Marc Bonin Department of Rheumatology and Clinical Immunology Charit é University Hospital

1. Prediction of MethotrexateTreatment Response in Rheumatoid Arthritis via Affymetrix miRNA Microarray Profiling Marc Bonin, Stephan Peter, Karsten Mans, Carolin Sohnrey, Gerd-Rüdiger Burmester, Thomas Häupl, Bruno Stuhlmüller Department of Rheumatology and Clinical Immunology, Charité UniversityHospital, Berlin, Germany analysis. Accordingtothe EULAR responsecriteria 14 patients of the HIT HARD groupwerecategorizedasgoodresponders, 10 patientsas moderate responders and fourpatientsas non-responders. The ownobservationalgroupcomprisesfourgoodresponders, four moderate and four non-responders. In bothgroupsresponders and non-respondersshowed a comparablemeandiseaseactivitybefore MTX treatment (Tab. 1). Introduction: Methotrexate (MTX) is the standard medication to treat Rheumatoid Arthritis (RA). It is generally efficient and affordable. Nevertheless, some patients suffer from significant adverse effects and about 30-40% of patients do not show adequate improvement under MTX treatment1. Therefore predictors for treatment response would be useful which enable the clinician to only treat patients that will benefit from MTX. Loss of valuable time and unnecessary side effects in MTX non-responders could thus be avoided. A novel and promising class of potential biomarkers are miRNAs which exhibit several advantages such as higher stability than mRNA and abundance in many easily accessible body fluids. microRNAs are short, single-stranded, non-coding RNAs that regulate a multitude of physiological and pathological processes through posttranscriptional repression of protein-coding genes. Goal of thisstudy was todefine miRNA biomarkerstopredictresponsetomethotrexatetreatment in rheumatoid arthritis (RA) patients. Methods: Fig. 1: Hierarchicalcluster of thetestgroupbased on four miRNAs Patients of the HIT HARD groupwereclustered (euclideandistance, averagelinkage) based on four miRNAs statisticallydeterminedbetweengoodresponders (R) and non-responders (NR) to MTX as potential responsebiomarkers. (MR: moderate responder) Whole blood samples of 28 patients (test group) from the clinical trial HIT HARD were collected in PAXgene® Blood RNA Tubes (PreAnalytiX GmbH, Switzerland) prior to treatment with MTX. A second RA patient cohort (validation group, n=11) receiving MTX monotherapy was assembled from donors recruited at the Rheumatology Clinic of the Charité. Intracellular total RNA including miRNA was extracted according to the PAXgene® Blood miRNA Kit protocol (PreAnalytiX GmbH, Switzerland). Extracted total RNA samples were labeled using the FlashTag™ Biotin HSR RNA Labeling Kit for Affymetrix® GeneChip® miRNA Arrays (Genisphere, LLC., USA) and hybridized onto GeneChip® miRNA 2.0 Arrays (Affymetrix, Inc., USA) according to the manufacturer protocol. The generated signal data were background corrected (RMA), normalized (quantile) and summarized (median polish) utilizing the miRNA QC Tool v 1.1.1.0 (Affymetrix, Inc., USA).Biomarker candidates to predict MTX treatment effectiveness were determined in the well defined HIT HARD patient cohort and then validated in the second patient group recruited separately at the Rheumatology Clinic of the Charité (own observationalgroup) to asses the applicability of the miRNA predictor set. Classification of RA patients into good (R), moderate (MR) and non-responders (NR) was performed based on the DAS28 and EULAR response criteria after three to four months of MTX treatment.Differential expression of human miRNAs among four non-responders versus 14 good responders of the HIT HARD test group was determined by calculating the fold changes (FC) and p-values (one-tailed Welch’s t-test) for the miRNA expression signals between the two groups. Only miRNAs that were detected (TRUE) in all patients were included in the analysis. Hierarchical clustering for visualization was performed using Genesis 1.7.6 (IGB TU-Graz, Austria). In a secondstep all