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e1188 B58: Evaluation of tumour-associated autoantibody signature for the diagnosis of prostate cancer Kalnina Z. 1 , Lietuvietis V. 2 , Sadovska L. 1 , Zayakin P. 1 , Sperga G. 2 , Silina K. 1 , Miculis K. 3 , Line A. 1 , Zane Kalnina 1 Latvian Biomedical Research And Study Centre, Cancer Biomarker Group, Riga, Latvia, 2 Riga East University Hospital, Dept. of Urology, Riga, Latvia, 3 Riga Stradins University, Faculty of Medicine, Riga, Latvia INTRODUCTION & OBJECTIVES: Prostate cancer (PC) currently is the most commonly diagnosed malignancy in men in developed countries. The widely used PSA test has substantially aided to the diagnosis of PC, however it lacks specificity and intrinsically cannot define aggressiveness of PC. Thus, the identification of novel more specific non-invasive diagnostic and prognostic PC biomarkers is still of major interest. Circulating IgG class autoantibodies against tumour-associated antigens (TAAs) – due to their specificity, stability in serum and ease of access - have been shown to be promising biomarker candidates. This study was aimed for the identification and exploration of the PC-associated autoantibody repertoires in order to identify a biomarker signature with potential diagnostic and prognostic value. MATERIAL & METHODS: A set of 158 PC-associated T7 phage-displayed antigen clones, identified in our previous study, was selected for the development of a focussed phage-displayed antigen microarray. It was used to systematically survey for the presence of specific autoantibodies serum samples from 248 PC and 222 BPH and/or prostatitis patients, and 161 healthy male controls (HC). After microarray data normalisation and setting of a cut-off value to define positive signal, each antigen was ranked according to the detected serum autoantibody signal intensity and frequency of reactivity in PC patients compared to HD, and a serum score (SS) was calculated for each serum by summing up the intensities of sero-positive antigens. The used statistical tests included non-parametric Fisher’s exact and Mann-Whitney U tests, and ROC curve analyses. Leave one-out cross-validation approach was used for biomarker model verification. The logistic regression model was used to determine merged diagnostic performance of TAA and total PSA tests. RESULTS: Obtained sero-reactivity data revealed 42 TAAs with a positive rating. Among top-ranked antigens there were known TAAs - SSX2, NY-ESO-1, MAGEC1/C2, TP53, Koc1 and several novel antigens. From the samples analysed, 45% of PC, 26% BPH/prostatitis and 10% of HC sera had a positive score, yet the mean scores within the PC cohort were substantially higher - 1.82 in contrast to 0.2 in HD and 0.72 in BPH/prostatitis group. The SS could discriminate between PC and HC with AUC of 0.63 (Sn=0.33, Sp=0.9, p=1.4x10 -7 , 95% CI), and PC versus BPH/prostatitis group with AUC of 0.61 (Sn=0.25, Sp=0.9, p=1.9x10 -6 , 95% CI); however, showed no added diagnostic value to the PSA test within the ‘grey zone’. Nevertheless, we identified an autoantibody signature capable to distinguish high Gleason score (>7) PC from medium/low (<7) with 41% sensitivity and 90% specificity (p=1.1x10 -5 , 95% CI). It included autoantibodies against MAGEC1/C2, MAGEA12 and SSX2 and performed regardless of the total PSA levels. Moreover, SS were shown to increase depending on primary tumour size, indicating that it may have direct impact on the tumour antigen load and therefore specific autoantibody titres. CONCLUSIONS: The study demonstrated that the identified serum autoantibody signature has no substantial added diagnostic value to the PSA test; however, it may contribute to the discrimination between aggressive and indolent PC types and/or earlier detection of advanced PC. Further validation in an independent patient cohort would be needed to ascertain the clinical use of the identfied biomarkers. Eur Urol Suppl 2014; 13(2): e1188
