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PubMed1997

Profile clusters in the WAIS-R standardization sample.

In this study we applied clustering procedures to a subgroup of 341 participants from the WAIS-R standardization sample. These individuals were selected by virtue of their having full-scale profiles characterized by scatter of greater than 8 scaled scores. Using a hierarchical clustering algorithm, a multistage procedure was used to establish and evaluate a cluster solution. The subject selection and clustering methods were successful in revealing a set of 9 profile types characterized by unique profile shapes. All profiles were associated with FSIQs that were at least in the average range. Seven of the profiles were characterized by specific subtest strengths, only 1 with subtest weaknesses. Examination of the external correlates of profile membership revealed differences among profile groups for age, marital status, education, and occupation. Our findings suggest that variability in and across the 9 profile types in this sample reflects increased contributions of unique abilities in comparison to the influence of the underlying primary and secondary WAIS-R dimensions of cognitive ability.

Adolescent↗
PubMedDate not supplied

[Shigellae isolated in 1997--plasmid profiles and antibiotic resistance].

INTRODUCTION: Shigella spp is one of the most frequently isolated bacteria causing acute diarrhea with us. Genetics of pathogenicity of Shigella spp. includes chromosomal and plasmid genes. Most virulence factors are coded by invasion plasmid antigen genes residing on a 180-230 MDa plasmid. There is a big problem with multiple resistance of Shigella spp. strains, which is mostly plasmid-borne. Genetic analysis of bacterial cells, that is plasmid profile analysis, is important for investigation of sources and ways of spreading of the infection. All isolates originating from the same clone have identical plasmid profiles, i.e. number and size of plasmids. The aim of the investigation was: comparing the type of resistance to antimicrobical agents found in epidemic and nonepidemic. Shigella strains isolated in 1997, analyzing plasmid profiles of these isolates and confirming their epidemic connection. MATERIAL AND METHODS: Susceptibility to antibiotics was examined by a standard disc-diffusion method. Plasmid profiles of 40 strains (20 from the outbreak and 20 from sporadic cases) were tested using a method of alkaline lysis by Birnboim and Doly followed by electrophoresis in agarose gel. RESULTS: Shigella strains were resistant to antimicrobial agents which are most commonly used. Epidemic isolates shared the same resistance type, they were resistant to cephalexin, streptomycin and co-trimoxazole. The dominant type of resistance of nonepidemic strains was to ampicillin, streptomycin and co-trimoxazole. Strains isolated during the outbreak had identical plasmid profiles (2 plasmid bands of 55 and 1.5 MDa). Non-epidemic isolates had different plasmid profiles as well as type of resistance. CONCLUSION: Strains of Shigella spp. isolated during an outbreak had the same type of resistance and the same plasmid profiles, which indicated their origin from the same clone. The plasmid profile analysis is a reliable and precise method for determination of epidemic connection of Shigella isolates.

DNA, Bacterial↗
PubMed1998

[SEM (Scanning Electron Microscopy) study of the deterioration of ProFile .04 and .06].

BACKGROUND: The ProFile are endodontic instruments made by a special nickel-titanium alloy. They have to work on constant rotation at a speed of 350 revolutions per minute. The purpose of the study is to assess, through SEM research, a possible deterioration of different ProFile conicity. METHODS: Sixteen dental elements pulled out for period dental reasons have been used as samples to assess the progressive deterioration of .04 and .06 ProFile conicity. Eight molars and eight premolars with a total of 36 radicular canals were examined. The types of ProFile tested were 8: they were respectively 4 with .04 conicity and 4 with .06 conicity. Before being used, all instruments are previously studied through SEM. The tested ProFile with .04 conicity had a diameter of 15, 25, 30 and 45. Those with .06 conicity had a diameter of 20, 25, 30 and 35. Each tested ProFile was introduced inside a radicular canal and was turned for 180 seconds with a constant rotation of 200 revolutions per minute. After this first step, the alterations produced by the instrument could be observed through SEM. Afterwards, the same ProFile has worked again inside another radicular canal with the same time and the same number of turns, before being observed again through SEM. We have continued using this method up to the break of the instrument. RESULTS: The instruments with .04 conicity and smaller diameter are subject to a faster deterioration, more visible at the point. After a working time of 180 seconds all the instruments have their distinct morphological alterations: after other 180 seconds it is possible to often observer an alteration to the pitch of the instrument. The breaking times are related to the diameter and conicity of ProFile tested. CONCLUSIONS: Endodontic nickel-titanium instruments, even if they represent a progress in the field of canal preparation, undergo some alterations in their shape if they are put under inevitable mechanical stress. The damages can be: break at the top of the instrument and loss of cutting abilities at the turns level.