responders and non-respondersfromthetest and thevalidationgroupwereusedtopredict MTX responsewith a nearest prototype classificationmodel. A leave-one-out cross-validation was performedinstead of splittingthedataintotraining and testgroup. miRNA predictorselection and validation via Microarray analysis Onlygoodresponders and non-responderswereincluded in thestatistical analysis toselect miRNA candidatespredictiveforpatientresponseto MTX treatment. Moderate responderswereexcludedforthecalculations. Comparingonlythegoodresponders and non-responders of the HIT HARD groupfour miRNA candidateswereselectedbelow a threshold of p<0.01 allowing a gooddiscrimination of responders and non-respondersbyhierarchicalclustering (Fig. 1). Only one out of 14 good responders is classified incorrectly as non-responder while all non-responders were identified correctly (Sensitivity: 100%, Specificity: 93%). Moderate responders which were included in the clustering are distributed among both of the distinguishable groups (Fig.1). While three of the miRNA candidates are higher expressed in non-responders, one shows a lower expression in this group compared to good responders. The four miRNA candidates were validated as predictive markers for MTX treatment ineffectiveness by clustering a separate group of RA patients (own observationalgroup) according to the expression levels of the four candidate miRNAs prior to MTX treatment (Fig. 2). Hierarchical clustering again shows a good discrimination between responders and non-responders. All patients except one non-responder are classified correctly (Sensitivity: 75%, Specificity: 100%) Moderate responders again are divided between both main groups in the cluster (Fig. 2). Fig. 2: Validation group Ourownobservationalpatientgroup was clustered (euclideandistance, averagelinkage) forvalidationbased on thefour miRNA candidatesdeterminedusingthe HIT HARD patientgroup. (R: goodresponder, MR: moderate responder, NR: non-responderto MTX) Withreferencetothe MTX responsepredictiontheleave-one-out crossvalidationshoweda Sensitivity upto 65 % and a Specificityupto 95 %. The leave-one-out crossvalidationusesupto 428 genes fortheprediction. (91 of the genes are in all of the different cross-validation groups(p-value < 0,04), 0-25% (249 genes), 26-50% (26 genes). 51-75% (28 genes), 76-99% (34 genes)). The overlapbetweenthistwo different predictionmodelsaretwo genes, whichwereused in all of thecrossvalidationgrpups. Tab. 1: Patient characteristics Shownarethegender, age, diseaseduration and diseaseactivity (DAS28) priorto MTX treatmentfortheanalyzedpatients of the HIT HARD group and ourownobservationalgroupsplitupbased on theresponseto MTX after 3-4 months (EULAR responsecriteria). Results: In total PAXgene® wholebloodsamples of 39 RA patientswereanalyzed. The 28 patientsenrolled in the HIT HARD clinicaltrial (testgroup) all showedactiveearly RA with a DAS28 >5.1 and a diseasedurationlessthatoneyearpriortotreatment. The 11 patientsrecruitedseparatelyat Rheumatology Clinic of theCharité (validationgroup) showed a diseaseduration of lessthantwoyearsexceptfortwo moderate responders. Patientswereselectedwhichhadreceivednooronlylowdoses of steroidsatthe time of bloodsamplingprecedingthe MTX treatmenttoavoidhighlychangedexpressionpatternscausedby high doses of steroidstodistorttheintended Conclusion: Prediction of responseto MTX therapyusingmicroarrayanalysesallowsreducingcosts, preventingsideeffects and is an opportunityforeffective„individualizedmedicine“. Next tomRNAexpression analysis theinvestigationof miRNAs asposttranscriptionalregulatorscouldprovehelpfultobetterunderstandphysiological and pathologicalprocesses, todefine miRNA biomarkers and predictresponsetomedication. Contacts: Marc Bonin Department of Rheumatology and Clinical Immunology Charité University Hospital Charitéplatz 1 D-10117 Berlin Germany Tel: +49(0) 30 450 513 296 Fax: +49(0) 30 450 513 968 E-Mail: marc.bonin@charite.de Web: www.charite-bioinformatik.de www.charite-bioinformatik.de