Genes related to emphysema are enriched for ubiquitination pathways.

BACKGROUND: Increased small airway resistance and decreased lung elasticity contribute to the airflow limitation in chronic obstructive pulmonary disease (COPD). The lesion that corresponds to loss of lung elasticity is emphysema; the small airway obstruction is due to inflammatory narrowing and obliteration. Despite their convergence in altered physiology, different mechanisms contribute to these processes. The relationships between gene expression and these specific phenotypes may be more revealing than comparison with lung function. METHODS: We measured the ratio of alveolar surface area to lung volume (SA/V) in lung tissue from 43 smokers. Two samples from 21 subjects, in which SA/V differed by >49 cm2/mL were profiled to select genes whose expression correlated with SA/V. Significant genes were tested for replication in the 22 remaining subjects. RESULTS: The level of expression of 181 transcripts was related to SA/V ( p < 0.05). When these genes were tested in the 22 remaining subjects as a replication, thirty of the 181 genes remained significantly associated with SA/V (P < 0.05) and the direction of association was the same in 164/181. Pathway and network analysis revealed enrichment of genes involved in protein ubiquitination, and western blotting showed altered expression of genes involved in protein ubiquitination in obstructed individuals. CONCLUSION: This study implicates modified protein ubiquitination and degradation as a potentially important pathway in the pathogenesis of emphysema.

Gene expression profiling in patients with chronic obstructive pulmonary disease and lung cancer.

RATIONALE: Chronic obstructive lung disease (COPD) is a common and disabling lung disease for which there are few therapeutic options. OBJECTIVES: We reasoned that gene expression profiling of COPD lungs could reveal previously unidentified disease pathways. METHODS: Forty-eight human lung samples were obtained from tissue resected from five nonsmokers, 21 GOLD (Global Initiative for Chronic Obstructive Lung Disease) stage 0, 9 GOLD stage 1, 10 GOLD stage 2, and 3 GOLD stage 3 patients. mRNA from the specimens was profiled using Agilent's Functional ID v2.0 array (Agilent, Santa Clara, CA) containing 23,720 sequences. MEASUREMENTS AND MAIN RESULTS: The gene expression pattern was influenced by the percentage of the sample made up of parenchyma. Gene expression was related to forced expiratory flow between 25 and 75% of forced expiratory volume (FEF(25-75%) % predicted) revealing a signature gene set of 203 transcripts. Genes involved in extracellular matrix synthesis/degradation and apoptosis were among the up-regulated genes, whereas genes that participate in antiinflammatory responses were down-regulated. Immunohistochemistry confirmed expression of urokinase plasminogen activator (PLAU), urokinase plasminogen activator receptor (PLAUR), and thrombospondin (THBS1) by alveolar macrophages and airway epithelial cells. Genes in this pathway have been shown to be involved in the activation of transforming growth factor (TGF)-beta1 and matrix metalloproteinases and are subject to inhibition by SERPINE2. Interestingly, both TGF-beta1 and SERPINE2 have been identified as candidate genes in COPD genetic linkage and association studies. CONCLUSIONS: The results provide evidence that genes involved in tissue remodeling and repair are differentially regulated in the lungs of obstructed smokers and suggest that they are potential therapeutic targets. Data deposited in GEO at http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE8500.

Use of hybridization kinetics for differentiating specific from non-specific binding to oligonucleotide microarrays.

Hybridization kinetics were found to be significantly different for specific and non-specific binding of labeled cRNA to surface-bound oligonucleotides on microarrays. We show direct evidence that in a complex sample specific binding takes longer to reach hybridization equilibrium than the non- specific binding. We find that this property can be used to estimate and to correct for the hybridization contributed by non-specific binding. Useful applications are illustrated including the selection of superior oligonucleotides, and the reduction of false positives in exon identification.

Signatures of environmental exposures using peripheral leukocyte gene expression: tobacco smoke.

Functional biological markers of environmental exposures are important in epidemiological studies of disease risk. Such markers not only provide a measure of the exposure, they also reflect the degree of physiological and biochemical response to the exposure. In an observational study, using DNA microarrays, we show that it is possible to distinguish between 85 individuals exposed and unexposed to tobacco smoke on the basis of mRNA expression in peripheral leukocytes. Furthermore, we show that active exposure to tobacco smoke is associated with a biologically relevant mRNA expression signature. These findings suggest that expression patterns can be used to identify a complex environmental exposure in humans.

