Comparative gene expression profiling by oligonucleotide fingerprinting.

The use of hybridisation of synthetic oligonucleotides to cDNAs under high stringency to characterise gene sequences has been demonstrated by a number of groups. We have used two cDNA libraries of 9 and 12 day mouse embryos (24 133 and 34 783 clones respectively) in a pilot study to characterise expressed genes by hybridisation with 110 hybridisation probes. We have identified 33 369 clusters of cDNA clones, that ranged in representation from 1 to 487 copies (0.7%). 737 were assigned to known rodent genes, and a further 13 845 showed significant homologies. A total of 404 clusters were identified as significantly differentially represented (P < 0.01) between the two cDNA libraries. This study demonstrates the utility of the fingerprinting approach for the generation of comparative gene expression profiles through the analysis of cDNAs derived from different biological materials.     

Peripheral blood gene expression profiling for cardiovascular disease assessment

Whole blood gene expression profiling has the potential to be informative about dynamic changes in disease states and to provide information on underlying disease mechanisms. Having demonstrated proof of concept in animal models, a number of studies have now tried to tackle the complexity of cardiovascular disease in human hosts to develop better diagnostic and prognostic indicators. These studies show that genomic signatures are capable of classifying patients with cardiovascular diseases into finer categories based on the molecular architecture of a patient's disease and more accurately predict the likelihood of a cardiovascular event than current techniques. To highlight the spectrum of potential applications of whole blood gene expression profiling approach in cardiovascular science, we have chosen to review the findings in a number of complex cardiovascular diseases such as atherosclerosis, hypertension and myocardial infarction as well as thromboembolism, aortic aneurysm, and heart transplant.     

Quality prediction of cell substrate using gene expression profiling

Changes in cell culture conditions influence the metabolism of cells, which consequently affects the quality of the products that they produce, such as viral vectors, recombinant proteins, or vaccines. Currently there is no effective technique available to monitor global quality of cells in cell culture. Here we describe a new method using gene expression profiling by microarray to predict the quality of cell substrates. Human embryonic kidney 293 cells are a commonly used cell substrate in the production of biological products. We demonstrate that the yield of adenoviral vectors was lower in over-confluent 293 cells, compared to 40 or 90% confluent cells. Total RNA derived from these cells of different confluence states was reverse transcribed, labeled, and used to hybridize 10K cDNA arrays to determine biomarkers for confluence states. Phenotype scatter-plot analysis and cluster analysis were used for class discovery. Based on this approach, we identified genes that were either up-regulated or down-modulated in response to different cell confluence states. By multivariate predictive models we identified a set of 37 genes that were either down-regulated or up-regulated compared to 90% confluent cells as a predictor of cell confluence and quality of 293 cell cultures. The predictive accuracy of these models was assessed by the leave-one-out cross-validation method. The expression of selected gene predictors was validated by quantitative PCR analysis. Our results demonstrate that gene expression profiling can assess the quality of cell substrates prior to large-scale production of a biological product.     

Microarray-based, high-throughput gene expression profiling of microRNAs

MicroRNAs (miRNAs) are small regulatory RNAs that serve fundamental biological roles across eukaryotic species. We describe a new method for high-throughput miRNA detection. The technique is termed the RNA-primed, array-based Klenow enzyme (RAKE) assay, because it involves on-slide application of the Klenow fragment of DNA polymerase I to extend unmodified miRNAs hybridized to immobilized DNA probes. We used RAKE to study human cell lines and brain tumors. We show that the RAKE assay is sensitive and specific for miRNAs and is ideally suited for rapid expression profiling of all known miRNAs. RAKE offers unique advantages for specificity over northern blots or other microarray-based expression profiling platforms. Furthermore, we demonstrate that miRNAs can be isolated and profiled from formalin-fixed paraffin-embedded tissue, which opens up new opportunities for analyses of small RNAs from archival human tissue. The RAKE assay is theoretically versatile and may be used for other applications, such as viral gene profiling.     

Comparative gene expression profiling analysis of urothelial carcinoma of the renal pelvis and bladder

Background

Tumor therapy mainly attacks the metabolism to interfere the tumor's anabolism and signaling of proliferative second messengers. However, the metabolic demands of different cancers are very heterogeneous and depend on their origin of tissue, age, gender and other clinical parameters. We investigated tumor specific regulation in the metabolism of breast cancer.

Methods

For this, we mapped gene expression data from microarrays onto the corresponding enzymes and their metabolic reaction network. We used Haar Wavelet transforms on optimally arranged grid representations of metabolic pathways as a pattern recognition method to detect orchestrated regulation of neighboring enzymes in the network. Significant combined expression patterns were used to select metabolic pathways showing shifted regulation of the aggressive tumors.

Results

Besides up-regulation for energy production and nucleotide anabolism, we found an interesting cellular switch in the interplay of biosynthesis of steroids and bile acids. The biosynthesis of steroids was up-regulated for estrogen synthesis which is needed for proliferative signaling in breast cancer. In turn, the decomposition of steroid precursors was blocked by down-regulation of the bile acid pathway.

Conclusion

We applied an intelligent pattern recognition method for analyzing the regulation of metabolism and elucidated substantial regulation of human breast cancer at the interplay of cholesterol biosynthesis and bile acid metabolism pointing to specific breast cancer treatment.     

Analysis of host responses to microbial infection using gene expression profiling

Gene expression profiling offers new opportunities for understanding host-cell responses to microbial pathogens and their products. Current strategies involve either first identifying mRNAs that differ in their expression status under different experimental conditions and later defining the identity of the respective genes (for example, differential display or serial analysis of gene expression), or alternatively assessing changes in the expression of already defined genes (for example, cDNA or oligonucleotide microarrays). Early studies indicate the power of gene expression profiling for providing new insights into groups of genes whose expression is altered during the course of host-microbe interactions, and for the discovery of cellular genes that were not previously recognized to be regulated by infection.     

Molecular classification of scrapie strains in mice using gene expression profiling

Transmissible spongiform encephalopathy strains demonstrate specific prion characteristics, each with specific incubation times, and strain-specific patterns of deposition of the misfolded isoform of prion, PrPSc, in the brains of infected individuals. Different biochemical properties, including glycosylation profiles and the degree of proteinase resistance, have been shown to be strain-specific. However, no relationship between these properties and the phenotypic differences in the subsequent diseases has as yet been determined. Here we explore the utility of gene expression profiles to identify differences in the host response to different strains of prion agent. We identify 114 genes that exhibit significantly different levels of expression in mice infected with three strains of scrapie. These genes represent a pool of genes involved in a strain-specific response to prion disease. We have identified the most discriminatory genes from this list utilizing a wrapper-based feature selection algorithm with external cross-validation.     

Microarray gene expression profiling of angiogenesis inhibitors using the rat aortic ring assay

The rat aortic ring assay has been previously described as a useful ex vivo model for analyzing the biological activity of various inhibitors of angiogenesis. Rat aortic rings are exposed to antiangiogenic agents for a five-day incubation period. Then, the degree of microvessel outgrowth from the rings is analyzed and quantified. In contrast to most in vitro angiogenesis assays, the rat aortic ring model provides a unique microenvironment to evaluate the interaction of various cell types and biological factors for their influence on angiogenesis. Microarray analysis is an accepted method for the evaluation of gene expression profiles and can be used to better understand changes in gene expression that occur when rat aortic rings are exposed to a particular biological agent. Here we describe a method of using microarray technology to evaluate the modulation of gene expression in angiogenesis using the rat aortic ring assay.