Parallel gene expression profiling of mantle cell lymphoma - How do we transform 'omics data into clinical practice

DNA microarray technology has been a valuable tool to provide a global view of the changes in gene expression that characterize different types of B cell lymphomas, both in relation to clinical parameters but also in comparison with the non-malignant counterparts. The number of transcripts that can be analyzed on an array has dramatically increased, and now most commercially available arrays cover the whole genome, enabling overall analysis of the transcriptome. The backside of collecting this massive amount of information is that even after strict data filtering, it is impossible to do follow-up studies on all findings. Down-stream analysis is time-consuming and when performing confirmatory experiments on the protein level, the experiments are in most cases restricted to proteins recognized by commercially available reagents. Furthermore, since gene expression data is a comparative method not only are the experimental set-up but also the characteristics of both the sample and reference crucial for our ability to answer the questions posed. Thus, initial care must be taken in the design of the experiment and the preparation of the samples. The aim of this review is to discuss the progress in mantle cell lymphoma research enabled by gene expression analysis and to pinpoint the difficulties in making efficient use of the generated data to provide a fast and accurate clinical diagnosis, efficient stratification of patients into disease sub-groups and improved therapy.