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PubMed2005

Towards precise classification of cancers based on robust gene functional expression profiles.

BACKGROUND: Development of robust and efficient methods for analyzing and interpreting high dimension gene expression profiles continues to be a focus in computational biology. The accumulated experiment evidence supports the assumption that genes express and perform their functions in modular fashions in cells. Therefore, there is an open space for development of the timely and relevant computational algorithms that use robust functional expression profiles towards precise classification of complex human diseases at the modular level. RESULTS: Inspired by the insight that genes act as a module to carry out a highly integrated cellular function, we thus define a low dimension functional expression profile for data reduction. After annotating each individual gene to functional categories defined in a proper gene function classification system such as Gene Ontology applied in this study, we identify those functional categories enriched with differentially expressed genes. For each functional category or functional module, we compute a summary measure (s) for the raw expression values of the annotated genes to capture the overall activity level of the module. In this way, we can treat the gene expressions within a functional module as an integrative data point to replace the multiple values of individual genes. We compare the classification performance of decision trees based on functional expression profiles with the conventional gene expression profiles using four publicly available datasets, which indicates that precise classification of tumour types and improved interpretation can be achieved with the reduced functional expression profiles. CONCLUSION: This modular approach is demonstrated to be a powerful alternative approach to analyzing high dimension microarray data and is robust to high measurement noise and intrinsic biological variance inherent in microarray data. Furthermore, efficient integration with current biological knowledge has facilitated the interpretation of the underlying molecular mechanisms for complex human diseases at the modular level.

Algorithms↗

PubMed2002

[Investigation of the gene expression profile in spermatocytes].

OBJECTIVE: To investigate the gene expression profile in the mature spermatocytes and the molecular mechanism of the male infertility syndromes. METHODS: Restriction display PCR (RD-PCR), a new method of differential display technique, was used to collect plenty of gene fragments expressed in either normal or abnormal spermatocytes, the gene expression profile of which were demonstrated by these fragments(gene expression sequence tags, ESTs), in the form of cDNA fragments length polymorphism. These ESTs will be used to make DNA microarray as probes to further explore the gene expression profile in spermatocytes and to diagnose the male infertility. RESULTS: Lots of ESTs were expressed in either normal or abnormal spermatocytes and some differentially expressed ESTs have been collected and purified. CONCLUSION: Either for known or unknown genes, RD-PCR is very effective in rapid acquisition of large amount of ESTs with proper and similar length fit for making microarray as the probes.

Gene Expression Profiling↗

PubMed2006

Gene expression profiling and outcome prediction in non-Hodgkin lymphoma.

Gene expression profiling with microarrays has provided new insights into the molecular biology of tumors can that underlie differences in responses to therapy and patient outcomes. In diffuse large B-cell lymphoma, gene expression profiling has revealed at least 2 diseases that are strikingly different in their response to chemotherapy and the inhibition of critical oncogenic pathways. In follicular lymphoma, gene expression profiling showed that the host immune response to tumors is an important determinant of outcome and can strongly predict survival at the time of diagnosis. The application of immunologic therapies that modify the host immune response could have a major effect on survival in patients with follicular lymphoma. Thus, the application of gene expression profiling in non-Hodgkin lymphoma provides important prognostic information at the time of diagnosis and can be translated into therapeutic options that improve patient outcomes.

Disease-Free Survival↗

PubMed2002

Modelling regulatory pathways in E. coli from time series expression profiles.

MOTIVATION: Cells continuously reprogram their gene expression network as they move through the cell cycle or sense changes in their environment. In order to understand the regulation of cells, time series expression profiles provide a more complete picture than single time point expression profiles. Few analysis techniques, however, are well suited to modelling such time series data. RESULTS: We describe an approach that naturally handles time series data with the capabilities of modelling causality, feedback loops, and environmental or hidden variables using a Dynamic Bayesian network. We also present a novel way of combining prior biological knowledge and current observations to improve the quality of analysis and to model interactions between sets of genes rather than individual genes. Our approach is evaluated on time series expression data measured in response to physiological changes that affect tryptophan metabolism in E. coli. Results indicate that this approach is capable of finding correlations between sets of related genes.