Bicuspid↗
PubMed2005

Gene-expression profiles for five key glycosylation genes for galactose-fed CHO cells expressing recombinant IL-4/13 cytokine trap.

Recombinant protein glycosylation profiles have been shown to affect the in-vivo half-life, and therefore the efficacy and economics, for many therapeutics. While much research has been conducted correlating the effects of various stimuli on recombinant protein glycosylation characteristics, relatively little work has examined glycosylation-related gene-expression profiles. In this study, the effects of galactose feeding on the gene-expression profiles for five key glycosylation-related genes were determined for Chinese hamster ovary cells producing a recombinant IL-4/13 cytokine trap fusion. The genes investigated were sialidase, a putative alpha2,3-sialyltransferase, CMP-sialic acid transporter, beta1,4-galactosyltransferase, and UDP-galactosyltransferase. Additionally, the sialic acid content (sialylation) of the recombinant protein was examined. The peak sialic acid content of the IL-4/13 cytokine trap fusion protein was observed to be similar for the control and galactose-fed cultures. The gene-expression profiles for four of the glycosylation genes were observed to be sensitive to the glucose concentration and not significantly different for the control and galactose-fed cultures prior to glucose depletion. However, the sialidase gene-expression profiles were different for the control and galactose-fed cultures. The sialidase gene-expression profile increased significantly for the galactose-fed cultures prior to glucose depletion, whereas for the control cultures, the sialidase gene-expression profiles did not increase until the late stationary phase. The intracellular sialidase enzyme activity decreased exponentially with time for the control cultures; however, for the galactose-fed cultures, the intracellular sialidase enzyme activity decreased initially and then remained relatively high compared to the control cultures. These results indicate that the galactose feeding may increase the potential for desialylation, which offsets any improvements in the sialylation rate due to increased substrate levels. Thus, galactose feeding is an unnecessary expense for the production of the IL-4/13 cytokine trap fusion protein in a batch process.

Animals↗
PubMed2004

Gene expression profiling of oral squamous cell carcinoma using laser microdissection and cDNA microarray.

Cancer diagnosis and therapy are performed on the basis of clinical stage and clinicopathological findings; however, sensitivity to therapy and prognosis may not always be the same even when considering similar cancers because it is difficult to recognize adequate biological characteristics of a cancer when determining cancer therapy. To enable personalized medicine for cancer diagnosis and therapy, which may solve this problem, we used laser microdissection and cDNA microarrays to study the gene expression profile of oral squamous cell carcinoma. Moreover, to establish an objective evaluation with this system, we examined which type of gene expression profile corresponded to the biological characteristics of this cancer. We identified several genes that were up- or downregulated in the majority of cases and clarified genes sharing common behavioral profiles between metastasis-positive and metastasis-negative cases. It was suspected that the genes that were commonly up- or downregulated in the majority of cases were important for histogenesis and acquisition of invasion and proliferation capability and that the genes sharing common behavioral profiles between metastasis-positive and metastasis-negative cases played a large role in cancer metastasis. Using the expression profile of these genes, it may be possible to evaluate cellular state and metastatic potential and use them as tumor markers. Alternately, we showed averaged gene expression profiles in cases with or without metastasis; this may reveal a profile that could evaluate metastatic potential, which is an important element in the biological characteristics of cancer. In conclusion, our system using laser microdissection and cDNA microarray may contribute to cancer diagnosis and therapy and improvement in the quality of life of cancer patients.

Adult↗
PubMedDate not supplied

Gene expression profiles characterize early graft response in living donor small bowel transplantation: a case report.

