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PubMed2004

Prediction of mechanisms of action of antibacterial compounds by gene expression profiling.

We have generated a database of expression profiles carrying the transcriptional responses of the model organism Bacillus subtilis following treatment with 37 well-characterized antibacterial compounds of different classes. The database was used to build a predictor for the assignment of the mechanisms of action (MoAs) of antibacterial compounds by the use of support vector machines. This predictor was able to correctly classify the MoA class for most compounds tested. Furthermore, we provide evidence that the in vivo MoA of hexachlorophene does not match the MoA predicted from in vitro data, a situation frequently faced in drug discovery. A database of this kind may facilitate the prioritization of novel antibacterial entities in drug discovery programs. Potential applications and limitations are discussed.

Anti-Bacterial Agents↗

PubMed2005

Gene expression profiling allows distinction between primary and metastatic squamous cell carcinomas in the lung.

Lung neoplasms commonly develop in patients previously treated for head and neck carcinomas. The derivation of these tumors, either as new primary lung cancers or as metastatic head and neck cancers, is difficult to establish based on clinical or histopathologic criteria since both are squamous cell carcinomas and have identical features under light microscopy. However, this distinction has significant treatment and prognostic implications. Gene expression profiling was performed on a panel of 52 sequentially collected patients with either primary lung (n = 21) or primary head and neck (n = 31) carcinomas using the Affymetrix HG_U95Av2 high-density oligonucleotide microarray. Unsupervised hierarchical clustering with Ward linkage and the Pearson correlation metric was performed. To assess robustness, bootstrap resampling was performed with 1,000 iterations. A t test of the normalized values for each gene was used to determine the genes responsible for segregating head and neck from lung primary carcinomas, and those with the most differential expression were used for later analyses. In the absence of a large "test" set of tumors, we used a supervised leave-one-out cross-validation to test how well we could predict the tumor origin. Once a gene expression profile was established, 12 lung lesions taken from patients with previously treated head and neck cancers were similarly analyzed by gene expression profiling to determine their sites of origin. Unsupervised clustering analysis separated the study cohort into two distinct groups which reliably remained segregated with bootstrap resampling. Group 1 consisted of 30 tongue carcinomas. Group 2 consisted of 21 lung cancers and 1 tongue carcinoma. The clustering was not changed even when normal lung or tongue profiles were subtracted from the corresponding carcinomatous lesions, and a leave-one-out cross-validation showed a 98% correct prediction (see Supplementary Data 1). A minimum set of 500 genes required to distinguish these groups was established. Given the ability to segregate these lesions using molecular profiling, we analyzed the lung tumors of undetermined origin. All cases clearly clustered with either lung or tongue tumor subsets, strongly supporting our hypothesis that this technique could elucidate the tissue of origin of metastatic lesions. Although histologically similar, squamous cell carcinomas have distinct gene expression profiles based on their anatomic sites of origin. Accordingly, the application of gene expression profiling may be useful in identifying the derivation of lung nodules and consequently enhances treatment planning.

Algorithms↗

PubMedDate not supplied

On predicting medulloblastoma metastasis by gene expression profiling.

Accurately predicting clinical outcome or metastatic status from gene expression profiles remains one of the biggest hurdles facing the adoption of predictive medicine. Recently, MacDonald et al. (Nat. Genet. 2001, 29, 143-152) used gene expression profiles, from samples taken at diagnosis, to distinguish between clinically designated metastatic and nonmetastatic primary medulloblastomas, helping to elucidate the genetic mechanisms underlying metastasis and suggesting novel therapeutic targets. The obtained accuracy of predicting metastatic status does not, however, reach statistical significance on Fisher's exact test, although 22 training samples were used to make each prediction via leave-one-out testing. This paper introduces readily implemented nonlinear filters to transform sequences of gene expression levels into output signals that are significantly easier to classify and predict metastasis. It is shown that when only 3 exemplars each from the metastatic and nonmetastatic classes were assumed known, a predictor was constructed whose accuracy is statistically significant over the remaining profiles set aside as a test set. The predictor was as effective in recognizing metastatic as nonmetastatic medulloblastomas, and may be helpful in deciding which patients require more aggressive therapy. The same predictor was similarly effective on an independent set of 5 nonmetastatic tumors and 3 metastatic cell lines also used by MacDonald et al.

