on 106 genetic markers. Under field conditions, the two inbreds exhibited significant differences in root morphology and resistance to root lodging. Whole root tissue was collected at two developmental stages from inbred 100 and 101 grown in 2 years. RNA was isolated from both the V8 and V12 stages, a few weeks prior to flowering. The RNA samples from the 1997 growing season were analysed by GeneCalling analysis, an open-ended mRNA profiling method. From over 13 500 cDNA fragments detected from each of the V8- and V12-stage samples, 229 and 325 cDNA fragments, respectively, showed greater than 2-fold differences between the two inbred lines. A total of 69 cDNA fragments that showed 2-fold or greater differences for both inbred lines were observed at both developmental stages. The gene identity and expression differences of several cDNA fragments were determined and confirmed by RNA gel blot analysis. Two genes out of five identified were homologous to a cytochrome P450 and the impedance-induced protein, both showing high levels of expression in the roots of lodging resistant lines and low levels in the sensitive lines. These data provide the first clues of genes expressed in the roots during the formative stages of root development associated with root-lodging resistance.

Amino Acid Sequence↗

PubMed2006

The expression profile of microRNAs in mouse embryos.

MicroRNAs (miRNAs), which are non-coding RNAs 18-25 nt in length, regulate a variety of biological processes, including vertebrate development. To identify new species of miRNA and to simultaneously obtain a comprehensive quantitative profile of small RNA expression in mouse embryos, we used the massively parallel signature sequencing technology that potentially identifies virtually all of the small RNAs in a sample. This approach allowed us to detect a total of 390 miRNAs, including 195 known miRNAs covering approximately 80% of previously registered mouse miRNAs as well as 195 new miRNAs, which are so far unknown in mouse. Some of these miRNAs showed temporal expression profiles during prenatal development (E9.5, E10.5 and E11.5). Several miRNAs were positioned in polycistron clusters, including one particular large transcription unit consisting of 16 known and 23 new miRNAs. Our results indicate existence of a significant number of new miRNAs expressed at specific stages of mammalian embryonic development and which were not detected by earlier methods.

Animals↗

PubMed2000

Serial analysis of gene expression as a tool to assess the human thyroid expression profile and to identify novel thyroidal genes.

The assessment of the expression profile of normal human thyroid tissue using serial analysis of gene expression (SAGE) generated a collection of 10,994 sequence transcripts (tags). Each tag represented a messenger RNA transcript, and, in total, 6099 different tags could be distinguished. The presence and abundance of thyroid-specific transcripts showed the overall expression profile to be from a normal thyroid cell. The expression level of several transcripts was confirmed on Northern blot. Seventy percent of tags could not be attributed to a known human gene and, therefore, possibly correspond to novel genes putatively involved in thyroid function. The tag sequence generated by the SAGE technique can be used to further characterize these novel genes. In this way, application of the SAGE technique to thyroid tissue gives insight in the expression profile of a normal thyroid gland and provides the information to characterize novel genes involved in thyroid pathology, such as congenital hypothyroidism and thyroid neoplasia.

Base Sequence↗

PubMed2004

Differential gene-expression profiles associated with gastric adenoma.

Gastric adenomas may eventually progress to adenocarcinomas at varying rates. The purpose of the present study was to identify gene-expression profiles linked to the heterogeneous nature of gastric adenoma as compared to adenocarcinoma. Suppression subtractive hybridisation analysis was performed to extract relevant genes from two cases of low- and high-grade gastric adenomas. The identified genes were quantified by RT-PCR in 14 low-grade adenoma, nine high-grade adenoma and nine adenocarcinoma samples, followed by hierarchical clustering analysis to separate tumours into groups according to their gene-expression profiles. Nine genes previously implicated in carcinogenesis in a variety of organs, including three genes related to gastric adenocarcinoma, were identified. The overexpression of these genes in gastric adenoma has not been reported previously. The clustering analysis of these nine genes across 32 cases identified three groups, one of which consisted primarily of adenocarcinomas, whereas the other two groups consisted of adenomas. One group of adenomas, characterised by larger tumour size, exhibited gene-expression profiles of an intestinal cell lineage implicated in the pathogenesis of an intestinal-type gastric adenocarcinoma. Another adenoma group consisting of low-grade adenomas with smaller tumour size exhibited a unique expression profile. In conclusion, clustering analysis of expression profiles using a limited number of genes may serve as molecular markers for gastric adenoma with different biological properties. Although the prognostic values of these gene-expression profiles need to be evaluated in further follow-up study of adenoma cases, these findings add new insights to (a) our understanding of the pathogenesis of gastric tumours, (b) the development of specific tumour markers for clinical practice, and (c) the design of novel therapeutic targets.

