Sieving treatment biomarkers from blood gene-expression profiles: a pharmacogenomic update on two types of XXXX therapy.

@entity1 @entity1638 @entity15 @entity2391
@entity2391 ( @entity2391 ) and @entity1638 are routinely used to inhibit disease activity in @entity15 , but their mechanisms of action are incompletely understood. Individual treatment responses vary and candidate molecular markers that predict them have yet to be established. Why some @entity1 respond poorly to a certain treatment while others respond well is addressed by the pharmacogenomic approach, which postulates that the molecular response to treatment correlates with the clinical effects, and thus seeks biological markers to estimate prognosis, guide therapy, comprehend the drugs' mechanisms of action and offer insights into disease pathogenesis. A poor clinical response can be owing to genetic variants in drug receptors or signaling components, or the appearance of neutralizing antibodies that interfere with the drug's binding efficacy. Independently, such mechanisms could lead to inadequate, that is to say unchanged, molecular responses, or exceedingly increased or decreased changes. By means of DNA microarray studies, various research groups endeavour to establish a clinically relevant relationship between the biological response to these drugs and treatment effects. Molecular profiles obtained in this way differ in the pattern and number of modulated genes, suggesting the existence of an individual 'drug-response fingerprint'. To further unravel the underlying regulatory interaction structure of the genes responsive to these immunotherapies represents a daunting but inevitable task. In this article, we focus on longitudinal ex vivo transcriptomic studies in @entity15 and its therapy. We will discuss recurrently reported biomarker candidates, emphasizing those of immunologically meaning, and review studies with network module outputs.
