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PubMed2002

Identification, using cDNA macroarray analysis, of distinct gene expression profiles associated with pathological and virological features of hepatocellular carcinoma.

It is still unclear as to whether the gene expression profile in HCV- or HBV-related HCC exhibits a degree of specificity and whether the development of HCC in a context of cirrhosis influences this gene profile. To address these issues, the expression profiles of 15 cases of HCC were analysed using cDNA macroarray. A global analysis and hierarchical clustering, demonstrated the heterogeneity of HCC patterns, with a majority of down-regulated genes. Statistical analysis clearly showed a distinction between the gene expression profiles of HCV- and HBV-related HCC. HBV-associated HCC exhibited involvement of different cellular pathways, those controlling apoptosis, p53 signalling and G1/S transition. In HCV-related HCC we identified a more heterogenous pattern with an over-expression of the TGF-beta induced gene. In HCC developing on non-cirrhotic tissues, beta-catenin encoding gene and genes implicated in the PKC pathway were specifically up-regulated. In addition, our investigation highlighted a distinct profiles of TGF-beta superfamily encoding genes in well, moderately or poorly differentiated HCC. Overall, our study supports the hypothesis that despite the heterogeneity of the HCC pattern, the large-scale screening of gene expression may provide data significant to our understanding of the mechanism of liver carcinogenesis.

Carcinoma, Hepatocellular↗
PubMed2006

The UVB-induced gene expression profile of human epidermis in vivo is different from that of cultured keratinocytes.

In order to obtain a comprehensive picture of the molecular events regulating cutaneous photodamage of intact human epidermis, suction blister roofs obtained after a single dose of in vivo ultraviolet (UV)B exposure were used for microarray profiling. We found a changed expression of 619 genes. Half of the UVB-regulated genes had returned to pre-exposure baseline levels at 72 h, underscoring the transient character of the molecular cutaneous UVB response. Of special interest was our finding that several of the central p53 target genes remained unaffected following UVB exposure in spite of p53 protein accumulation. We next compared the in vivo expression profiles of epidermal sheets to that of cultured human epidermal keratinocytes exposed to UVB in vitro. We found 1931 genes that differed in their expression profiles between the two groups. The expression profile in intact epidemis was geared mainly towards DNA repair, whereas cultured keratinocytes responded predominantly by activating genes associated with cell-cycle arrest and apoptosis. These differences in expression profiles might reflect differences between mature differentiating keratinocytes in the suprabasal epidermal layers versus exponentially proliferating keratinocytes in cell culture. Our findings show that extreme care should be taken when extrapolating from findings based on keratinocyte cultures to changes in intact epidermis.

Adult↗
PubMed2006

Nuclear-mitochondrial genomic profiling reveals a pattern of evolution in epithelial ovarian tumor stem cells.

Analyses of genome orthologs in cancer on the background of tumor heterogeneity, coupled with the recent identification that the tumor propagating capacity resides within a very small fraction of cells (the tumor stem cells-TSCs), has not been achieved. Here, we describe a strategy to explore genetic drift in the mitochondrial genome accompanying varying stem cell dynamics in epithelial ovarian cancer. A major and novel outcome is the identification of a specific mutant mitochondrial DNA profile associated with the TSC lineage that is drastically different from the germ line profile. This profile, however, is often camouflaged in the primary tumor, and sometimes may not be detected even after metastases, questioning the validity of whole tumor profiling towards determining individual prognosis. Continuing mutagenesis in subsets with a mutant mitochondrial genome could result in transformation through a cooperative effect with nuclear genes - a representative example in our study is a tumor suppressor gene viz. cAMP responsive element binding binding protein. This specific profile could be a critical predisposing step undertaken by a normal stem cell to overcome a tightly regulated mutation rate and DNA repair in its evolution towards tumorigenesis. Our findings suggest that varying stem cell dynamics and mutagenesis define TSC progression that may clinically translate into increasing tumor aggression with serious implications for prognosis.

Adenocarcinoma, Papillary↗
PubMed2006

Vascular biology: cellular and molecular profiling.

Our understanding of the mechanisms underlying cerebrovascular atherosclerosis has improved in recent years, but significant gaps remain. New insights into the vascular biological processes that result in ischemic stroke may come from cellular and molecular profiling studies of the peripheral blood. In recent cellular profiling studies, increased levels of a proinflammatory T-cell subset (CD4 (+)CD28 (-)) have been associated with stroke recurrence and death. Expansion of this T-cell subset may occur after ischemic stroke and be a pathogenic mechanism leading to recurrent stroke and death. Increases in certain phenotypes of endothelial cell microparticles have been found in stroke patients relative to controls, possibly indicating a state of increased vascular risk. Molecular profiling approaches include gene expression profiling and proteomic methods that permit large-scale analyses of the transcriptome and the proteome, respectively. Ultimately panels of genes and proteins may be identified that are predictive of stroke risk. Cellular and molecular profiling studies of the peripheral blood and of atherosclerotic plaques may also pave the way for the development of therapeutic agents for primary and secondary stroke prevention.

