Dr. Bruno Stuhlmüller and his team at Charité, Free University and Humboldt University in Berlin have used whole-genome mRNA and miRNA microarray analysis to identify RNA biomarkers that enable accurate prediction of successful anti-TNF therapy in rheumatoid arthritis (RA) patients. The test yields a sensitive and specific predictive gene signature from whole blood, which is necessary for practical clinical use.

To date, no diagnostic tools are available to identify the molecular differences among RA patients, or to predict an individual's response to therapy. Patients with chronic autoimmune diseases such as RA often undergo many different tests, none of which are definitive predictors of therapeutic effectiveness. Therapy becomes a trial-and-error process. Meanwhile, the disease progresses. Delivering the right patient treatment the first time can improve the standard of care, improve patient well-being, and decrease healthcare costs.

Dr. Stuhlmüller's team sought to identify and validate mRNA and miRNA biomarkers that reveal molecular parameters to define the success of various therapy strategies for RA. They chose GeneChip® U133 Plus 2.0 Array from Affymetrix to conduct expression analysis in whole-blood samples. The protocol was highly automated, done in collaboration with Drs. Thomas Häupl, MD and Andreas Grützka, who developed computational tools that recalculate differences in cell compositions in whole blood prior to transcriptomic analyses. Using this approach, the team identified 11 RNA biomarkers that allow accurate prediction of successful anti-TNF therapy in RA patients.

With GeneChip U133 Plus 2.0 Array, the team will be able to validate additional biomarkers, and to translate the signatures immediately into clinically applicable test systems for diagnosis, prognosis, therapy monitoring, and prediction of successful therapies for RA individuals. Next, they plan to expand the size of the patient cohort and conduct a larger validation trial. They will continue to use whole-genome microarray transcription profiling to define predictive biomarkers for other biologics or drugs used in RA treatment. Dr. Stuhlmüller anticipates that the identification of RNA biomarkers needed for diagnosis, prognosis, therapy monitoring, or prediction of therapeutic success might open new avenues for personalized medicine.

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