Gene expression profiling of cardiovascular disease models

Recent development of gene expression profiling technologies has enabled the large-scale analysis of gene expression changes during disease progression. Frequently, cardiovascular diseases involve complex interactions of multiple cell types over prolonged periods of time. A better understanding of the pathology of cardiovascular diseases and the potential identification of underlying genetic defects are currently being explored by using profiling methodologies in a number of animal and tissue-culture models.     

Peripheral blood gene expression profiles in COPD subjects

To identify non-invasive gene expression markers for chronic obstructive pulmonary disease (COPD), we performed genome-wide expression profiling of peripheral blood samples from 12 subjects with significant airflow obstruction and an equal number of non-obstructed controls. RNA was isolated from Peripheral Blood Mononuclear Cells (PBMCs) and gene expression was assessed using Affymetrix U133 Plus 2.0 arrays.Tests for gene expression changes that discriminate between COPD cases (FEV1< 70% predicted, FEV1/FVC < 0.7) and controls (FEV1> 80% predicted, FEV1/FVC > 0.7) were performed using Significance Analysis of Microarrays (SAM) and Bayesian Analysis of Differential Gene Expression (BADGE). Using either test at high stringency (SAM median FDR = 0 or BADGE p < 0.01) we identified differential expression for 45 known genes. Correlation of gene expression with lung function measurements (FEV1 & FEV1/FVC), using both Pearson and Spearman correlation coefficients (p < 0.05), identified a set of 86 genes. A total of 16 markers showed evidence of significant correlation (p < 0.05) with quantitative traits and differential expression between cases and controls. We further compared our peripheral gene expression markers with those we previously identified from lung tissue of the same cohort. Two genes, RP9and NAPE-PLD, were identified as decreased in COPD cases compared to controls in both lung tissue and blood. These results contribute to our understanding of gene expression changes in the peripheral blood of patients with COPD and may provide insight into potential mechanisms involved in the disease.     

Beta-Adrenergic gene therapy for cardiovascular disease

Gene therapy using in vivo recombinant adenovirus-mediated gene transfer is an effective technique that offers great potential to improve existing drug treatments for the complex cardiovascular diseases of heart failure and vascular smooth muscle intimal hyperplasia. Cardiac-specific adenovirus-mediated transfer of the carboxyl-terminus of the β-adrenergic receptor kinase (βARKct), acting as a G_βγ-β-adrenergic receptor kinase (βARK)1 inhibitor, improves basal and agonist-induced cardiac performance in both normal and failing rabbit hearts. In addition, βARKct adenovirus infection of vascular smooth muscle is capable of significantly diminishing neointimal proliferation after angioplasty. Therefore, further investigation is warranted to determine whether inhibition of βARK1 activity and sequestration of G_βγ via an adenovirus that encodes the βARKct transgene might be a useful clinical tool for the treatment of cardiovascular pathologies.     

Differential gene expression profiling in blood from patients with digestive system cancers

To develop a non-invasive and sensitive diagnostic test for cancer using peripheral blood, we evaluated gene expression profiling of blood obtained from patients with cancer of the digestive system and normal subjects. The expression profiles of blood-derived total RNA obtained from 39 cancer patients (11 colon cancer, 14 gastric cancer, and 14 pancreatic cancer) was clearly different from those obtained from 15 normal subjects. By comparing the gene expression profiles of cancer patients and normal subjects, 25 cancer-differentiating genes (p < 5.0 × 10⁻⁶ and fold differences >3) were identified and an “expression index” deduced from the expression values of these genes differentiated the validation cohort (11 colon cancer, 8 gastric cancer, 18 pancreatic cancer, and 15 normal subjects) into cancer patients and normal subjects with 100% (37/37) and 87% (13/15) accuracy, respectively. Although, the expression profiles were not clearly different between the cancer patients, some characteristic genes were identified according to the stage and species of the cancer. Interestingly, many immune-related genes such as antigen presenting, cell cycle accelerating, and apoptosis- and stress-inducing genes were up-regulated in cancer patients, reflecting the active turnover of immune regulatory cells in cancer patients. These results showed the potential relevance of peripheral blood gene expression profiling for the development of new diagnostic examination tools for cancer patients.     

VizStruct: exploratory visualization for gene expression profiling

MOTIVATION: DNA arrays provide a broad snapshot of the state of the cell by measuring the expression levels of thousands of genes simultaneously. Visualization techniques can enable the exploration and detection of patterns and relationships in a complex data set by presenting the data in a graphical format in which the key characteristics become more apparent. The dimensionality and size of array data sets however present significant challenges to visualization. The purpose of this study is to present an interactive approach for visualizing variations in gene expression profiles and to assess its usefulness for classifying samples. RESULTS: The first Fourier harmonic projection was used to map multi-dimensional gene expression data to two dimensions in an implementation called VizStruct. The visualization method was tested using the differentially expressed genes identified in eight separate gene expression data sets. The samples were classified using the oblique decision tree (OC1) algorithm to provide a procedure for visualization-driven classification. The classifiers were evaluated by the holdout and the cross-validation techniques. The proposed method was found to achieve high accuracy. AVAILABILITY: Detailed mathematical derivation of all mapping properties as well as figures in color can be found as supplementary on the web page http://www.cse.buffalo.edu/DBGROUP/bioinformatics/supplementary/vizstruct. All programs were written in Java and Matlab and software code is available by request from the first author.     