BACKGROUND: The cellular and histological events that occur during the regeneration process in invertebrates have been studied in the field of visceral regeneration. We would like to explore the molecular aspects of the regeneration process in the small intestine. The aim of this study was to characterize the gene expression profiles of the intestinal graft to identify which genes may have a role in regeneration of graft tissue posttransplant. METHODS: In a patient undergoing living related small bowel transplantation (LRSBTx) in our institution, mucosal biopsies were obtained from the recipient intestine and donor graft at the time of transplant and at weeks 1, 2, 3, and 6 posttransplant. Total RNA was isolated from sample biopsies followed by gene expression profiles determined from the replicate samples (n = 3) for each biopsy using the Affymetrix U133 Plus 2.0 Human GeneChip set. RESULTS: Two profiles were obtained from the data. One profile showed rapid increase of 45 genes immediately after transplant by week 1 with significant changes (P < .05) greater than threefold including the chemokine CXC9 and glutathione-related stress factors, GPX2 and GSTA4. The second profile identified 133 genes that were significantly decreased by threefold or greater immediately after transplant week 1, including UCC1, the human homolog of the Ependymin gene. CONCLUSION: We have identified two gene expression profiles representing early graft responses to small bowel transplantation. These profiles will serve to identify and study those genes whose products may play a role in accelerating tissue regeneration following segmental LRSBTx.

Biopsy↗
PubMed2003

Direct comparison of microarray gene expression profiles between non-amplification and a modified cDNA amplification procedure applicable for needle biopsy tissues.

Global gene expression profiling by cDNA microarray analysis has been used to discover the biomarkers for early diagnosis of various cancers, subclassing cancer type, and prediction of patient's treatment outcome. The information provided by gene expression profiling may contribute to the design of molecular mechanism-based strategies for cancer prevention and/or treatment. However, the standard procedure for cDNA microarray analysis requires 5mug of good quality total RNA as starting material for each target preparation reaction. Thus, there is a limit for needle biopsy samples, laser capture microdissected tissues, or flow-sorted cells to successfully utilize the microarray technology. In order to profile the gene expression of needle biopsy tissue, we have modified the standard protocol by carrying out cDNA amplification after cDNA synthesis. We compared percentage present calls, absent calls, reproducibility, and concordance in needle biopsy samples processed by standard microarray protocol (cDNA non-amplification method) and our modified protocol (cDNA amplification method). The results showed that cDNA amplification method provided high reproducibility, representation, and concordance with the standard cDNA non-amplification method. We have successfully analyzed the gene expression profiles of needle biopsy tissues using the modified method without significantly changing the expression profiles. These results suggest that the global gene expression profiles of small biopsy samples can be achieved by our modified method to facilitate the analysis of gene expression profiles for clinical application.

Biopsy, Needle↗
PubMed2003

Gene profiling and promoter reporter assays: novel tools for comparing the biological effects of botanical extracts on human prostate cancer cells and understanding their mechanisms of action.

The use of botanical mixtures is commonplace in patients with prostate cancer, yet the majority of these products have not been rigorously tested in clinical trials. Here we use PC-SPES, a combination of eight herbs that has been shown to be effective in clinical trials in patients with prostate cancer, as a model system to demonstrate 'proof of principle' as to how gene expression profiling coupled with promoter assays can evaluate the effect of herbal cocktails on human prostate cancer. In addition, we demonstrate how such approaches may be used for standardization of herbal extract activity by comparing the gene profile of PC-SPES with that of PC-CARE, a product with a similar herbal composition. Since prior studies have shown that PC-SPES contains estrogenic organic compounds, and such compounds are known to affect prostate cancer, an important issue is whether these are the primary drivers of the gene profile. Our data suggest that gene expression profiles of LNCaP human prostate cancer cells in response to PC-SPES are different from those found when diethylstilbestrol (DES), a synthetic estrogen, is used, suggesting that the estrogenic moieties within PC-SPES do not drive this expression signature. In contrast, the expression profile of PC-CARE was almost identical to that of DES, highlighting that mixtures containing similar herbal compositions do not necessarily result in similar biological activities. Interestingly, these three agents cause similar in vitro morphological changes and growth effects on LNCaP. To validate the expression profiling data, we evaluated the protein expression and promoter activity of prostate-specific antigen (PSA), a gene induced by PC-SPES but repressed by DES. In order to gain a mechanistic understanding of how PC-SPES and DES affect PSA expression differently, LNCaP cells were transiently transfected with wild-type and mutagenized PSA promoter, ARE concatemers and appropriate controls. We provide evidence that androgen response elements (ARE) II and III within the promoter region are responsible for the suppressive effects of DES and stimulatory effects of PC-SPES. In addition, we show that the effects on PSA transcription are ARE specific in the case of DES while PC-SPES affects this promoter nonspecifically. In conclusion, expression profiling coupled with mechanistic target validation yield valuable clues as to the mode of action of complex botanical mixtures and provides a new way to compare objectively mixtures with similar components either for effect or quality assurance prior to their use in clinical trials.