Biomarkers of the Hedgehog/Smoothened pathway in healthy volunteers.

The Hedgehog (Hh) pathway is involved in oncogenic transformation and tumor maintenance. The primary objective of this study was to select surrogate tissue to measure messenger ribonucleic acid (mRNA) levels of Hh pathway genes for measurement of pharmacodynamic effect. Expression of Hh pathway specific genes was measured by quantitative real time polymerase chain reaction (qRT-PCR) and global gene expression using Affymetrix U133 microarrays. Correlations were made between the expression of specific genes determined by qRT-PCR and normalized microarray data. Gene ontology analysis using microarray data for a broader set of Hh pathway genes was performed to identify additional Hh pathway-related markers in the surrogate tissue. RNA extracted from blood, hair follicle, and skin obtained from healthy subjects was analyzed by qRT-PCR for 31 genes, whereas 8 samples were analyzed for a 7-gene subset. Twelve sample sets, each with ≤500 ng total RNA derived from hair, skin, and blood, were analyzed using Affymetrix U133 microarrays. Transcripts for several Hh pathway genes were undetectable in blood using qRT-PCR. Skin was the most desirable matrix, followed by hair follicle. Whether processed by robust multiarray average or microarray suite 5 (MAS5), expression patterns of individual samples showed co-clustered signals; both normalization methods were equally effective for unsupervised analysis. The MAS5- normalized probe sets appeared better suited for supervised analysis. This work provides the basis for selection of a surrogate tissue and an expression analysis-based approach to evaluate pathway-related genes as markers of pharmacodynamic effect with novel inhibitors of the Hh pathway.

A gene expression signature that classifies human atherosclerotic plaque by relative inflammation status.

BACKGROUND: Atherosclerosis is a complex disease requiring improvements in diagnostic techniques and therapeutic treatments. Both improvements will be facilitated by greater exploration of the biology of atherosclerotic plaque. To this end, we carried out large-scale gene expression analysis of human atherosclerotic lesions. METHODS AND RESULTS: Whole genome expression analysis of 101 plaques from patients with peripheral artery disease identified a robust gene signature (1514 genes) that is dominated by processes related to Toll-like receptor signaling, T-cell activation, cholesterol efflux, oxidative stress response, inflammatory cytokine production, vasoconstriction, and lysosomal activity. Further analysis of gene expression in microdissected carotid plaque samples revealed that this signature is differentially expressed in macrophage-rich and smooth muscle cell-containing regions. A quantitative PCR gene expression panel and inflammatory composite score were developed on the basis of the atherosclerotic plaque gene signature. When applied to serial sections of carotid plaque, the inflammatory composite score was observed to correlate with histological and morphological features related to plaque vulnerability. CONCLUSIONS: The robust mRNA expression signature identified in the present report is associated with pathological features of vulnerable atherosclerotic plaque and may be useful as a source of biomarkers and targets of novel antiatherosclerotic therapies.

Rosetta error model for gene expression analysis.

MOTIVATION: In microarray gene expression studies, the number of replicated microarrays is usually small because of cost and sample availability, resulting in unreliable variance estimation and thus unreliable statistical hypothesis tests. The unreliable variance estimation is further complicated by the fact that the technology-specific variance is intrinsically intensity-dependent. RESULTS: The Rosetta error model captures the variance-intensity relationship for various types of microarray technologies, such as single-color arrays and two-color arrays. This error model conservatively estimates intensity error and uses this value to stabilize the variance estimation. We present two commonly used error models: the intensity error-model for single-color microarrays and the ratio error model for two-color microarrays or ratios built from two single-color arrays. We present examples to demonstrate the strength of our error models in improving statistical power of microarray data analysis, particularly, in increasing expression detection sensitivity and specificity when the number of replicates is limited.

Pathway and gene-set activation measurement from mRNA expression data: the tissue distribution of human pathways.

