Despite the indisputable benefit of curative disease-specific chemotherapy regimens, the systematic administration of drugs is associated with a substantial treatment burden in hemato-oncological patients. The side effects and adverse events related to the applied therapy are generally manageable through the optimization of the drug dosage or by supportive care. Nevertheless, a considerable number of patients fail to achieve an optimal therapy response or do not benefit from such burdensome therapy at all. The early identification of patients with a priori predisposition who will not benefit from the intended chemotherapy regimens, represents fundamental clinical information that could redirect the initial therapeutic intentions towards alternative treatment strategies. From the perspective of personalized care, the recognition of reliable biomarkers that enable early stratification of patients into responders and non-responders, prior to chemotherapy administration, is greatly needed.
Gene expression patterns of candidate genes, such as those encoding regulatory microRNAs, influx and efflux drug transporters or proteins involved in key signaling pathways, are intensively studied for their predictive potential. However, in the context of the particular disease, gene expression monitoring often suffers from the underestimated pitfalls that complicate the translation of these biomarkers into the clinical space.