Adenocarcinoma↗
PubMed2003

Local Context Finder (LCF) reveals multidimensional relationships among mRNA expression profiles of Arabidopsis responding to pathogen infection.

A major task in computational analysis of mRNA expression profiles is definition of relationships among profiles on the basis of similarities among them. This is generally achieved by pattern recognition in the distribution of data points representing each profile in a high-dimensional space. Some drawbacks of commonly used pattern recognition algorithms stem from their use of a globally linear space and/or limited degrees of freedom. A pattern recognition method called Local Context Finder (LCF) is described here. LCF uses nonlinear dimensionality reduction for pattern recognition. Then it builds a network of profiles based on the nonlinear dimensionality reduction results. LCF was used to analyze mRNA expression profiles of the plant host Arabidopsis interacting with the bacterial pathogen Pseudomonas syringae. In one case, LCF revealed two dimensions essential to explain the effects of the NahG transgene and the ndr1 mutation on resistant and susceptible responses. In another case, plant mutants deficient in responses to pathogen infection were classified on the basis of LCF analysis of their profiles. The classification by LCF was consistent with the results of biological characterization of the mutants. Thus, LCF is a powerful method for extracting information from expression profile data.

Arabidopsis↗
PubMed2002

A tree kernel to analyse phylogenetic profiles.

MOTIVATION: The phylogenetic profile of a protein is a string that encodes the presence or absence of the protein in every fully sequenced genome. Because proteins that participate in a common structural complex or metabolic pathway are likely to evolve in a correlated fashion, the phylogenetic profiles of such proteins are often 'similar' or at least 'related' to each other. The question we address in this paper is the following: how to measure the 'similarity' between two profiles, in an evolutionarily relevant way, in order to develop efficient function prediction methods? RESULTS: We show how the profiles can be mapped to a high-dimensional vector space which incorporates evolutionarily relevant information, and we provide an algorithm to compute efficiently the inner product in that space, which we call the tree kernel. The tree kernel can be used by any kernel-based analysis method for classification or data mining of phylogenetic profiles. As an application a Support Vector Machine (SVM) trained to predict the functional class of a gene from its phylogenetic profile is shown to perform better with the tree kernel than with a naive kernel that does not include any information about the phylogenetic relationships among species. Moreover a kernel principal component analysis (KPCA) of the phylogenetic profiles illustrates the sensitivity of the tree kernel to evolutionarily relevant variations.

Algorithms↗
PubMed2003

Identification of functional links between genes using phylogenetic profiles.