BACKGROUND: Interpretation of lists of genes or proteins with altered expression is a critical and time-consuming part of microarray and proteomics research, but relatively little attention has been paid to methods for extracting biological meaning from these output lists. One powerful approach is to examine the expression of predefined biological pathways and gene sets, such as metabolic and signaling pathways and macromolecular complexes. Although many methods for measuring pathway expression have been proposed, a systematic analysis of the performance of multiple methods over multiple independent data sets has not previously been reported. RESULTS: Five different measures of pathway expression were compared in an analysis of nine publicly available mRNA expression data sets. The relative sensitivity of the metrics varied greatly across data sets, and the biological pathways identified for each data set are also dependent on the choice of pathway activation metric. In addition, we show that removing incoherent pathways prior to analysis improves specificity. Finally, we create and analyze a public map of pathway expression in human tissues by gene-set analysis of a large compendium of human expression data. CONCLUSION: We show that both the detection sensitivity and identity of pathways significantly perturbed in a microarray experiment are highly dependent on the analysis methods used and how incoherent pathways are treated. Analysts should thus consider using multiple approaches to test the robustness of their biological interpretations. We also provide a comprehensive picture of the tissue distribution of human gene pathways and a useful public archive of human pathway expression data.

Individual-specific variation of gene expression in peripheral blood leukocytes.

DNA microarray technology is used to determine gene expression profiles of various cell types, especially abnormal cells, such as cancer. By contrast, relatively little attention has been given to expression profiling of normal tissues. Here we describe studies of gene expression in peripheral blood leukocytes (PBL) from normal individuals sampled multiple times over periods ranging from several weeks up to 6 months. We demonstrate stable patterns of gene expression that differ between individuals. Among the genes whose expression varies by individual is a group of genes responsive to interferon stimulation. Certain individuals ( approximately 10-20% of those tested) showed higher baseline levels and lower inducibility of these genes in response to in vitro interferon stimulation. These studies demonstrate the feasibility of using DNA microarrays to measure the variations in gene expression of PBL from different individuals in response to environmental and genetic factors.

Microarray standard data set and figures of merit for comparing data processing methods and experiment designs.

MOTIVATION: There is a very large and growing level of effort toward improving the platforms, experiment designs, and data analysis methods for microarray expression profiling. Along with a growing richness in the approaches there is a growing confusion among most scientists as to how to make objective comparisons and choices between them for different applications. There is a need for a standard framework for the microarray community to compare and improve analytical and statistical methods. RESULTS: We report on a microarray data set comprising 204 in-situ synthesized oligonucleotide arrays, each hybridized with two-color cDNA samples derived from 20 different human tissues and cell lines. Design of the approximately 24 000 60mer oligonucleotides that report approximately 2500 known genes on the arrays, and design of the hybridization experiments, were carried out in a way that supports the performance assessment of alternative data processing approaches and of alternative experiment and array designs. We also propose standard figures of merit for success in detecting individual differential expression changes or expression levels, and for detecting similarities and differences in expression patterns across genes and experiments. We expect this data set and the proposed figures of merit will provide a standard framework for much of the microarray community to compare and improve many analytical and statistical methods relevant to microarray data analysis, including image processing, normalization, error modeling, combining of multiple reporters per gene, use of replicate experiments, and sample referencing schemes in measurements based on expression change. AVAILABILITY/SUPPLEMENTARY INFORMATION: Expression data and supplementary information are available at http://www.rii.com/publications/2003/HE_SDS.htm

Discovering modes of action for therapeutic compounds using a genome-wide screen of yeast heterozygotes.

Modern medicine faces the challenge of developing safer and more effective therapies to treat human diseases. Many drugs currently in use were discovered without knowledge of their underlying molecular mechanisms. Understanding their biological targets and modes of action will be essential to design improved second-generation compounds. Here, we describe the use of a genome-wide pool of tagged heterozygotes to assess the cellular effects of 78 compounds in Saccharomyces cerevisiae. Specifically, lanosterol synthase in the sterol biosynthetic pathway was identified as a target of the antianginal drug molsidomine, which may explain its cholesterol-lowering effects. Further, the rRNA processing exosome was identified as a potential target of the cell growth inhibitor 5-fluorouracil. This genome-wide screen validated previously characterized targets or helped identify potentially new modes of action for over half of the compounds tested, providing proof of this principle for analyzing the modes of action of clinically relevant compounds.