Can a microarray implicate human genes in post‐transplant lymphoproliferative disorders?

Post-transplant lymphoproliferative disorders (PTLD) are a significant cause of morbidity and mortality after solid organ transplantation in children (1, 2). Most cases are associated with Epstein–Barr virus (EBV) infection, and the risk of developing PTLD appears to be highest in children who experience primary EBV infection following transplantation (3). In this issue, Allen et al. (4) ask whether expression profiling with DNA microarrays can identify human genes whose expression might be predictive of EBVinduced lymphoproliferation after organ transplantation. The current estimate of the number of proteincoding genes in the human genome stands at 20 488, plus a hundred or so that are yet to be discovered (5). Creating the ability to profile the expression patterns of all these genes has been a driving force behind the development of DNA microarray technologies. For over a decade, DNA microarrays have been used for expression profiling of the cells involved in many different diseases. A typical array is laid out in a grid of thousands of spots, each containing a unique oligonucleotide corresponding to a specific gene. The entire human genome can be arrayed on a surface of glass, plastic, or silicon no larger than a standard microscope slide. Relatively inexpensive, commercially available DNA microarrays (or gene chips) have made the enormous complexity of the human genome accessible to experimental inquiry. Basically, molecules of mRNA purified from tissues are converted to cDNA copies which are labeled with a fluorescent dye. The labeled cDNA is applied to the microarray, where each sequence hybridizes with the complementary DNA spot and generates an area of fluorescence whose intensity is proportional to the level of that gene s expression. For each gene, the Affymetrix microarrays used by Allen et al. (4) contain a probe set of 11–20 distinct oligonucleotide probe sequences, whose signal intensities are combined to define that gene s expression intensity. Conceptually, there are many challenges that need to be overcome to conduct a microarray experiment, beginning with the array itself. Commercial and in-house produced microarrays differ in fabrication technique, probe design, assay protocol and analysis methods, all of which affect accuracy, efficiency, and cost. This lack of standardization has created what is known in the genomics community as the interoperability problem, a barrier that prevents comparisons of data obtained from different platforms. The problem is severe enough that a Microarray and Gene Expression Data Society (http:// www.mged.org/) has been formed to address the apparently limited repeatability of published microarray studies and promote stricter publication rules regarding data availability and data processing and analysis (6). In addition, the high cost of performing a genome-wide microarray means that to be clinically useful, studies need to identify the minimum number of genes required to be prognostic, which can lead to the development of a smaller-scale assay that detects the expression of those genes alone. Microarray analyses of cells in the peripheral blood may also be more useful because blood samples are easy to acquire, store, and process consistently, although determinations of significance in whole blood rather than PBMCs can be thrown off by the abundance of globin genes (7). For a good example, see Martı́nez-Lloreda et al. (8), who compared mRNA levels in PBMCs of liver transplant recipients who experienced tolerance without immunosuppression to those who Pediatr Transplantation 2009: 13: 944–947 2009 John Wiley & Sons A/S.