Adaptation, Physiological↗

PubMed2005

Database of mRNA gene expression profiles of multiple human organs.

Genome-wide expression profiling of normal tissue may facilitate our understanding of the etiology of diseased organs and augment the development of new targeted therapeutics. Here, we have developed a high-density gene expression database of 18,927 unique genes for 158 normal human samples from 19 different organs of 30 different individuals using DNA microarrays. We report four main findings. First, despite very diverse sample parameters (e.g., age, ethnicity, sex, and postmortem interval), the expression profiles belonging to the same organs cluster together, demonstrating internal stability of the database. Second, the gene expression profiles reflect major organ-specific functions on the molecular level, indicating consistency of our database with known biology. Third, we demonstrate that any small (i.e., n approximately 100), randomly selected subset of genes can approximately reproduce the hierarchical clustering of the full data set, suggesting that the observed differential expression of >90% of the probed genes is of biological origin. Fourth, we demonstrate a potential application of this database to cancer research by identifying 19 tumor-specific genes in neuroblastoma. The selected genes are relatively underexpressed in all of the organs examined and belong to therapeutically relevant pathways, making them potential novel diagnostic markers and targets for therapy. We expect this database will be of utility for developing rationally designed molecularly targeted therapeutics in diseases such as cancer, as well as for exploring the functions of genes.

Cluster Analysis↗

PubMedDate not supplied

Microarray-based expression profiling in prostate tumors.

High throughput gene expression profiling is increasingly becoming a desirable method for identifying genes differentially expressed in disease versus normal tissues. Microarrays and gene chips containing hundreds to thousands of genes of interest, both known and novel, can be used to establish the expression profile of numerous genes in a single experiment. In order to validate the hits emerging out of such an experiment it is necessary to use an appropriate panel of the cDNA repository. We investigated the usefulness of such a method to identify prostate cancer-specific genes. A microarray containing 588 known genes was analyzed using cDNA probes derived from normal and three independent prostate tumors. At least 19/588 genes were found to be differentially expressed in the tumors in comparison to the normal tissue. Among the nine test genes chosen, one gene, Glutathione-S-transferase theta 1 (GSTT1), showed a correlation with the microarray results when analyzed by RT-PCR. Using a comprehensive panel of normal and tumor tissues and cancer-derived cell lines, we have rapidly validated the expression relevance of GSTT1 in solid tumors. The microarray was also useful in the preliminary identification of androgen-regulated genes in the prostate tumor models. These results indicate that microarray in combination with a relevant cDNA repository can facilitate rapid identification of potential targets for therapy and diagnosis of prostate and other cancers.

Female↗

PubMed2005

Gene expression profiling in human cardiovascular disease.

Gene expression profiling studies in human diseases have allowed better understanding of pathophysiological processes. In addition, they may lead to the development of new clinical tools to improve diagnosis and prognosis of patients. Most of these studies have been successfully performed for human cancers. Inspired by these results, researchers in the cardiovascular field have also started using large-scale transcriptional analysis to better understand and classify human cardiovascular disease. Here we provide an overview of the literature revealing new cardiac disease markers and encouraging results for further development of the expression profiling strategy for future clinical applications in cardiology.

Calcium Signaling↗

PubMed2004

Identification of a gene expression profile that differentiates between ischemic and nonischemic cardiomyopathy.

