Microarrays Technologies 2006: an overview

Comparison of mRNA and protein measures of cytokines following vaccination with human papillomavirus-16 L1 virus-like particles

BACKGROUND

mRNA expression signatures are frequently used as surrogate measures of cellular function and pathway changes. Few studies have directly compared results obtained using gene expression and multiplex protein assays for corresponding gene products.

METHODS

We used data available from a clinical trial of a human papillomavirus-16 vaccine that tracked gene expression and cytokine/chemokine production by peripheral blood mononuclear cells stimulated in culture with various antigens to evaluate the degree to which gene expression levels reflect observed levels of cytokines/chemokines. Twenty-six women enrolled in a phase II clinical trial of a human papillomavirus-16 vaccine were evaluated for gene expression (using the Affymetrix Human Genome Focus Array) and cytokine/chemokine levels (using a bead-based 22-plex cytokine assay developed by Linco Research, Inc.) before and after vaccination.

RESULTS

Our results suggest the presence of a wide range of correlations between mRNA expression and secreted protein levels. The strongest correlation was observed for IFN-gamma (R = 0.90 overall levels; R = 0.69 when vaccine induced changes were evaluated). More modest overall correlations ranging from 0.40 to 0.80 were observed for MIP1A, IP10, TNF-alpha, MCP1, IL-2, GM-CSF, IL-5, RANTES, and IL-8. Weaker or no correlation was observed between gene expression and protein levels for the remaining cytokines/chemokines evaluated.

CONCLUSION

The degree of correlation between gene expression and protein levels varied among different cytokines/chemokines.

IMPACT

Researchers should be cautious when using mRNA expression array results as a proxy for protein levels using existing technologies.

Diagnostic microarrays in hematologic oncology: applications of high- and low-density arrays

Microarrays have become important tools for high-throughput analysis of gene expression, chromosome aberrations, and gene mutations in cancer cells. In addition to high-density experimental microarrays, low-density, gel-based biochip technology represents a versatile platform for translation of research into clinical practice. Gel-based microarrays (biochips) consist of nanoliter gel drops on a hydrophobic surface with different immobilized biopolymers (primarily nucleic acids and proteins). Because of the high immobilization capacity of the gel, such biochips have a high probe concentration and high levels of fluorescence signals after hybridization, which allow the use of simple, portable detection systems. The notable accuracy of the analysis is reached as a result of the high level of discrimination between positive and negative gel-bound probes. Different applications of biochips in the field of hematologic oncology include analysis of chromosomal translocations in leukemias, diagnostics of T-cell lymphomas, and pharmacogenetics.

The development of a comparison approach for Illumina bead chips unravels unexpected challenges applying newest generation microarrays

Background

The MAQC project demonstrated that microarrays with comparable content show inter- and intra-platform reproducibility. However, since the content of gene databases still increases, the development of new generations of microarrays covering new content is mandatory. To better understand the potential challenges updated microarray content might pose on clinical and biological projects we developed a methodology consisting of in silico analyses combined with performance analysis using real biological samples.

Results

Here we clearly demonstrate that not only oligonucleotide design but also database content and annotation strongly influence comparability and performance of subsequent generations of microarrays. Additionally, using human blood samples and purified T lymphocyte subsets as two independent examples, we show that a performance analysis using biological samples is crucial for the assessment of consistency and differences.

Conclusion

This study provides an important resource assisting investigators in comparing microarrays of updated content especially when working in a clinical or regulatory setting.

Identification of intra-group, inter-individual, and gene-specific variances in mRNA expression profiles in the rheumatoid arthritis synovial membrane

Introduction

Rheumatoid arthritis (RA) is a chronic inflammatory and destructive joint disease characterized by overexpression of pro-inflammatory/pro-destructive genes and other activating genes (for example, proto-oncogenes) in the synovial membrane (SM). The gene expression in disease is often characterized by significant inter-individual variances via specific synchronization/desynchronization of gene expression. To elucidate the contribution of the variance to the pathogenesis of disease, expression variances were tested in SM samples of RA patients, osteoarthritis (OA) patients, and normal controls (NCs).

Method

Analysis of gene expression in RA, OA, and NC samples was carried out using Affymetrix U133A/B oligonucleotide arrays, and the results were validated by real-time reverse transcription-polymerase chain reaction. For the comparison between RA and NC, 568 genes with significantly different variances in the two groups (P ≤ 0.05; Bonferroni/Holm corrected Brown-Forsythe version of the Levene test) were selected. For the comparison between RA and OA, 333 genes were selected. By means of the Kyoto Encyclopedia of Genes and Genomes, the pathways/complexes significantly affected by higher gene expression variances were identified in each group.