Gene Expression Profiling↗

PubMed2002

Transcriptional expression profiles of oral squamous cell carcinomas.

BACKGROUND: Currently, the classification of oral squamous cell carcinoma (OSCC) depends heavily on the clinical and pathologic examination of tissue. This system can lead to the classification of potentially heterogeneous tumors into single groups when they may have different degrees of aggressiveness. No system to date has incorporated genetic changes as a factor by which to classify OSCC tumors. METHODS: To test the hypothesis that OSCC has a genome-wide genetic expression profile that differs from normal oral tissue and that transcriptional expression profiling can be used to characterize the heterogeneity among tumors, the authors examined the genetic expression profiles of 26 invasive squamous cell carcinomas of the oral cavity and oropharynx, 2 premalignant lesions, and 18 normal oral tissue samples using oligonucleotide arrays that contained probes representing approximately 7000 full-length human genes. RESULTS: Using hierarchical clustering analysis, the data show that oral carcinomas are distinguishable from normal oral tissue based on genome-wide transcriptional expression patterns. However, there is genetic expression profile heterogeneity among tumors of a particular histopathologic grade and stage. In addition, using a statistical approach that integrated normalization and regression analysis, the authors found 314 genes that were expressed differentially in the OSCC samples with statistical significance (P <or= 0.05). Of these, 239 genes were overexpressed in the OSCC samples, whereas 75 genes were down-regulated. CONCLUSIONS: No statistically significant differences in gene expression were found between early-stage disease and late-stage disease or between metastatic tumors and nonmetastatic tumors. The implications of these findings for the prediction of clinical outcome and for the discovery of new OSCC tumor markers are discussed.

Carcinoma, Squamous Cell↗

PubMed2006

Gene expression profiling to monitor therapeutic and adverse effects of antisense therapies for Duchenne muscular dystrophy.

OBJECTIVES: The objective of this study was to assess the utility of the gene expression profiling technique for the preclinical evaluation of drug efficacy and safety, taking a new therapeutic approach for Duchenne muscular dystrophy (DMD) as an example. METHODS: Muscles from dystrophin-deficient (mdx) mice, a well-characterized animal model for DMD, were injected with antisense constructs that restore the open reading frame in the Dmd gene. Synthetic antisense oligonucleotides (AONs) complexed with different carriers to enhance cellular uptake and recombinant adeno-associated virus (rAAV)-expressed antisense sequences were evaluated. Muscular gene expression profiles were analyzed on oligonucleotide microarrays. RESULTS: Polyethylenimine (PEI)-complexed AONs restored the reading frame slightly more effectively than uncomplexed, F127- or Optison-complexed AONs. However, PEI induced the expression of many immune genes, reflecting an aggravation of the inflammation present in untreated mdx mice. Expression profiles in Optison and F127-injected muscles were similar to those of saline treated muscles, implying that these carriers did not evoke adverse responses. Due to moderate levels of exon skipping, a significant shift toward wild-type expression levels was not detected. Injection with rAAV vectors resulted in much higher production of dystrophin and greatly improved the histological appearance of the muscle. Depending on the efficacy of the treatment, the expression of genes previously shown to be elevated in muscular dystrophies, partly or completely returned to wild-type expression levels. Reductions in inflammation and fibrosis were among the most prominent changes observed. CONCLUSION: Expression profiling is a powerful tool for the evaluation of both desired and adverse effects of new pharmacological therapies. It is sensitive and detects changes that are not histologically visible. In addition, its ability to simultaneously monitor a large number of different biological processes not only reduces the number of different assays required in preclinical research and clinical trials, but may also assist in the early detection of potential side effects.

Animals↗

PubMed2003

Genome-wide germline-enriched and sex-biased expression profiles in Caenorhabditis elegans.