MOTIVATION: Genes with identical patterns of occurrence across the phyla tend to function together in the same protein complexes or participate in the same biochemical pathway. However, the requirement that the profiles be identical (i) severely restricts the number of functional links that can be established by such phylogenetic profiling; (ii) limits detection to very strong functional links, failing to capture relations between genes that are not in the same pathway, but nevertheless subserve a common function and (iii) misses relations between analogous genes. Here we present and apply a method for relaxing the restriction, based on the probability that a given arbitrary degree of similarity between two profiles would occur by chance, with no biological pressure. Function is then inferred at any desired level of confidence. RESULTS: We derive an expression for the probability distribution of a given number of chance co-occurrences of a pair of non-homologous orthologs across a set of genomes. The method is applied to 2905 clusters of orthologous genes (COGs) from 44 fully sequenced microbial genomes representing all three domains of life. Among the results are the following. (1) Of the 51 000 annotated intrapathway gene pairs, 8935 are linked at a level of significance of 0.01. This is over 30-fold greater than the 271 intrapathway pairs obtained at the same confidence level when identical profiles are used. (2) Of the 540 000 interpathway genes pairs, some 65 000 are linked at the 0.01 level of significance, some 12 standard deviations beyond the number expected by chance at this confidence level. We speculate that many of these links involve nearest-neighbor path, and discuss some examples. (3) The difference in the percentage of linked interpathway and intrapathway genes is highly significant, consistent with the intuitive expectation that genes in the same pathway are generally under greater selective pressure than those that are not. (4) The method appears to recover well metabolic networks. This is illustrated by the TCA cycle which is recovered as a highly connected, weighted edge network of 30 of its 31 COGs. (5) The fraction of pairs having a common pathway is a symmetric function of the Hamming distance between their profiles. This finding, that the functional correlation between profiles with near maximum Hamming distance is as large as between profiles with near zero Hamming distance, and as statistically significant, is plausibly explained if the former group represents analogous genes.

Algorithms↗
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↗
PubMed2005

Gene expression profiles associated with response to chemotherapy in epithelial ovarian cancers.

PURPOSE: The goal of this study was to determine whether distinct gene expression profiles are associated with intrinsic and/or acquired chemoresistance in epithelial ovarian carcinoma. EXPERIMENTAL DESIGN: Gene expression profiles were generated from 21 primary chemosensitive tumors and 24 primary chemo-resistant tumors using cDNA-based microarrays. Gene expression profiles of both groups of primary tumors were then compared with those of 15 ovarian carcinomas obtained following platinum-based chemotherapy ("post-chemotherapy" tumors). A theme discovery tool was used to identify functional categories of genes involved in drug resistance. RESULTS: Comparison of primary chemosensitive and chemo-resistant tumors revealed differential expression of 85 genes (P < 0.001). Comparison of gene expression profiles of primary chemosensitive tumors and post-chemotherapy tumors revealed more robust differences with 760 genes differentiating the two groups (P < 0.001). In contrast, only 230 genes were differentially expressed between primary chemo-resistant and post-chemotherapy groups (P < 0.001). Common to both gene lists were 178 genes representing transcripts differentially expressed between post-chemotherapy tumors and all primary tumors irrespective of intrinsic chemosensitivity. The gene expression profile of post-chemotherapy tumors compared with that of primary tumors revealed statistically significant overrepresentation of genes encoding extracellular matrix-related proteins. CONCLUSIONS: These data show that gene expression profiling can discriminate primary chemo-resistant from primary chemosensitive ovarian cancers. Gene expression profiles were also identified that correlate with states of intrinsic and acquired chemoresistance and that represent targets for future investigation and potential therapeutic interventions.

Adult↗
PubMed2006

Ensemble attribute profile clustering: discovering and characterizing groups of genes with similar patterns of biological features.

BACKGROUND: Ensemble attribute profile clustering is a novel, text-based strategy for analyzing a user-defined list of genes and/or proteins. The strategy exploits annotation data present in gene-centered corpora and utilizes ideas from statistical information retrieval to discover and characterize properties shared by subsets of the list. The practical utility of this method is demonstrated by employing it in a retrospective study of two non-overlapping sets of genes defined by a published investigation as markers for normal human breast luminal epithelial cells and myoepithelial cells. RESULTS: Each genetic locus was characterized using a finite set of biological properties and represented as a vector of features indicating attributes associated with the locus (a gene attribute profile). In this study, the vector space models for a pre-defined list of genes were constructed from the Gene Ontology (GO) terms and the Conserved Domain Database (CDD) protein domain terms assigned to the loci by the gene-centered corpus LocusLink. This data set of GO- and CDD-based gene attribute profiles, vectors of binary random variables, was used to estimate multiple finite mixture models and each ensuing model utilized to partition the profiles into clusters. The resultant partitionings were combined using a unanimous voting scheme to produce consensus clusters, sets of profiles that co-occurred consistently in the same cluster. Attributes that were important in defining the genes assigned to a consensus cluster were identified. The clusters and their attributes were inspected to ascertain the GO and CDD terms most associated with subsets of genes and in conjunction with external knowledge such as chromosomal location, used to gain functional insights into human breast biology. The 52 luminal epithelial cell markers and 89 myoepithelial cell markers are disjoint sets of genes. Ensemble attribute profile clustering-based analysis indicated that both lists contained groups of genes with the functional properties of membrane receptor biology/signal transduction and nucleic acid binding/transcription. A subset of the luminal markers was associated with metabolic and oxidoreductase activities, whereas a subset of myoepithelial markers was associated with protein hydrolase activity. CONCLUSION: Given a set of genes and/or proteins associated with a phenomenon, process or system of interest, ensemble attribute profile clustering provides a simple method for collating and sythesizing the annotation data pertaining to them that are present in text-based, gene-centered corpora. The results provide information about properties common and unique to subsets of the list and hence insights into the biology of the problem under investigation.