BACKGROUND: Gene expression profiling refines diagnostic and prognostic assessment in oncology but has not yet been applied to myocardial diseases. We hypothesized that gene expression differentiates ischemic and nonischemic cardiomyopathy, demonstrating that gene expression profiling by clinical parameters is feasible in cardiology. METHODS AND RESULTS: Affymetrix U133A microarrays of 48 myocardial samples from Johns Hopkins Hospital (JHH) and the University of Minnesota (UM) obtained (1) at transplantation or left ventricular assist device (LVAD) placement (end-stage; n=25), (2) after LVAD support (post-LVAD; n=16), and (3) from newly diagnosed patients (biopsy; n=7) were analyzed with prediction analysis of microarrays. A training set was used to develop the profile and test sets to validate the accuracy of the profile. An etiology prediction profile developed in end-stage JHH samples was tested in independent samples from both JHH and UM with 100% sensitivity and 100% specificity in end-stage samples and 33% sensitivity and 100% specificity in both post-LVAD and biopsy samples. The overall sensitivity was 89% (95% CI 75% to 100%), and specificity was 89% (95% CI 60% to 100%) over 210 random partitions of end-stage samples into training and test sets. Age, gender, and hemodynamic differences did not affect the profile's accuracy in stratified analyses. Select gene expression was confirmed with quantitative polymerase chain reaction. CONCLUSIONS: Gene expression profiling accurately predicts cardiomyopathy etiology, is generalizable to samples from separate institutions, is specific to disease stage, and is unaffected by differences in clinical characteristics. This strongly supports ongoing efforts to incorporate expression profiling-based biomarkers in determining prognosis and response to therapy in heart failure.

Adult↗

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↗

PubMedDate not supplied

Gene expression profiling and breast cancer care: what are the potential benefits and policy implications?

PURPOSE: Gene expression profiling has been proposed as an alternative to clinical guidelines to identify high-risk patients for adjuvant chemotherapy. However, the outcomes associated with gene expression profiling are not clear, and guidelines for the appropriate use of genomic technologies have not been established. METHODS: We developed a decision analytic model to evaluate the incremental cost and quality-adjusted life years of gene expression profiling versus NIH clinical guidelines in a hypothetical cohort of premenopausal early stage breast cancer patients 44 years of age. We conducted empirical analyses and identified literature-based data to inform the model, and performed probabilistic sensitivity analyses to evaluate uncertainty in the results. We interpreted the implications of our findings for treatment guidelines and policies. RESULTS: Use of gene expression profiling resulted in an absolute 5% decrease in the proportion of cases of distant recurrence prevented, 0.21 fewer quality-adjusted life years, and a cost savings of USD 2882. The chosen test cutoff value to identify a tumor as poor prognosis and the cost of adjuvant chemotherapy were the most influential parameters in the analysis, but our findings did not change substantially in sensitivity analyses. Regardless of the test cutoff used to identify a poor prognosis tumor, the gene expression profiling assay studied in our analysis, at its current level of performance, did not attain the threshold sensitivity (95%) necessary to produce equal or greater quality-adjusted life years than NIH guidelines. CONCLUSION: Although the use of gene expression profiling in breast cancer care holds great promise, our analysis suggests additional refinement and validation are needed before use in clinical practice.

Adult↗

PubMed1996

Haemopoietic growth factor tyrosine kinase receptor expression profiles in normal haemopoiesis.

Expression profiles were generated for the haemopoietic tyrosine kinase receptors (HGF-TKRs or class III TKRs) by PCR on cDNA samples (RT-PCR) using a degenerate primer set. Each profile consisted of primary and secondary, i.e. enriched for less-expressed sequences, fingerprints. This method was applied on FACS-purified haemopoietic CD34+ cells, both from bone marrow (BM) and umbilical cord blood (UCB), and on mature cells from peripheral blood. CD34+ BM cells showed expression of c-fms. flt3, whereas CD34+ UCB cells expressed c-fms and, to a lesser extent, c-kit and flt3. In mature blood cells, only c-fms was observed in monocytes and a weaker flt3 expression in monocytes and T lymphocytes, whereas no known class III TKRs were detected in B lymphocytes and polymorphonuclear cells (PMNs). In all fractions a novel band could be observed, which appeared to be RET. Expression of RET was confirmed by RT-PCR and showed the highest levels in monocytes, followed by PMNs and CD34+ cells. B lymphocytes revealed low levels of expression. RET is known to be essential in neural development. Our results suggest a possible role for this receptor in haemopoiesis.

Antigens, CD34↗

PubMed2006

Identification of differentially expressed genes in human bladder cancer through genome-wide gene expression profiling.

