4.5 Article

Evaluation of apolipoprotein A1 and posttranslationally modified forms of transthyretin as biomarkers for ovarian cancer detection in an independent study population

Journal

CANCER EPIDEMIOLOGY BIOMARKERS & PREVENTION
Volume 15, Issue 9, Pages 1641-1646

Publisher

AMER ASSOC CANCER RESEARCH
DOI: 10.1158/1055-9965.EPI-05-0980

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Background: Although overall 5-year survival rates for ovarian cancer are poor (10-30%), stage I/Ila patients have a 95% 5-year survival. New biomarkers that improve the diagnostic performance of existing tumor markers are critically needed. A previous study by Zhang et al. reported identification and validation of three biomarkers using proteomic profiling that together improved early-stage ovarian cancer detection. Methods: To evaluate these markers in an independent study population, postdiagnostic/pretreatment serum samples were collected from women hospitalized at the Mayo Clinic from 1980 to 1989 as part of the National Cancer Institute Immunodiagnostic Serum Bank. Sera from 42 women with ovarian cancer, 65 with benign tumors, and 76 with digestive diseases were included in this study. Levels of various posttranslationally forms of transthyretin and apolipoprotein A1 were measured in addition to CA125. Results: Mean levels of five of the six forms of transthyretin were significantly lower in cases than in controls. The specificity of a model including transthyretin and apolipoprotein A1 alone was high [96.5%; 95% confidence interval (95% CI), 91.9-98.8%] but sensitivity was low (52.4%; 95% CI, 36.4-68.0%). A class prediction algorithm using all seven markers, CA125, and age maintained high specificity (94.3%; 95% CI, 89.1-97.5%) but had higher sensitivity (78.6%; 95% CI, 63.2-89.7%). Conclusions: We were able to replicate the findings reported by Zhang et al. in an independently conducted blinded study. These results provide some evidence that including age of patient and these markers in a model may improve specificity, especially when CA125 levels are >= 35 units/mL. Influences of sample handling, subject characteristics, and other covariates on biomarker levels require further consideration in discovery and replication or validation studies.

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