Adenocarcinoma↗

PubMed2002

Expression profiling in mouse fetal thymus reveals clusters of coordinately expressed genes that mark individual stages of T-cell ontogeny.

To search for genes that participate in regulatory networks sustaining mouse embryonic T-cell development, we have performed expression profiling using nylon macroarrays. Labeled samples representative of individual developmental stages were utilized, taking advantage of cell homogeneity during early thymus ontogeny. cDNAs revealing differential expression were further selected using labeled samples derived from lymphoid versus non-lymphoid tissues, and from mutant thymi exhibiting T-cell developmental defects. We thus identified clusters of coexpressed genes during T-cell embryogenesis and characterized their sequences through bioinformatics. We compare our results with those from other profiling analyses in the immune system, and discuss their implications for the definition of genes whose products are involved in T-cell development.

Animals↗

PubMedDate not supplied

Microarray analysis using amplified mRNA from laser capture microdissection of microscopic hepatocellular precancerous lesions and frozen hepatocellular carcinomas reveals unique and consistent gene expression profiles.

The indirect labeling cDNA microarray technique was used to evaluate gene expression profiles of pure cell populations from frozen sections of carcinomas and adenomas harvested from precancerous hepatocellular lesions by using laser capture microdissection (LCM). The levels of differentially expressed genes were investigated using a cDNA microarray with 9,984 features with only 2 ug of two-round amplified aRNA, equivalent to 35 cells from LCM-adenomas and frozen samples of carcinomas from simian virus 40 (SV40) large T antigen transgenic rats. A total of 855 genes were identified as being 3-fold or more differentially expressed in carcinomas or adenomas as compared to normal tissue controls. Among these 855 genes, 71 genes were differentially expressed in both carcinomas and adenomas. Commonly up-regulated genes in both carcinoma and adenomas were 28 while 41 of the 71 genes were commonly down-regulated. Two genes, Igh1 (immunoglobulin heavy chain 1(Serum IgG2a), Image clone ID: 875880) and EST clone (AI893585, Image clone ID: 596604) were more than 7-fold up-regulated in carcinomas and 6-fold down-regulated in adenomas. In Cy5 and Cy3 reciprocal experiments for screening out false positive signals, the amplified carcinomas showed higher Pearson Correlation Coefficient values (-0.94 and -0.92) than the LCM-amplified adenoma samples (-0.79 and -0.84). LCM-amplified samples provided higher signal intensities over backgrounds and a greater average of Cy5:Cy3 ratios. Expression levels of mRNAs from selected genes, determined by using traditional dot blot analysis, revealed that 36 of 40 tested expression profiles were consistent with the microarray data. Thus, amplified aRNA harvested from homogeneous cell types using LCM can be applied to study gene expression profiles by use of microarray analysis.

Animals↗

PubMed2006

Gene expression profiling of the human prostate zones.

OBJECTIVE: To investigate differences in gene expression in different zones of the prostate by microarray analyses, to better understand why aggressive tumours predominantly occur in the peripheral zone (PZ), whereas benign prostatic hyperplasia (BPH) occurs almost exclusively in the transition zone (TZ). MATERIALS AND METHODS: Expression profiling of both prostate zones was done by microarray analysis. Reverse transcription-polymerase chain reaction (RT-PCR) of the top 18 genes confirmed the microarray analyses. RT-PCR with common cell-type markers indicated that the differential expression between the zones was not caused by an unequal distribution of different cell types. Primary stromal and epithelial prostate cells were used to study cell type expression in the 12 highest differentially expressed zonal-specific genes. RESULTS: In all, 346 genes were identified as preferentially expressed in the TZ or PZ. A few of the TZ-specific genes, including ASPA, FLJ10970 and COCH, were also stroma-specific. Comparisons with other microarray studies showed that gene expression profiles of prostate cancer and BPH correlate with the expression profiles of the PZ and TZ, respectively. CONCLUSION: Gene expression differs between the PZ and TZ of the prostate, and stromal-epithelial interactions might be responsible for the distinct zonal localization of prostate diseases.

False Positive Reactions↗