We performed a genome-wide analysis of gene expression in C. elegans to identify germline- and sex-regulated genes. Using mutants that cause defects in germ cell proliferation or gametogenesis, we identified sets of genes with germline-enriched expression in either hermaphrodites or males, or in both sexes. Additionally, we compared gene expression profiles between males and hermaphrodites lacking germline tissue to define genes with sex-biased expression in terminally differentiated somatic tissues. Cross-referencing hermaphrodite germline and somatic gene sets with in situ hybridization data demonstrates that the vast majority of these genes have appropriate spatial expression patterns. Additionally, we examined gene expression at multiple times during wild-type germline development to define temporal expression profiles for these genes. Sex- and germline-regulated genes have a non-random distribution in the genome, with especially strong biases for and against the X chromosome. Comparison with data from large-scale RNAi screens demonstrates that genes expressed in the oogenic germline display visible phenotypes more frequently than expected.

Animals↗

PubMed2003

Monitoring human radiation exposure by gene expression profiling: possibilities and pitfalls.

Advances in high throughput analysis of mRNA expression have made it possible to establish gene expression profiles for different cells, tissues, diseases and exposure states. For instance, recent studies have demonstrated the utility of such an approach to classify sub-types of cancers with more detail than was previously possible. In addition, gene expression studies of ionizing radiation exposure both in vitro and in vivo are affording insight into the molecular mechanisms of mammalian radiation response. We have demonstrated that radiation expression profiles are a good predictor of p53 function in cell lines, and such profiles also indicate a major role for p53-regulated genes in the in vivo radiation response. Gene expression can be a sensitive indicator of radiation response as we have shown linear dose-responses for induction of several genes down to doses as low as 2 cGy. As profiles are established from radiation studies, it is hoped that they may be useful for identifying individuals with specific exposures or predisposition to negative outcome of exposure. Although this technology holds great promise, some obstacles remain to be overcome before it can be successfully applied to population studies.

Cyclin-Dependent Kinase Inhibitor p21↗

PubMed2002

Monitoring the expression profiles of 7000 Arabidopsis genes under drought, cold and high-salinity stresses using a full-length cDNA microarray.

Full-length cDNAs are essential for functional analysis of plant genes in the post-sequencing era of the Arabidopsis genome. Recently, cDNA microarray analysis has been developed for quantitative analysis of global and simultaneous analysis of expression profiles. We have prepared a full-length cDNA microarray containing approximately 7000 independent, full-length cDNA groups to analyse the expression profiles of genes under drought, cold (low temperature) and high-salinity stress conditions over time. The transcripts of 53, 277 and 194 genes increased after cold, drought and high-salinity treatments, respectively, more than fivefold compared with the control genes. We also identified many highly drought-, cold- or high-salinity- stress-inducible genes. However, we observed strong relationships in the expression of these stress-responsive genes based on Venn diagram analysis, and found 22 stress-inducible genes that responded to all three stresses. Several gene groups showing different expression profiles were identified by analysis of their expression patterns during stress-responsive gene induction. The cold-inducible genes were classified into at least two gene groups from their expression profiles. DREB1A was included in a group whose expression peaked at 2 h after cold treatment. Among the drought, cold or high-salinity stress-inducible genes identified, we found 40 transcription factor genes (corresponding to approximately 11% of all stress-inducible genes identified), suggesting that various transcriptional regulatory mechanisms function in the drought, cold or high-salinity stress signal transduction pathways.

Arabidopsis↗

PubMed2001

TissueInfo: high-throughput identification of tissue expression profiles and specificity.

We describe TissueInfo, a knowledge-based method for the high-throughput identification of tissue expression profiles and tissue specificity. TissueInfo defines a set of tissue information calculations that can be computed for large numbers of genes, expressed sequence tags (ESTs) or proteins. Tissue information records that result from the TissueInfo calculations are used to generate tables suitable for data mining and for the selection of genes according to a given expression profile or specificity. When benchmarked against a test set of 116 proteins and literature information, TissueInfo was found to be accurate for 69% of identified tissue specificities and for 80% of expression profiles. The accuracy of the identifications can be increased if query sequences for which little information is available from dbEST are ignored. Thus, with 80% coverage, TissueInfo achieves an accuracy of 76% for specificity and 89% for expression. For the same set of proteins, the curated tissue specificity offered in SWISS-PROT was accurate in 78% of cases. TissueInfo can be useful for the selection of clones for custom microarrays, selection of training sets for ab initio identification of tissue information, gene discovery and genome-wide predictions. Further information about the program can be found at http://icb.mssm.edu/tissueinfo.