Atherosclerosis↗
PubMed2004

Sister grouping of chimpanzees and humans as revealed by genome-wide phylogenetic analysis of brain gene expression profiles.

Gene expression profiles from the anterior cingulate cortex (ACC) of human, chimpanzee, gorilla, and macaque samples provide clues about genetic regulatory changes in human and other catarrhine primate brains. The ACC, a cerebral neocortical region, has human-specific histological features. Physiologically, an individual's ACC displays increased activity during that individual's performance of cognitive tasks. Of approximately 45,000 probe sets on microarray chips representing transcripts of all or most human genes, approximately 16,000 were commonly detected in human ACC samples and comparable numbers, 14,000-15,000, in gorilla and chimpanzee ACC samples. Phylogenetic results obtained from gene expression profiles contradict the traditional expectation that the non-human African apes (i.e., chimpanzee and gorilla) should be more like each other than either should be like humans. Instead, the chimpanzee ACC profiles are more like the human than like the gorilla; these profiles demonstrate that chimpanzees are the sister group of humans. Moreover, for those unambiguous expression changes mapping to important biological processes and molecular functions that statistically are significantly represented in the data, the chimpanzee clade shows at least as much apparent regulatory evolution as does the human clade. Among important changes in the ancestry of both humans and chimpanzees, but to a greater extent in humans, are the up-regulated expression profiles of aerobic energy metabolism genes and neuronal function-related genes, suggesting that increased neuronal activity required increased supplies of energy.

Animals↗
PubMed2005

Transcriptional profiling of the left and median liver lobes of male f344/n rats following exposure to acetaminophen.

The liver is a common organ for transcriptional profiling because of its role in xenobiotic metabolism and because hepatotoxicity is a common response to chemical exposure. To explore the impact that sampling different lobes may have on transcriptional profiling experiments we have examined and compared gene expression profiles of the left and median lobes of livers from male F344 rats exposed to toxic and nontoxic doses of acetaminophen. Transcript profiling using micorarrays revealed clear differences in the response of the left and median liver lobes of F344 rats to acetaminophen exposure both at low doses as well as doses that caused hepatotoxicity. Differences were found in the total number of differentially expressed genes in the left and median lobes, the number and identity of genes that were differentially expressed uniquely only in the left or median lobe, and in the patterns of gene expression. While it is not possible to generalize these results to compounds other than acetaminophen or other strains of rat, these results highlight the potential impact of sampling differences on the interpretation of gene expression profiles in the liver.

Acetaminophen↗
PubMed2006

Expression profiling of peripheral-blood mononuclear cells from patients with chronic hepatitis C undergoing interferon therapy.

BACKGROUND: Interferon (IFN) is now the standard treatment for chronic hepatitis C (CH-C); however, treatment efficacy is unpredictable before IFN therapy is started. METHODS: We investigated the gene-expression profiles of peripheral-blood mononuclear cells (PBMCs) from patients with CH-C showing different responses to IFN. Gene-expression profiles of PBMCs were analyzed in 21 patients with CH-C treated with IFN alone or in combination with ribavirin as well as in 6 healthy volunteers. Serial changes in the gene-expression profiles of PBMCs from individual patients were evaluated before treatment, 2 weeks after the start of IFN therapy, and 6 months after the completion of IFN therapy. RESULTS: Interestingly, the gene-expression profiles of PBMCs from patients with CH-C and healthy volunteers differed substantially; early T cell-activation antigen CD69 was significantly up-regulated in patients with CH-C, but immune-related molecules such as chemokine (C-C motif) receptor 2 and interleukin 7 receptor were significantly down-regulated. Selected combinations of expressed genes obtained before treatment and during IFN therapy by use of a fuzzy neural network combined with the SWEEP operator method predicted the outcome of IFN therapy with peak accuracies of 91.0% and 90.2%, respectively. CONCLUSIONS: These findings suggest that the gene-expression profiles of PBMCs from patients with CH-C may be useful biomarkers for IFN therapy.

Adult↗
PubMedDate not supplied

Evaluation of an in vitro model of hepatic inflammatory response by gene expression profiling.