Large-scale gene expression profiling is an effective strategy for understanding the progression of bladder cancer (BC). The aim of this study was to identify genes that are expressed differently in the course of BC progression and to establish new biomarkers for BC. Specimens from 21 patients with pathologically confirmed superficial (n = 10) or invasive (n = 11) BC and 4 normal bladder samples were studied; samples from 14 of the 21 BC samples were subjected to microarray analysis. The validity of the microarray results was verified by real-time RT-PCR. Of the 136 up-regulated genes we detected, 21 were present in all 14 BCs examined (100%), 44 in 13 (92.9%), and the other 71 in 12 BCs (85.7%). Of 69 down-regulated genes, 25 were found in all 14 BCs (100%), 22 in 13 (92.9%), and the other 22 in 12 BCs (85.7%). Functional annotation revealed that of the up-regulated genes, 36% were involved in metabolism and 14% in transcription and processing; 25% of the down-regulated genes were linked to cell adhesion/surface and 21% to cytoskeleton/cell membrane. Real-time RT-PCR confirmed the microarray results obtained for the 6 most highly up- and the 2 most highly down-regulated genes. Among the 6 most highly up-regulated genes, CKS2 was the only gene with a significantly greater level of up-regulation in invasive than in superficial BC (p = 0.04). To confirm this result, we subjected all 21 BC samples to real-time PCR assay for CKS2. We found a considerable difference between superficial and invasive BC (p = 0.001). Interestingly, there was a considerable difference between the normal bladder and invasive BC (p = 0.001) and less difference between the normal bladder and superficial BC (p = 0.005). We identified several genes as promising candidates for diagnostic biomarkers of human BC and the CKS2 gene not only as a potential biomarker for diagnosing, but also for staging human BC. This is the first report demonstrating that CKS2 expression is strongly correlated with the progression of human BC.

Aged↗

PubMed2005

Gene expression profiling of mantle cell lymphoma cells reveals aberrant expression of genes from the PI3K-AKT, WNT and TGFbeta signalling pathways.

Microarray studies have revealed the differential expression of several genes in mantle cell lymphoma (MCL), but it is unknown which of these differences are dependent on the transformed MCL cell itself or on the tumour microenvironment. To investigate which genes and signalling pathways are aberrantly expressed in MCL cells we used oligonucleotide microarrays to perform gene expression profiling of both purified leukaemic MCL cells and their normal counterparts, the naive B cells. A total of 106 genes were differentially expressed at least threefold in MCL cells compared with naive B cells; 63 upregulated and 43 downregulated. To validate the microarray results in a larger set of samples, we selected 10 differentially expressed genes and quantified their expression by real-time polymerase chain reaction in peripheral blood of MCL patients (n=21), purified MCL cells (n=6) and naive B cells (n=4), obtaining fully concordant results. A computer-assisted approach was used to procure specific molecular signalling pathways that were aberrantly expressed in MCL cells. Several genes related to apoptosis and to the PI3K/AKT, WNT and tumour growth factor beta signalling pathways were altered in MCL cells when compared with naive B cells. These pathways may play a significant role in the pathogenesis of MCL and deserve further investigation as candidates for new therapeutic targets.

Adult↗

PubMed2005

Expression profiling of purified male germ cells: stage-specific expression patterns related to meiosis and postmeiotic development.

Gene expression profiling was performed using the National Institute on Aging 15,000-cDNA microarray to reveal the differential expression pattern of 160 genes between meiotic pachytene spermatocytes and postmeiotic round spermatids of the mouse. Our results indicate that more genes are expressed in spermatids than in spermatocytes. Genes participating in cell cycle regulation and chromatin structure and dynamics are preferentially expressed in spermatocytes, while genes for protein turnover, signal transduction, energy metabolism, and intracellular transport are prevalent in spermatids. This suggests that a switch of functional requirement occurs when meiotic germ cells differentiate into haploid spermatids. Concordant expression patterns were obtained when quantitative real-time polymerase chain reaction was performed to verify the microarray data. Interestingly, the majority of the differentially expressed genes were underrepresented in mitotic type A spermatogonia, and they were preferentially expressed in the testis. Our results suggest that an even higher proportion of the mouse genome is devoted to male gamete development from meiosis than was previously estimated. We also provide evidence that underscores the advantage of using purified germ cells over whole testes in profiling spermatogenic gene expression to identify transcripts that demonstrate stage-specific expression patterns.