Computational Biology↗

PubMed2006

Unique sequence and expression profiles of rat galectins-5 and -9 as a result of species-specific gene divergence.

Presence of species-specific gene divergence in a protein family prompts to thoroughly study structural aspects and expression profiles of the products. We herein focus on two members of an adhesion/growth-regulatory group of endogenous lectins, i.e. galectins-5 and -9. After first ascertaining species specificity of occurrence of galectin-5, constituted by a short section of rat galectin-9's N-terminal part and its C-terminal carbohydrate recognition domain, by database mining, we next detected and defined sequence differences in the proximal promoter region between the two genes. The ensuing hypothesis for distinct expression profiles was tested first by RT-PCR and then by immunohistochemistry. For the latter purpose, we employed antibodies rigorously controlled for absence of cross-reactivity including assays with various other galectins and, if necessary, refined by chromatographic removal of bi- or oligospecific activities. Indeed, the galectins have non-identical expression profiles, qualitative differences, e.g. seen for galectin-5-positive bone marrow and erythrocytes or for hitherto unknown expression in cells of the theca folliculi and galectin-9-positive skin epidermis and esophageal epithelium. Lack of hepatocyte or renal cortex staining separates these two expression profiles in rat from localization of galectin-9 in mouse. Interspecies extrapolation in a case of a galectin involved in unique gene divergence may thus not be valid. The presented results on galectin-5 relative to galectin-9 intimate distinct functions especially in erythropoiesis and imply currently unknown mechanisms to compensate its absence from the galectin network in other mammals.

Amino Acid Sequence↗

PubMed2006

[Preliminary study of gene expression profiling in human type I and II endometrial carcinoma].

OBJECTIVE: To study gene expression profiling in human type I and II endometrial carcinoma. METHODS: Six Affymetrix human genome genechips were utilized to investigate the differences in gene expression profiles between type I and II endometrial carcinoma with bioinformatic analysis. RESULTS: Many genes were highly expressed in estrogen-dependent endometrial carcinoma, and some of them were involved in the metabolism and conversion of estrogen, while some others in estrogen regulation. CYP2C9, for instance, was involved in the conversion of estrogen sulfate to 16-hydroxy sulfate metabolite, DDC in estrogen-dependent pathogenesis of endometrial carcinoma possibly by DDC interaction with AR to enhance steroid receptor transcription. CONCLUSION: High expression of these genes in estrogen-dependent endometrial carcinoma may provide insights into their roles in the pathogenesis and prognosis of this malignancy.

Adenocarcinoma↗

PubMed2006

A distinct inflammatory gene expression profile in patients with psoriatic arthritis.

Psoriatic arthritis (PsA) is a systemic inflammatory condition featuring polyarthritis associated with psoriasis. Apart from clinical indicators, few biomarkers exist to aid in the diagnosis and management of PsA. We hypothesized that whole blood gene expression profiling would provide new diagnostic markers and/or insights into pathogenesis of the disease. We compared whole blood gene expression profiles in PsA patients and in age-matched controls. We identified 310 differentially expressed genes, the majority of which are upregulated in PsA patients. The PsA expression profile does not significantly overlap with profiles derived from patients with rheumatoid arthritis or systemic lupus erythematosus. Logistic regression identified two lymphocyte-specific genes (zinc-finger protein 395 and phosphoinositide-3-kinase 2B) that discriminate PsA patients from normal controls. In addition, a highly coregulated cluster of overexpressed genes implicated in protein kinase A regulation strongly correlates with erythrocyte sedimentation rate. Other clusters of coregulated, yet suppressed genes in PsA patient blood include molecules involved in T-cell signaling. Finally, differentially expressed genes in PsA fall into diverse functional categories, but many downregulated genes belong to a CD40 signaling pathway. Together, the data suggest that gene expression profiles of PsA patient blood contain candidate novel disease markers and clues to pathogenesis.