The body's response to biochemical stress involves coordinated changes in the expression of several sets of genes that regulate its return to homeostasis. Although several cell culture systems have been utilized for studying such complex physiological events in vitro, their assessment has been limited to biochemical assays on individual genes and proteins, limiting interpretation of the results in a systems context. Advances in genomics provide an opportunity to provide a more comprehensive assessment. In this study, we have used DNA microarrays to profile gene expression dynamics during interleukin 6-stimulated inflammation in hepatocytes maintained in a stable, collagen double-gel in vitro model system. The observed expression profile was also compared with that obtained from rat liver tissue after burn injury to determine the extent and nature of responses captured by the in vitro system. Our results indicate that several aspects of the in vivo hepatic inflammatory response can be captured by the in vitro system at the molecular systems level. Statistical analysis of the mRNA profiles was also used to characterize the temporal response in each model system and demonstrate similar behavior. A small panel of molecules involved in the hepatic acute-phase response was also profiled, using quantitative kinetic polymerase chain reaction, to confirm these observations. These results indicate the utility of the stable hepatocyte culture system for expression profiling of inflammatory states and for providing insights into the interplay of changes in gene expression during complex physiological states.

Acute-Phase Reaction↗
PubMed2005

Advancing the molecular diagnosis of thyroid nodules: defining benign lesions by molecular profiling.

BACKGROUND: Thyroid nodules are common and most are benign. Previous data from our laboratory and others has suggested that gene profiling can accurately distinguish between benign and malignant thyroid nodules and provide new leads in the study of thyroid tumorigenesis. Current preoperative techniques do not permit distinction between neoplastic and hyperplastic follicular neoplasms. These studies were undertaken to determine whether benign follicular tumors could be subcategorized by molecular profiling. METHODS: Molecular profiles of 8 follicular adenomas and 8 hyperplastic nodules were analyzed by oligonucleotide microarray analysis. A list of 402 differentially expressed genes was produced based on a comparison of these two groups. Seven additional benign follicular lesions were then added to the analysis. A hierarchical clustering analysis was performed on all 23 samples, utilizing the gene list generated from the test set, to examine the groups for potential differences and the ability of the gene list to distinguish tumor types. RESULTS: Cluster analysis of all 23 samples produced two distinct groups, one containing the adenomas and one containing the hyperplastic lesions. The analysis was able to identify follicular adenomas with a sensitivity of 84.6% and a specificity of 100%. CONCLUSIONS: These data indicate that benign thyroid lesions can be separated into distinct groups through molecular profiling. Analysis of the gene list may help further the understanding of thyroid tumorigenesis. Expression profiling may ultimately allow us to distinguish potentially malignant from benign follicular nodules.

Biomarkers↗
PubMed2002

Large-scale analysis of gene expression profiles.

The accumulation of DNA microarray data has now made it possible to use gene expression profiles to analyse expression data. A gene expression profile contains the expression data for a given gene over various samples, and can be contrasted with an expression signature, which contains the expression data for a single sample. Gene expression profiles are most revealing when samples are grouped appropriately, either by standard clinical or pathological categories or by categories discovered through cluster analysis techniques. Expression profiles can exist at various levels of abstraction, yielding information across various tissues or across diseases within a particular tissue. Hypothesis tests may be applied to expression profiles on a large scale to identify candidate genes of interest.

Cluster Analysis↗
PubMed2002

Comparing expression profiles of genes with similar promoter regions.

MOTIVATION: Gene regulatory elements are often predicted by seeking common sequences in the promoter regions of genes that are clustered together based on their expression profiles. We consider the problem in the opposite direction: we seek to find the genes that have similar promoter regions and determine the extent to which these genes have similar expression profiles. RESULTS: We use the data sets from experiments on Saccharomyces cerevisiae. Our similarity measure for the promoter regions is based on the set of common mapped or putative transcription factor binding sites and other regulatory elements in the upstream region of the genes, as contained in the Saccharomyces cerevisiae Promoter Database. We pair up the genes with high similarity scores and compare their expression levels in time-course experiment data. We find that genes with similar promoter regions on the average have significantly higher correlation, but it can vary widely depending on the genes. This confirms that the presence of similar regulatory elements often does not correspond to similarity in expression profiles and indicates that finding transcription factor binding sites or other regulatory elements starting with the expression patterns may be limited in many cases. Regardless of the correlation, the degree to which the profiles agree under different experimental conditions can be examined to derive hypotheses concerning the role of common regulatory elements. Overall, we find that considering the relationship between the promoter regions and the expression profiles starting with the regulatory elements is a difficult but useful process that can provide valuable insights.