A quality-controlled microarray method for gene expression profiling

Gene expression profiling on microarrays is widely used to measure the expression of large numbers of genes in a single experiment. Because of the high cost of this method, feasible numbers of replicates are limited, thus impairing the power of statistical analysis. As a step toward reducing technically induced variation, we developed a procedure of sample preparation and analysis that minimizes the number of sample manipulation steps, introduces quality control before array hybridization, and allows recovery of the prepared mRNA for independent validation of results. Sample preparation is based on mRNA separation using oligo(dT) magnetic beads, which are subsequently used for first-strand cDNA synthesis on the beads. cDNA covalently bound to the magnetic beads is used as template for second-strand cDNA synthesis, leaving the intact mRNA in solution for further analysis. The quality of the synthesized cDNA can be assessed by quantitative polymerase chain reaction using 3'- and 5'-specific primer pairs for housekeeping genes such as glyceraldehyde-3-phosphate dehydrogenase. Second-strand cDNA is chemically labeled with fluorescent dyes to avoid dye bias in enzymatic labeling reactions. After hybridization of two differently labeled samples to microarray slides, arrays are scanned and images analyzed automatically with high reproducibility. Quantile-normalized data from five biological replica display a coefficient of variation 45% for 90% of profiled genes, allowing detection of twofold changes with false positive and false negative rates of 10% each. We demonstrate successful application of the procedure for expression profiling in plant leaf tissue. However, the method could be easily adapted for samples from animal including human or from microbial origin.     

A system for assessment of monokine gene expression using human whole blood

Monocyte derived cytokines (monokines) are important mediators in inflammatory diseases and cancer. Control of monokine expression is also a major therapeutic target in autoimmune inflammation. Whole blood cultures permit examination of monokine expression under conditions which emulate the in-vivo environment whilst avoiding many of the artefacts associated with monocyte separation and culture. Here we describe a system for measuring interleukin-1β, interleukin-1α, interleukin-6 and tumour necrosis factor-α mRNA in stimulated human whole blood ex-vivo, which can be applied to specimens from treated patients. Oligodeoxyribonucleotide probes are designed to allow standardisation of hybridisation and washing procedures. Washing and reprobing of membranes in appropriate sequence permits measurement of each monokine mRNA and mRNA for glyceraldehyde-3-phosphate dehydrogenase in only 7 ml of lipopolysaccharide-stimulated human blood. The method has been used successfully in studies of dexamethasone and methotrexate action on lipopolysaccharide stimulated IL-β gene expression.     

Global functional profiling of gene expression

The typical result of a microarray experiment is a list of tens or hundreds of genes found to be differentially regulated in the condition under study. Independent of the methods used to select these genes, the common task faced by any researcher is to translate these lists of genes into a better understanding of the biological phenomena involved. Currently, this is done through a tedious combination of searches through the literature and a number of public databases. We developed Onto-Express (OE) as a novel tool able to automatically translate such lists of differentially regulated genes into functional profiles characterizing the impact of the condition studied. OE constructs functional profiles (using Gene Ontology terms) for the following categories: biochemical function, biological process, cellular role, cellular component, molecular function, and chromosome location. Statistical significance values are calculated for each category. We demonstrate the validity and the utility of this comprehensive global analysis of gene function by analyzing two breast cancer datasets from two separate laboratories. OE was able to identify correctly all biological processes postulated by the original authors, as well as discover novel relevant mechanisms.     

Role of gene expression profiling for diagnosing acute leukemias

Cytomorphology and cytochemistry in combination with multiparameter immunophenotyping today are the standard methods for establishing the diagnosis of acute leukemias. In addition, cytogenetics, fluorescence in situ hybridization, and polymerase chain reaction based assays provide important information regarding biologically defined and prognostically relevant subgroups and allow a comprehensive diagnosis of well defined subentities. With regard to the clinical setting a better understanding of the clinical course of distinct biologically defined disease subtypes is needed to select disease-specific therapeutic approaches. Paralleling the increase in knowledge on deregulated pathways in leukemia the development of new therapeutics is accelerated and therefore requires a detailed and comprehensive diagnostic tool. Revealing and quantifying the expression status of many ten thousands of genes in a single analysis the microarray technology holds this potential to become an essential tool for the molecular classification of leukemias. It may therefore be used as a routine method for diagnostic purposes in the near future. Furthermore, it is anticipated that new biologically defined and clinically relevant subtypes of leukemia will be identified based on gene expression profiling. This method may therefore guide therapeutic decisions.