Adolescent↗

PubMed2005

Gene expression profile in oral squamous cell carcinoma: a pilot study.

PURPOSE: To study the gene expression profile of oral squamous cell carcinomas. MATERIALS AND METHODS: Gene expression profile was investigated in oral squamous cell carcinomas in 5 patients using the Atlas Glass Human 3.8 I Microarray (which detects cDNA obtained from cellular total RNA) (Clontech Laboratories, Palo Alto, CA). Data were normalized by the LOWESS method. Statistical significances of deviations from a 1:1 ratio were evaluated by t tests, with P<.05. RESULTS: Of the 3,757 genes analyzed, 322 (8.6%) were significantly overexpressed in tumoral tissue with respect to normal tissue, while 104 (2.8%) were significantly underexpressed. The affected genes fell into a wide range of functional categories. CONCLUSION: We consider that cDNA microarrays are of clear value for investigating the biology of these tumors, and that this technology may help in the molecular classification of oral squamous cell carcinomas and in the identification of targets for gene therapy.

Aged↗

PubMed2005

Differential gene expression profiling in whole blood during acute systemic inflammation in lipopolysaccharide-treated rats.

Microarrays have been used to evaluate the expression of thousands of genes in various tissues. However, few studies have investigated the change in gene expression profiles in one of the most easily accessible tissues, whole blood. We utilized an acute inflammation model to investigate the possibility of using a cDNA microarray to measure the gene expression profile in the cells of whole blood. Blood was collected from male Sprague-Dawley rats at 2 and 6 h after treatment with 5 mg/kg (ip) LPS. Hematology showed marked neutrophilia accompanied by lymphopenia at both time points. TNF-alpha and IL-6 levels were markedly elevated at 2 h, indicating acute inflammation, but by 6 h the levels had declined. Total RNA was isolated from whole blood and hybridized to the National Institute of Environmental Health Sciences Rat Chip v.3.0. LPS treatment caused 226 and 180 genes to be differentially expressed at 2 and 6 h, respectively. Many of the differentially expressed genes are involved in inflammation and the acute phase response, but differential expression was also noted in genes involved in the cytoskeleton, cell adhesion, oxidative respiration, and transcription. Real-time RT-PCR confirmed the differential regulation of a representative subset of genes. Principal component analysis of gene expression discriminated between the acute inflammatory response apparent at 2 h and the observed recovery underway at 6 h. These studies indicate that, in whole blood, changes in gene expression profiles can be detected that are reflective of inflammation, despite the adaptive shifts in leukocyte populations that accompany such inflammatory processes.

Animals↗

PubMed2005

Gene expression profiling in pediatric rheumatic disease: what have we learned? What can we learn?

PURPOSE OF THIS REVIEW: Gene expression profiling is emerging as a promising methodology in pediatric rheumatology research. There is considerable interest in using this technology as the basis for diagnostic assays. This review will summarize the new knowledge. RECENT FINDINGS: Most gene expression studies of children have been exploratory in nature. However, preliminary gene expression studies in juvenile dermatomyositis, systemic lupus erythematosus, and chronic forms of arthritis demonstrate both the promise and limits of this technology. It seems likely that gene expression profiling will significantly enhance our understanding of the immunopathology of childhood-onset rheumatic diseases; however, considerable impediments must be overcome before these assays move into the clinical arena. SUMMARY: Gene expression profiling carries considerable potential to provide novel insights into the rheumatic diseases of childhood. Future developments will determine whether these technologies provide new clinical diagnostic or prognostic tools.

Child↗

PubMed2006

An interactive tool for visualization of relationships between gene expression profiles.

