Pattern robustness of diagnostic gene expression signatures in leukemia.

Microarray technology has been proposed as an addition to the methods in current use for diagnosing leukemia. Before a new technology can be used in a diagnostic setting, the method has to be shown to produce robust results. It is known that, given the technical aspects of specimen sampling and target preparation, global gene expression patterns can change dramatically. Various parameters such as RNA degradation, shipment time, sample purity, and patient age can principally influence measured gene expression. However, thus far, no information has been available on the robustness of a diagnostic gene expression signature. We demonstrate here that for a subset of acute leukemia, expression profiling is applicable in a diagnostic setting, considering various influencing parameters. With the use of a set of differentially expressed genes, that is, a diagnostic gene expression signature, four genetically defined acute myeloid leukemia subtypes with recurrent chromosomal aberrations can clearly be identified. In addition, we show that preparation by different operators and using different sample-handling procedures did not impair the robustness of diagnostic expression signatures. In conclusion, our results provide additional support for the applicability of microarrays in a diagnostic setting, and we have been encouraged to enroll patients in a prospective study in which microarrays will be tested as an additional routine diagnostic method in parallel with standard diagnostic procedures.