Over the last decade, the introduction of microarray technology has had a profound impact on gene expression research. The publication of studies with dissimilar or altogether contradictory results, obtained using different microarray platforms to analyze identical RNA samples, has raised concerns about the reliability of this technology. The MicroArray Quality Control (MAQC) project was initiated to address these concerns, as well as other performance and data analysis issues. Expression data on four titration pools from two distinct reference RNA samples were generated at multiple test sites using a variety of microarray-based and alternative technology platforms. Here we describe the experimental design and probe mapping efforts behind the MAQC project. We show intraplatform consistency across test sites as well as a high level of interplatform concordance in terms of genes identified as differentially expressed. This study provides a resource that represents an important first step toward establishing a framework for the use of microarrays in clinical and regulatory settings.

Background: Reproducibility is a fundamental requirement in scientific experiments. Some recent publications have claimed that microarrays are unreliable because lists of differentially expressed genes (DEGs) are not reproducible in similar experiments. Meanwhile, new statistical methods for identifying DEGs continue to appear in the scientific literature. The resultant variety of existing and emerging methods exacerbates confusion and continuing debate in the microarray community on the appropriate choice of methods for identifying reliable DEG lists.

Nearly one fourth of all outpatients received one or more drugs that have pharmacogenomic information in the label for that drug. The incorporation and appropriate use of pharmacogenomic information in drug labels should be tested for its ability to improve drug use and safety in the United States.

The discovery, development, and use of biomarkers for a variety of drug development purposes are areas of tremendous interest and need. Biomarkers can become accepted for use through submission of biomarker data during the drug approval process. Another emerging pathway for acceptance of biomarkers is via the biomarker qualification program developed by the Center for Drug Evaluation and Research (CDER, US Food and Drug Administration). Evidentiary standards are needed to develop and evaluate various types of biomarkers for their intended use and multiple stakeholders, including academia, industry, government, and consortia must work together to help develop this evidence. The article describes various types of biomarkers that can be useful in drug development and evidentiary considerations that are important for qualification. A path forward for coordinating efforts to identify and explore needed biomarkers is proposed for consideration.

BackgroundA number of publications have reported the use of microarray technology to identify gene expression signatures to infer mechanisms and pathways associated with systemic lupus erythematosus (SLE) in human peripheral blood mononuclear cells. However, meta-analysis approaches with microarray data have not been well-explored in SLE.MethodsIn this study, a pathway-based meta-analysis was applied to four independent gene expression oligonucleotide microarray data sets to identify gene expression signatures for SLE, and these data sets were confirmed by a fifth independent data set.ResultsDifferentially expressed genes (DEGs) were identified in each data set by comparing expression microarray data from control samples and SLE samples. Using Ingenuity Pathway Analysis software, pathways associated with the DEGs were identified in each of the four data sets. Using the leave one data set out pathway-based meta-analysis approach, a 37-gene metasignature was identified. This SLE metasignature clearly distinguished SLE patients from controls as observed by unsupervised learning methods. The final confirmation of the metasignature was achieved by applying the metasignature to a fifth independent data set.ConclusionsThe novel pathway-based meta-analysis approach proved to be a useful technique for grouping disparate microarray data sets. This technique allowed for validated conclusions to be drawn across four different data sets and confirmed by an independent fifth data set. The metasignature and pathways identified by using this approach may serve as a source for identifying therapeutic targets for SLE and may possibly be used for diagnostic and monitoring purposes. Moreover, the meta-analysis approach provides a simple, intuitive solution for combining disparate microarray data sets to identify a strong metasignature.Please see Research Highlight: http://genomemedicine.com/content/3/5/30

BACKGROUND Following allotransplantation, renal ischemia-reperfusion (I/R) injury initiates a series of events that provokes counter-adaptive immunity. Though T cells clearly mediate allospecific immunity, the manner in which reperfusion events augment their activation has not been established. In addition, comprehensive analysis of I/R injury in humans has been limited. METHODS To evaluate the earliest events occurring following allograft reperfusion and gain insight into those factors linking reperfusion to alloimmunity, we examined human renal allografts 30 to 60 minutes postreperfusion (n=10) and compared them with allografts with normal function that had resolved their I/R injury insult (>1 month posttransplant, n=6) and to normal kidneys (living donor kidneys before procurement, n=8). Biopsies were processed both for immunohistochemical analysis as well as for transcript analysis by real-time quantitative polymerase chain reaction (RT-PCR). RESULTS Reperfusion injury was characterized by increased levels of gene transcripts known to be involved in cellular adhesion, chemotaxis, apoptosis, and monocyte recruitment and activation. T-cell-associated transcripts were generally absent. However, recovered allografts exhibited increased levels of T-cell and costimulation-related gene transcripts despite normal allograft function. Consistent with these findings, the immediate postreperfusion state was characterized histologically by tubular injury and monocyte infiltration, while the stable posttransplant state was notable for T-cell infiltration. CONCLUSIONS These data suggest that monocytes and transcripts related to their recruitment dominate the immediate postreperfusion state. This gives way to a T-cell dominant milieu even in grafts selected for their stable function and absence of rejection. These data have implications for understanding the fundamental link between I/R injury and alloimmunity.

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The US FDA encourages the integration of biomarkers in drug development and their appropriate use in clinical practice. It is believed that this approach will help alleviate stagnation and foster innovation in the development of new medical products, and, ultimately, lead to more personalized medicine. To facilitate the use of biomarkers in drug development and clinical practice, the FDA organized workshops, issued guidances, established a voluntary submission process, developed online educational tools and, most importantly, strives to ensure the integration of this information into drug labels, for example, via the update of existing labels, or the inclusion of appropriate language in new drug labels. A pilot process has been set up to qualify novel biomarkers that are not associated with specific drug products, but are of more common use (e.g., biomarkers for drug safety). In addition, the FDA has initiated the creation of various consortia that are working towards the identification and characterization of exploratory biomarkers in order to qualify them for a specific use.