BACKGROUND: Application of phenetic methods to gene expression analysis proved to be a successful approach. Visualizing the results in a 3-dimentional space may further enhance these techniques. RESULTS: We designed and built TreeBuilder3D, an interactive viewer for visualizing the hierarchical relationships between expression profiles such as SAGE libraries or microarrays. The program allows loading expression data as plain text files and visualizing the relative differences of the analyzed datasets in 3-dimensional space using various distance metrics. CONCLUSION: TreeBuilder3D provides a simple interface and has a small size. Written in Java, TreeBuilder3D is a platform-independent, open source application, which may be useful in analysis of large-scale gene expression data.

Algorithms↗

PubMed2005

Gene expression profiling of colorectal adenomas and early invasive carcinomas by cDNA array analysis.

It is generally accepted that most colorectal carcinomas arise in pre-existing adenomas. Morphologically, colorectal adenomas can be divided into two groups, protruded type and flat type. The aim of this study was to clarify relevant alterations of gene expression associated with the early stage of colorectal carcinogenesis. Using cDNA array, we analysed the expression profiles of 550 cancer-related genes in 36 colorectal adenomas (18 flat-type and 18 protruded-type adenomas) and 14 early invasive carcinomas. Among the 550 genes, we chose 32 genes the average expression levels of which were at least three-fold up- or downregulated in tumour tissues compared with levels in matched normal tissues. A total of 13 and 19 genes were identified as up- and downregulated genes in tumour tissues, respectively. Among the upregulated genes, the average expression levels of E1AF, bone morphogenic protein (BMP)-4, insulin-like growth factor (IGF)-2, inducible nitric oxide synthase (iNOS), tissue inhibitors of metalloproteinase (TIMP)-1, Smad4, and nm23 in tumour tissues were over five times higher than those in matched normal tissues. Colorectal adenomas and early invasive carcinomas were divided into two major clusters by clustering analysis. Moreover, flat- and protruded-type adenomas were divided into two major clusters by clustering analysis. The expression profiles obtained by the cDNA array clearly indicate that colorectal adenomas and early invasive carcinomas have specific expression profiles. Likewise, the gene expression profiles of flat- and protruded-type adenomas are different. These results indicate that molecular classification of early colorectal tumours by a cDNA array is feasible.

Adenoma↗

PubMed2001

Analysis of gene expression profiles associated with cisplatin resistance in human ovarian cancer cell lines and tissues using cDNA microarray.

Gene expression profiles were analyzed by using cDNA microarray for a cisplatin-sensitive cell line (KF), and three- and thirty-fold cisplatin-resistant ovarian cancer cell lines (KFr and KFrP200) both showing no p53 mutation within exon 5, 6, 7, 8 and no pglycoprotein overexpression. Expression of GST-pi mRNA increased as the level of resistance to cisplatin became high. Microarray analysis revealed that DNA repair associated genes, i.e., XRCC5, XRCC6, ERCC5, hMLH1 were over-expressed in three-fold cisplatin-resistant cell line, KFr as compared to cisplatin-sensitive parental cell line, KF. Apoptosis inhibitors, i.e., IGFR type I and II were over-expressed, and apoptosis inducer, i.e., caspase 3 and BAK were underexpressed in highly cisplatin-resistant cell line, KFrP200 as compared to KFr. As for clinical cases, cDNA microarray was used to compare gene expression profiles directly between two groups, i.e., the chemotherapy (CAP) sensitive group (n = 2) and the resistant group (n = 2). Six genes such as beta tubulin, high-mobility group (nonhistone chromosomal) protein 1, connective tissue growth factor, insulin-like growth factor binding protein 2, alpha tubulin, and RAS-related gene were overexpressed in CAP therapy resistance group, whereas seven genes such as CD9 antigen, alpha-2-macroglobulin, caveolin 2, interleukin 1 receptor antagonist, Rho GTPase activating protein 1, reticulon 3, cyclin-dependent kinase 10, keratin 7 were underexpressed in CAP therapy resistance group. By increasing clinical case number and gene number of microarray to be used in the analysis of expression profile of gene cluster affecting anticancer drug resistance and sensitivity of the ovarian cancer, it would be possible to apply microarray analysis to personalization of chemotherapy such as selection of effective chemotherapy protocol and prediction of therapeutic effect in the near future.

Cisplatin↗