IDENTIFICATION OF BIOMARKERS PREDICTING STEROID RESPONSE IN ACUTE SEVERE ULCERATIVE COLITIS USING SURFACE-ENHANCED LASER DESORPTION/IONISATION TIME OF FLIGHT MASS SPECTROMETRY

Introduction: During an acute severe exacerbation of ulcerative colitis (UC), approximately two-thirds of patients will respond to intravenous corticosteroid therapy, the accepted first-line therapy. Clinical scoring systems such as the Edinburgh risk assessment and the Travis criteria incorporate standard serological tests to help predict which patients will fail to respond to corticosteroid therapy and ultimately require second-line medical therapy or surgery.

Aims and Methods: To determine novel serum and faecal biomarkers that will help to predict the outcome in acute severe UC using surface-enhanced laser desorption/ionisation–time of flight (SELDI–TOF) mass spectrometry and identify markers that may ultimately provide insight into the pathogenesis of steroid resistance. Blood and faecal samples were collected from 26 patients presenting with acute severe UC (satisfying Truelove and Witts criteria) within 24 h of starting intravenous steroid therapy. Blood samples were allowed to clot for 45 minutes before sera separation. All samples were stored at −80°C, sera were denatured using 9 mol urea, 2% CHAPS, 50 mmol TrisHCl pH 9; faecal samples were preprocessed using PhiCal extraction buffer. Samples were applied to CM10 ProteinChips (cationic exchange arrays) and mass spectra were generated using a PBS-IIc mass spectrometer at laser intensity settings of 165, 185 and 210. Spectra were calibrated and preprocessed with baseline subtraction, noise adjustment and normalisation. Peak identification was performed using ProteinChip software version 3.2.1. Peaks with a p value of less than 0.05 were considered significant discriminators between steroid-responsive and unresponsive patients.

Results: 15/26 (57.7%) patients responded to steroids, 11 underwent colectomy. Five serum biomarkers that discriminated between the two patient groups were identified. All of these markers are upregulated in steroid-responsive disease. The discriminant proteins have a mass over charge ratio (m/z) of 7565 (p = 0.004), 7927 (p = 0.003), 15 115 (p = 0.027), 15 855 (p = 0.046) and 28 007 (p = 0.040), respectively. None of the biomarkers identified in faecal samples showed a significant difference between steroid-responsive and unresponsive disease.

Conclusion: This is the first study, in the setting of acute severe UC, to look for predictive biomarkers of steroid response in serum or faecal samples using SELDI–TOF mass spectrometry. We have identified five serum biomarkers that discriminate between steroid-responsive and unresponsive individuals. Further work is being undertaken to identify these proteins and, using support vector machine analysis, to establish a model to determine the significance of protein fingerprints in predicting steroid response in acute severe UC.