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. 2010 Jun;19(6):1595-601.
doi: 10.1158/1055-9965.EPI-10-0068. Epub 2010 May 25.

Anti-MUC1 antibodies and ovarian cancer risk: prospective data from the Nurses' Health Studies

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Anti-MUC1 antibodies and ovarian cancer risk: prospective data from the Nurses' Health Studies

Simone P Pinheiro et al. Cancer Epidemiol Biomarkers Prev. 2010 Jun.

Abstract

Background: The surface epithelial glycoprotein MUC1 becomes overexpressed and hypoglycosylated in adenocarcinomas; similar changes occur during nonmalignant inflammatory events. Antibodies developed against tumor-like MUC1 in response to such events could be one way through which ovarian cancer risk factors operate.

Methods: We evaluated the association between anti-MUC1 antibodies and risk of ovarian cancer in a prospective nested case-control study in the Nurses' Health Studies. We used an ELISA to measure plasma anti-MUC1 antibodies in 117 ovarian cancer cases collected at least 3 years before diagnosis and 339 matched controls.

Results: In controls, younger women (P-trend = 0.03), those with a tubal ligation (P = 0.03), and those with fewer ovulatory cycles (P-trend = 0.04) had higher antibody levels. In cases, women with late-stage disease (P = 0.04) and those whose specimen was >11 years remote from diagnosis (P = 0.01) had higher antibody levels. Overall, increasing anti-MUC1 antibody levels were associated with a nonsignificant trend for lower risk for ovarian cancer, but there was highly significant heterogeneity by age (P-heterogeneity = 0.005). In women <64 years, the antibody level in quartiles 2 to 4 versus quartile 1 were associated with reduced risk (relative risk = 0.53; 95% confidence interval, 0.31-0.93; P-trend = 0.03), whereas in women > or = 64 years, the corresponding relative risk was 2.11 (95% confidence interval, 0.73-6.04); P-trend = 0.05).

Conclusion: Anti-MUC1 antibodies evaluated several years before diagnosis may be associated with lower risk of subsequent ovarian cancer in women <64 years old at assessment.

Impact: Key elements of an "immune model" to explain ovarian cancer risk factors are confirmed and should be evaluated in larger prospective studies.

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