Databases, Nucleic Acid↗
PubMed2003

Ligand-Info, searching for similar small compounds using index profiles.

MOTIVATION: The Ligand-Info system is based on the assumption that small molecules with similar structure have similar functional (binding) properties. The developed system enables a fast and sensitive index based search for similar compounds in large databases. Index profiles, constructed by averaging indexes of related molecules are used to increase the specificity of the search. The utilization of index profiles helps to focus on frequent, common features of a family of compounds. RESULTS: A Java-based tool for clustering and scanning of small molecules has been created. The tool can interactively cluster sets of molecules and create index profiles on the user side and automatically download similar molecules from a databases of 250 000 compounds. The results of the application of index profiles demonstrate that the profile based search strategy can increase the quality of the selection process. AVAILABILITY: The system is available at http://Ligand.Info. The application requires the Java Runtime Environment 1.4, which can be automatically installed during the first use on desktop systems, which support it. A standalone version of the program is available from the authors upon request.

Binding Sites↗
PubMed2006

A mixture model with random-effects components for clustering correlated gene-expression profiles.

MOTIVATION: The clustering of gene profiles across some experimental conditions of interest contributes significantly to the elucidation of unknown gene function, the validation of gene discoveries and the interpretation of biological processes. However, this clustering problem is not straightforward as the profiles of the genes are not all independently distributed and the expression levels may have been obtained from an experimental design involving replicated arrays. Ignoring the dependence between the gene profiles and the structure of the replicated data can result in important sources of variability in the experiments being overlooked in the analysis, with the consequent possibility of misleading inferences being made. We propose a random-effects model that provides a unified approach to the clustering of genes with correlated expression levels measured in a wide variety of experimental situations. Our model is an extension of the normal mixture model to account for the correlations between the gene profiles and to enable covariate information to be incorporated into the clustering process. Hence the model is applicable to longitudinal studies with or without replication, for example, time-course experiments by using time as a covariate, and to cross-sectional experiments by using categorical covariates to represent the different experimental classes. RESULTS: We show that our random-effects model can be fitted by maximum likelihood via the EM algorithm for which the E(expectation)and M(maximization) steps can be implemented in closed form. Hence our model can be fitted deterministically without the need for time-consuming Monte Carlo approximations. The effectiveness of our model-based procedure for the clustering of correlated gene profiles is demonstrated on three real datasets, representing typical microarray experimental designs, covering time-course, repeated-measurement and cross-sectional data. In these examples, relevant clusters of the genes are obtained, which are supported by existing gene-function annotation. A synthetic dataset is considered too. AVAILABILITY: A Fortran program blue called EMMIX-WIRE (EM-based MIXture analysis WIth Random Effects) is available on request from the corresponding author.

Algorithms↗
PubMed2006

Parallel changes in metabolite and expression profiles in crooked-tail mutant and folate-reduced wild-type mice.

Anomalies in homocysteine (HCY) and folate metabolism are associated with common birth defects and adult diseases, several of which can be suppressed with dietary folate supplementation. Although supplementation reduces the occurrence and severity of neural tube defects (NTDs), many cases are resistant to these beneficial effects. The basis for variable response and biomarkers that predict responsiveness are unknown. Crooked-tail (Cd) mutant mice are an important model of folate-responsive NTDs. To identify features that are diagnostic for responsiveness versus resistance to dietary folate supplementation, we surveyed metabolite and expression levels in liver samples from folate-supplemented, folate-reduced and control diets in Cd mutant and wild-type adult females. Cd homozygotes had normal total homocysteine (tHcy) levels suggesting that folate suppresses NTDs through a mechanism that does not involve modulating serum tHcy levels. Instead, parallel changes in metabolite and expression profiles in folate-supplemented Cd/Cd homozygotes and folate-reduced+/+and Cd/+mice suggest that Crooked-tail homozygotes have a defect in the utilization of intracellular folate. Then, by combining these expression and metabolite profile results with published results for other models and their controls, two clusters were found, one of which included several folate-responsive NTD models and the other previously untested and presumably folate-resistant models. The predictive value of these profiles was verified by demonstrating that NTDs of Ski-/-mutant mice, whose profile suggested resistance to folate supplementation, were not suppressed with dietary folate supplementation. These results raise the possibility of using metabolite and expression profiles to distinguish folate-responsive and resistance adult females who are at risk for bearing fetuses with an NTD.

Animals↗
PubMed2004

Molecular classification of human endometrial cycle stages by transcriptional profiling.