Algorithms↗
PubMed2006

Exploiting the full power of temporal gene expression profiling through a new statistical test: application to the analysis of muscular dystrophy data.

BACKGROUND: The identification of biologically interesting genes in a temporal expression profiling dataset is challenging and complicated by high levels of experimental noise. Most statistical methods used in the literature do not fully exploit the temporal ordering in the dataset and are not suited to the case where temporal profiles are measured for a number of different biological conditions. We present a statistical test that makes explicit use of the temporal order in the data by fitting polynomial functions to the temporal profile of each gene and for each biological condition. A Hotelling T2-statistic is derived to detect the genes for which the parameters of these polynomials are significantly different from each other. RESULTS: We validate the temporal Hotelling T2-test on muscular gene expression data from four mouse strains which were profiled at different ages: dystrophin-, beta-sarcoglycan and gamma-sarcoglycan deficient mice, and wild-type mice. The first three are animal models for different muscular dystrophies. Extensive biological validation shows that the method is capable of finding genes with temporal profiles significantly different across the four strains, as well as identifying potential biomarkers for each form of the disease. The added value of the temporal test compared to an identical test which does not make use of temporal ordering is demonstrated via a simulation study, and through confirmation of the expression profiles from selected genes by quantitative PCR experiments. The proposed method maximises the detection of the biologically interesting genes, whilst minimising false detections. CONCLUSION: The temporal Hotelling T2-test is capable of finding relatively small and robust sets of genes that display different temporal profiles between the conditions of interest. The test is simple, it can be used on gene expression data generated from any experimental design and for any number of conditions, and it allows fast interpretation of the temporal behaviour of genes. The R code is available from V.V. The microarray data have been submitted to GEO under series GSE1574 and GSE3523.

Animals↗
PubMed2005

Changes in the transcriptional profile of transporters in the intestine along the anterior-posterior and crypt-villus axes.

BACKGROUND: The purpose of this work was to characterize the expression of drug and nutrient carriers along the anterior-posterior and crypt-villus axes of the intestinal epithelium and to study the validity of utilizing whole gut tissue rather than purified epithelial cells to examine regional variations in gene expression. RESULTS: We have characterized the mRNA expression profiles of 76 % of all currently known transporters along the anterior-posterior axis of the gut. This is the first study to describe the expression profiles of the majority of all known transporters in the intestine. The expression profiles of transporters, as defined according to the Gene Ontology consortium, were measured in whole tissue of the murine duodenum, jejunum, ileum and colon using high-density microarrays. For nine transporters (Abca1, Abcc1, Abcc3, Abcg8, Slc10a2, Slc28a2, Slc2a1, Slc34a2 and Slc5a8), the mRNA profiles were further measured by RT-PCR in laser micro-dissected crypt and villus epithelial cells corresponding to the aforementioned intestinal regions. With respect to differentially regulated transporters, the colon had a distinct expression profile from small intestinal segments. The majority (59 % for p cutoff < or = 0.05) of transporter mRNA levels were constant across the intestinal sections studied. For the transporter subclass "carrier activity", which contains the majority of known carriers for biologically active compounds, a significant change (p < or = 0.05) along the anterior-posterior axis was observed. CONCLUSION: All nine transporters examined in laser-dissected material demonstrated good replication of the region-specific profiles revealed by microarray. Furthermore, we suggest that the distribution characteristics of Slc5a8 along the intestinal tract render it a suitable candidate carrier for monocarboxylate drugs in the posterior portion of the intestine. Our findings also predict that there is a significant difference in the absorption of carrier-mediated compounds in the different intestinal segments. The most pronounced differences can be expected between the adjoining segments ileum and colon, but the differences between the other adjoining segments are not negligible. Finally, for the examined genes, profiles measured in whole intestinal tissue extracts are representative of epithelial cell-only gene expression.

