PURPOSE: CA-125 has been a valuable marker for detecting ovarian cancer, however, it is not sensitive enough to detect early-stage disease and not specific to ovarian cancer. The purpose of our study was to identify autoantibody markers that are specific to ovarian cancer regardless of CA-125 levels. METHODS: Top-down and iTRAQ quantitative proteomics methods were used to identify high-frequency autoantibodies in ovarian cancer. Protein microarrays comprising the recombinant autoantigens were screened using serum samples from various stages of ovarian cancer with diverse levels of CA-125 as well as benign and healthy controls. ROC curve and dot blot analyses were performed to validate the sensitivity and specificity of the autoantibody markers. RESULTS: The proteomics methodologies identified more than 60 potential high-frequency autoantibodies in ovarian cancer. Individual serum samples from ovarian cancer stages I-IV compared to control samples that were screened on a microarray containing native recombinant autoantigens revealed a panel of stage I high-frequency autoantibodies. Preliminary ROC curve and dot blot analyses performed with the ovarian cancer samples showed higher specificity and sensitivity as compared to CA-125. Three autoantibody markers exhibited higher specificity in various stages of ovarian cancer with low and normal CA-125 levels. CONCLUSIONS: Proteomics technologies are suitable for the identification of protein biomarkers and also the identification of autoantibody biomarkers when combined with protein microarray screening. Using native recombinant autoantigen arrays to screen autoantibody markers, it is possible to identify markers with higher sensitivity and specificity than CA-125 that are relevant to early detection of ovarian cancer.
PURPOSE:CA-125 has been a valuable marker for detecting ovarian cancer, however, it is not sensitive enough to detect early-stage disease and not specific to ovarian cancer. The purpose of our study was to identify autoantibody markers that are specific to ovarian cancer regardless of CA-125 levels. METHODS: Top-down and iTRAQ quantitative proteomics methods were used to identify high-frequency autoantibodies in ovarian cancer. Protein microarrays comprising the recombinant autoantigens were screened using serum samples from various stages of ovarian cancer with diverse levels of CA-125 as well as benign and healthy controls. ROC curve and dot blot analyses were performed to validate the sensitivity and specificity of the autoantibody markers. RESULTS: The proteomics methodologies identified more than 60 potential high-frequency autoantibodies in ovarian cancer. Individual serum samples from ovarian cancer stages I-IV compared to control samples that were screened on a microarray containing native recombinant autoantigens revealed a panel of stage I high-frequency autoantibodies. Preliminary ROC curve and dot blot analyses performed with the ovarian cancer samples showed higher specificity and sensitivity as compared to CA-125. Three autoantibody markers exhibited higher specificity in various stages of ovarian cancer with low and normal CA-125 levels. CONCLUSIONS: Proteomics technologies are suitable for the identification of protein biomarkers and also the identification of autoantibody biomarkers when combined with protein microarray screening. Using native recombinant autoantigen arrays to screen autoantibody markers, it is possible to identify markers with higher sensitivity and specificity than CA-125 that are relevant to early detection of ovarian cancer.
Authors: Xiaoju Wang; Jianjun Yu; Arun Sreekumar; Sooryanarayana Varambally; Ronglai Shen; Donald Giacherio; Rohit Mehra; James E Montie; Kenneth J Pienta; Martin G Sanda; Philip W Kantoff; Mark A Rubin; John T Wei; Debashis Ghosh; Arul M Chinnaiyan Journal: N Engl J Med Date: 2005-09-22 Impact factor: 91.245
Authors: Daniel G Rosen; Lin Wang; J Neeley Atkinson; Yinhua Yu; Karen H Lu; Eleftherios P Diamandis; Ingegerd Hellstrom; Samuel C Mok; Jinsong Liu; Robert C Bast Journal: Gynecol Oncol Date: 2005-08-02 Impact factor: 5.482
Authors: Stefanie Brezina; Regina Soldo; Roman Kreuzhuber; Philipp Hofer; Andrea Gsur; Andreas Weinhaeusel Journal: Microarrays (Basel) Date: 2015-04-02