Animals↗

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↗

PubMed2005

Discovery of glpC, an organic solvent tolerance-related gene in Escherichia coli, using gene expression profiles from DNA microarrays.

Gene expression profiles were collected from Escherichia coli strains (OST3410, TK33, and TK31) before and after exposure to organic solvents, and the six genes that showed higher gene expression were selected. Among these genes, glpC encoding the anaerobic glycerol-3-phosphate dehydrogenase subunit C remarkably increased the organic solvent tolerance.

Cyclohexanes↗

PubMed2005

Carotid arteriotomy induces different temporal gene expression profiles in normotensive and hypertensive rat strains.

Analysis of gene expression profiles in patients or in animal models affected by cardiovascular diseases may provide insight into therapeutic strategies. In this study, 3 rat strains, Wistar Kyoto (WKY), spontaneously hypertensive rats (SHR) and the Milan hypertensive rat strain (MHS), have been investigated to assess the influence of genetic background and/or of hypertension on gene expression in arteriotomy-injured carotid arteries (CAs). Expression profiles of genes, c-myc, AT1, AT2, ETA, ETB, Bcl-2, Bax and Bcl-X, were determined by reverse transcription-polymerase chain reaction (RT-PCR) in the acute phase, from 1 to 48 h, following CA arteriotomy. WKY, SHR and MHS show significant differences in gene expression profiles after CA arteriotomy. c-Myc mRNA is activated earlier and/or to a greater extent in hypertensive strains than in WKY (p<0.05). AT1 mRNA increases in WKY after injury, while it decreases in both SHR and MHS (p<0.05). AT2 shows the opposite behaviour, decreasing in WKY and increasing in hypertensive strains (p<0.05). ETA mRNA decreases in all strains although with different timing and levels, associated with a replacement by ETB mRNA (p<0.05). Bcl-2/Bax ratio gradually decreases in WKY, while it decreases only transiently in SHR and MHS 4 h after injury (p<0.05). Overall data indicate that therapeutic strategies for stenosis prevention should carefully consider the gene expression profile after injury, the genetic background, the kind of vascular trauma and the diseases affecting the animal model or the patient.

Animals↗

PubMed2000

Expression profile and chromosomal location of cDNA clones, identified from an enriched adult retina library.

PURPOSE: To delineate the profile of genes expressed in the adult human retina and assign chromosomal location of cDNA clones. METHODS: The end-sequence of random clones from an enriched human retinal cDNA library was analyzed by NCBI database search. Expression profile was established by northern blot analysis, database search, or both. Selected cDNA clones were localized to human chromosomes by somatic cell hybrid analysis, in situ hybridization to metaphase chromosomes, or both. Chromosomal location was also obtained by searching the databases. RESULT: One hundred and thirty-seven clones were isolated from the subtracted retinal library. Fifty-one clones were identical with 35 known human genes in GenBank, and 24 clones corresponded to 23 uncharacterized human expressed sequenced tags (ESTs), novel genes, or both. The remaining 59 clones were not pursued further because they contained bacterial sequences or repetitive elements. Several clones indicated a restricted pattern of expression with high levels of transcripts in the retina. Chromosomal location of novel retinal ESTs is also reported. CONCLUSIONS: This study provides a profile of genes expressed in the adult human retina. One round of subtraction eliminated most constitutively expressed genes and permitted partial normalization of the retinal library. Twenty-three novel genes were identified. The combined information obtained from expression analysis and chromosomal localization of retinal cDNAs should be valuable in identifying candidate genes for diseases involving retinal dysfunction.

Blotting, Northern↗