Results

Ten pathways/complexes significantly affected by higher gene expression variances were identified in RA compared with NC, including cytokine–cytokine receptor interactions, the transforming growth factor-beta pathway, and anti-apoptosis. Compared with OA, three pathways with significantly higher variances were identified in RA (for example, B-cell receptor signaling and vascular endothelial growth factor signaling). Functionally, the majority of the identified pathways are involved in the regulation of inflammation, proliferation, cell survival, and angiogenesis.

Conclusion

In RA, a number of disease-relevant or even disease-specific pathways/complexes are characterized by broad intra-group inter-individual expression variances. Thus, RA pathogenesis in different individuals may depend to a lesser extent on common alterations of the expression of specific key genes, and rather on individual-specific alterations of different genes resulting in common disturbances of key pathways.

Development and application of a microarray meter tool to optimize microarray experiments

Background

Successful microarray experimentation requires a complex interplay between the slide chemistry, the printing pins, the nucleic acid probes and targets, and the hybridization milieu. Optimization of these parameters and a careful evaluation of emerging slide chemistries are a prerequisite to any large scale array fabrication effort. We have developed a 'microarray meter' tool which assesses the inherent variations associated with microarray measurement prior to embarking on large scale projects.

Findings

The microarray meter consists of nucleic acid targets (reference and dynamic range control) and probe components. Different plate designs containing identical probe material were formulated to accommodate different robotic and pin designs. We examined the variability in probe quality and quantity (as judged by the amount of DNA printed and remaining post-hybridization) using three robots equipped with capillary printing pins.

Discussion

The generation of microarray data with minimal variation requires consistent quality control of the (DNA microarray) manufacturing and experimental processes. Spot reproducibility is a measure primarily of the variations associated with printing. The microarray meter assesses array quality by measuring the DNA content for every feature. It provides a post-hybridization analysis of array quality by scoring probe performance using three metrics, a) a measure of variability in the signal intensities, b) a measure of the signal dynamic range and c) a measure of variability of the spot morphologies.

Applications of microarrays and biochips in pharmacogenomics

The complete sequence of the human genome and subsequent intensive searches for polymorphic variations are providing the prerequisite markers necessary to facilitate elucidation of the genetic variability in drug responses. Improvements in the sensitivity and precision of DNA microarrays permit a detailed and accurate scrutiny of the human genome. These advances have the potential to significantly improve health care management by improving disease diagnosis and targeting molecular therapy. Pharmacogenetic approaches, in limited use today, will become an integral part of therapeutic monitoring and health management, permitting patient stratification in advance of treatments, with the potential to eliminate adverse drug reactions. In this chapter, the current state of biochip technology is discussed, and recent applications in the arena of clinic diagnostics are explored.

Advancing mammalian cell culture engineering using genome-scale technologies

Mammalian cell-derived protein therapeutic production has changed the landscape of human healthcare in the past two decades. The importance of protein therapeutics has motivated the search for more cost-effective and efficient cell lines capable of producing high quality protein products. The factors contributing to optimal producer cell lines are often complex, and not simply conferred by one gene or gene product, which makes an understanding of system-wide properties for better engineering of optimized cell lines essential. Genome-scale technologies (genomics, transcriptomics and proteomics) enable such engineering studies. However, the use of these technologies in cell culture engineering is still in its infancy. Here, we summarize current knowledge of cell properties important for the design of efficient protein-producing mammalian cell lines, and highlight relevant studies to-date that use genome-scale technologies in these cell systems. We also provide a focused review of relevant alternative and emerging technologies, which have seen limited use in cell culture engineering, but hold great potential for significant advancements in protein therapeutic production.

Taking gene-expression profiling to the clinic: when will molecular signatures become relevant to patient care?

The advent of microarray technology has enabled scientists to simultaneously investigate the expression of thousands of genes. Gene-expression profiling studies have provided a molecular classification of breast cancer into clinically relevant subtypes, new tools to predict disease recurrence and response to different treatments, and new insights into various oncogenic pathways and the process of metastatic progression. Here we describe the state of the art of gene-expression studies in breast cancer, and consider both their current limitations and future promises. We also discuss the potential of molecular signatures to have an impact on individual breast cancer patient management, and ultimately to accelerate the transition between empirical and tailored medicine.