Endometrium is a dynamic tissue that undergoes cyclic changes each month, under the overall control of estrogen and progesterone. The aims of this study were to investigate the changing global gene expression profile of human endometrium during the menstrual cycle using microarray technology and to determine the correlation between histopathological evaluation and molecular profile of the samples. Standard two-colour cDNA microarrays were performed on the 43 samples against a common reference, using a 10.5 K cDNA glass slide microarray. The results were validated using real-time PCR. Analysis of expression data was carried out using parametric analysis of variance with Benjamini-Hochberg correction. Hierarchical clustering reveals a strong relationship between histopathology and transcriptional profile of the samples. The study identified 1452 genes that showed significant changes in expression (P< or =0.05) across the menstrual cycle, with 425 genes having changes that are at least 2-fold. The data were also independently analysed by a CSIRO algorithm called GeneRaVE that identified a small subset of genes whose expression profiles could be used to classify nearly all the biopsies into their correct cycle stage. We also identified and validated three genes [(natural cytotoxicity triggering receptor (NCR)3, fucosyl transferase (FUT)4 and Fyn-binding protein (FYB)] that had not been shown to have significant cyclic changes in the human endometrium, previously. We have shown for the first time that endometrial cycle stage prediction is possible based on global gene expression profile.

Adaptor Proteins, Signal Transducing↗
PubMed2002

Gene expression analysis reveals chemical-specific profiles.

The application of gene expression profiling technology to examine multiple genes and signaling pathways simultaneously promises a significant advance in understanding toxic mechanisms to ultimately aid in protection of public health. Public and private efforts in the new field of toxicogenomics are focused on populating databases with gene expression profiles of compounds where toxicological and pathological endpoints are well characterized. The validity and utility of a toxicogenomics is dependent on whether gene expression profiles that correspond to different chemicals can be distinguished. The principal hypothesis underlying a toxicogenomic or pharmacogenomic strategy is that chemical-specific patterns of altered gene expression will be revealed using high-density microarray analysis of tissues from exposed organisms. Analyses of these patterns should allow classification of toxicants and provide important mechanistic insights. This report provides a verification of this hypothesis. Patterns of gene expression corresponding to liver tissue derived from chemically exposed rats revealed similarity in gene expression profiles between animals treated with different agents from a common class of compounds, peroxisome proliferators [clofibrate (ethyl-p-chlorophenoxyisobutyrate), Wyeth 14,643 ([4-chloro-6(2,3-xylidino)-2-pyrimidinylthio]acetic acid), and gemfibrozil (5-2[2,5-dimethylphenoxy]2-2-dimethylpentanoic acid)], but a very distinct gene expression profile was produced using a compound from another class, enzyme inducers (phenobarbital).

Animals↗
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↗
PubMed2006

Transcriptional profiling of a Staphylococcus aureus clinical isolate and its isogenic agr and sarA mutants reveals global differences in comparison to the laboratory strain RN6390.

The production of Staphylococcus aureus virulence factors is under the control of complex regulatory circuits. Most studies aimed at defining these regulatory networks have focused on derivatives of the strain NCTC 8325, most notably RN6390. However, all NCTC 8325 derivatives, including RN6390, possess an 11 bp deletion in rsbU. This deletion renders NCTC 8325 derivatives naturally sigma-factor-B deficient. Recent studies have shown that RN6390 is also deficient, in comparison to clinical isolates, with respect to biofilm formation, a process which is important for both pathogenesis and antimicrobial resistance. Based on these considerations, the authors carried out genome-scale transcriptional profiling, comparing RN6390 with the virulent rsbU-positive clinical isolate UAMS-1. The results revealed significant genome-wide differences in expression patterns between RN6390 and UAMS-1, and suggested that the overall transcriptional profile of UAMS-1 is geared toward expression of factors that promote colonization and biofilm formation. In contrast, the transcriptional profile of RN6390 was heavily influenced by RNAIII expression, resulting in a phenotype characterized by increased production of exoproteins, and decreased capacity to form a biofilm. The greater influence of agr in RN6390 relative to UAMS-1 was also evident when the transcriptional profile of UAMS-1 was compared with that of its isogenic sarA and agr mutants. Specifically, the results indicate that, in contrast to NCTC 8325 derivatives, agr plays a limited role in overall regulation of gene expression in UAMS-1, when compared with sarA. Furthermore, by defining the sarA regulon in a biofilm-positive clinical isolate, and comparing the results with transcriptional profiling experiments defining biofilm-associated gene expression patterns in the same strain, the authors identified a sarA-regulated operon (alsSD) that is also induced in biofilms, and demonstrated that mutation of alsSD results in reduced capacity to form a biofilm.

Adaptation, Physiological↗