OBJECTIVES: To identify autoantibody signatures in ovarian cancer using protein microarray technology. DESIGN AND METHODS: Protein microarrays were screened using non-malignant peritoneal fluid (n=30) and ascites fluid pooled from ovarian cancer patients (n=30). RESULTS: Fifteen potential tumour-associated antigens were discovered. AASDHPPT showed the strongest signal-to-noise ratio. CONCLUSIONS: Protein microarrays are suitable for autoantibody discovery in ovarian cancer but the signatures are of low frequency.
OBJECTIVES: To identify autoantibody signatures in ovarian cancer using protein microarray technology. DESIGN AND METHODS: Protein microarrays were screened using non-malignant peritoneal fluid (n=30) and ascites fluid pooled from ovarian cancerpatients (n=30). RESULTS: Fifteen potential tumour-associated antigens were discovered. AASDHPPT showed the strongest signal-to-noise ratio. CONCLUSIONS: Protein microarrays are suitable for autoantibody discovery in ovarian cancer but the signatures are of low frequency.
Authors: Frank Antony; Cecilia Deantonio; Diego Cotella; Maria Felicia Soluri; Olga Tarasiuk; Francesco Raspagliesi; Fulvio Adorni; Silvano Piazza; Yari Ciani; Claudio Santoro; Paolo Macor; Delia Mezzanzanica; Daniele Sblattero Journal: Oncoimmunology Date: 2019-06-04 Impact factor: 8.110
Authors: Judith L Luborsky; Yi Yu; Seby L Edassery; Jade Jaffar; Yuan Yee Yip; Pu Liu; Karl Eric Hellstrom; Ingegerd Hellstrom Journal: Cancer Epidemiol Biomarkers Prev Date: 2011-08-16 Impact factor: 4.254
Authors: Kathryn M Frietze; Richard B S Roden; Ji-Hyun Lee; Yang Shi; David S Peabody; Bryce Chackerian Journal: Cancer Immunol Res Date: 2015-11-20 Impact factor: 11.151
Authors: Karen S Anderson; Daniel W Cramer; Sahar Sibani; Garrick Wallstrom; Jessica Wong; Jin Park; Ji Qiu; Allison Vitonis; Joshua LaBaer Journal: J Proteome Res Date: 2014-11-17 Impact factor: 4.466