Analysis of Variance↗
PubMed2005

Exploring hepatic hormone actions using a compilation of gene expression profiles.

BACKGROUND: Microarray analysis is attractive within the field of endocrine research because regulation of gene expression is a key mechanism whereby hormones exert their actions. Knowledge discovery and testing of hypothesis based on information-rich expression profiles promise to accelerate discovery of physiologically relevant hormonal mechanisms of action. However, most studies so-far concentrate on the analysis of actions of single hormones and few examples exist that attempt to use compilation of different hormone-regulated expression profiles to gain insight into how hormone act to regulate tissue physiology. This report illustrates how a meta-analysis of multiple transcript profiles obtained from a single tissue, the liver, can be used to evaluate relevant hypothesis and discover novel mechanisms of hormonal action. We have evaluated the differential effects of Growth Hormone (GH) and estrogen in the regulation of hepatic gender differentiated gene expression as well as the involvement of sterol regulatory element-binding proteins (SREBPs) in the hepatic actions of GH and thyroid hormone. RESULTS: Little similarity exists between liver transcript profiles regulated by 17-alpha-ethinylestradiol and those induced by the continuos infusion of bGH. On the other hand, strong correlations were found between both profiles and the female enriched transcript profile. Therefore, estrogens have feminizing effects in male rat liver which are different from those induced by GH. The similarity between bGH and T3 were limited to a small group of genes, most of which are involved in lipogenesis. An in silico promoter analysis of genes rapidly regulated by thyroid hormone predicted the activation of SREBPs by short-term treatment in vivo. It was further demonstrated that proteolytic processing of SREBP1 in the endoplasmic reticulum might contribute to the rapid actions of T3 on these genes. CONCLUSION: This report illustrates how a meta-analysis of multiple transcript profiles can be used to link knowledge concerning endocrine physiology to hormonally induced changes in gene expression. We conclude that both GH and estrogen are important determinants of gender-related differences in hepatic gene expression. Rapid hepatic thyroid hormone effects affect genes involved in lipogenesis possibly through the induction of SREBP1 proteolytic processing.

Animals↗
PubMed2004

Combining gene expression profiles and clinical parameters for risk stratification in medulloblastomas.

PURPOSE: Stratification of risk in patients with medulloblastoma remains a challenge. As clinical parameters have been proven insufficient for accurately defining disease risk, molecular markers have become the focus of interest. Outcome predictions on the basis of microarray gene expression profiles have been the most accurate to date. We ask in a multivariate model whether clinical parameters enhance survival predictions of gene expression profiles. PATIENTS AND METHODS: In a cohort of 55 young patients (whose medulloblastoma samples have been analyzed previously for gene expression profile), associations between clinical and gene expression variables and survival were assessed using Cox proportional hazards models. Available clinical variables included age, stage (ie, the presence of disseminated disease at diagnosis), sex, histologic subtype, treatment, and status. RESULTS: Univariate analysis demonstrated expression profiles to be the only significant clinical prognostic factor (P=.03). In multivariate analysis, gene expression profiles predicted outcome independent of other criteria. Clinical criteria did not significantly contribute additional information for outcome predictions, although an exploratory analysis noted a trend for decreased survival of patients with metastases at diagnosis but favorable gene expression profile. CONCLUSION: Gene expression profiling predicts medulloblastoma outcome independent of clinical variables. These results need to be validated in a larger prospective study.

Adolescent↗