Using protein microarray to identify and evaluate autoantibodies to tumor‐associated antigens in ovarian cancer

Alexandros G.Sfakianakis shared this article with you from Inoreader Using protein microarray to identify and evaluate autoantibodies to tumor‐associated antigens in ovarian cancer Μέσω Cancer Science Abstract The aim of this study was to develop a non‐invasive serological diagnostic approach in identifying and evaluating a panel of candidate autoantibodies to tumor‐associated antigens (TAAs) based on protein microarray technology for early detection of ovarian cancer (OC). Protein microarray based on 154 proteins encoded by 138 cancer driver genes was used to screen candidate anti‐TAA autoantibodies in discovery cohort containing 17 OC and 27 normal controls. Indirect enzyme‐linked immunosorbent assay (ELISA) was used to detect the content of candidate anti‐TAA autoantibodies in sera from 140 subjects in training cohort. Differential anti‐TAA autoantibodies were further validated in the validation cohort with 328 subjects. Subsequently, 112 sera from the patients with ovarian benign diseases with 104 OC sera and 104 NC sera together were recruited to identify the specificity of representative autoantibodies to OC among ovarian diseases. Five TAAs (GNAS, NPM1, FUBP1, p53, KR AS) were screened out in discovery phase, in which four of them presented higher levels in OC than controls (P<0.05) in training cohort, which was consistent with the result in the subsequent validation cohort. An optimized panel of three anti‐TAA (GNAS, p53 and NPM1) autoantibodies was identified to have relative higher sensitivity (51.2%), specificity (86.0%) and accuracy (68.6%), respectively. This panel can identify 51% of OC patients with CA125 negative. This study supports our assumption that anti‐TAA autoantibodies can be considered as potential diagnostic biomarkers for detection of OC, especially a panel of three anti‐TAA autoantibodies could be a good tool in immunodiagnosis of OC. View on the web Inoreader. Take back control of your news feed. Follow us on Twitter and Facebook.