Autoantibody biomarkers for the detection of serous ovarian cancer

Objective The purpose of this study was to identify a panel of novel serum tumor antigen-associated autoantibody (TAAb) biomarkers for the diagnosis of high-grade serous ovarian cancer. Methods. To detect TAAb we probed high-density programmable protein microarrays (NAPPA) containing 10,247 antigens with sera from patients with serous ovarian cancer (n = 30 cases/30 healthy controls) and measured bound IgG. We identified 735 promising tumor antigens and evaluated these with an independent set of serous ovarian cancer sera (n = 30 cases/30 benign disease controls/30 healthy controls). Thirty-nine potential tumor autoantigens were identified and evaluated using an orthogonal programmable ELISA platform against a total of 153 sera samples (n = 63 cases/30 benign disease controls/60 healthy controls). Sensitivities at 95% specificity were calculated and a classifier for the detection of high-grade serous ovarian cancer was constructed. Results. We identified 11-TAAbs (ICAM3, CTAG2, p53, STYXLI, PVR, POMC, NUDT11, TRIM39, UHMK1, KSR1, and NXF3) that distinguished high-grade serous ovarian cancer cases from healthy controls with a combined 45% sensitivity at 98% specificity. Conclusion. These are potential circulating biomarkers for the detection of serous ovarian cancer, and warrant confirmation in larger clinical cohorts. (C) 2017 Elsevier Inc. All rights reserved.