Serum antibodies against p53 in relation to cancer risk and prognosis in breast cancer: a population-based epidemiological study

Abstract

To perform an epidemiological evaluation of the predictive value of p53 autoantibodies in breast cancer, we measured antibodies against p53 in serum samples from 165 breast cancer patients in comparison with serum samples from 330 healthy controls, selected from the same population as the cases and matched for age, sex and specimen storage time. Median age of patients was 51 years (range 25–64 years). Presence of serum p53 autoantibodies was analysed by enzyme-linked immunosorbent assay (ELISA) and confirmed by Western blotting. The lower ELISA reactivities were similar for cases and controls, but presence of high-level reactivity was more common among cases than among controls [odds ratio (OR) 9.03, 95% confidence interval (CI) 2.40–50.43]. Presence of Western blot-detected p53 autoantibodies had a very similar association (OR 10.8, CI 3.0–59.4). Among the cases, we also studied whether there was any correlation between level of anti-p53 antibodies and stage of the disease or survival. There was no significant correlation between presence of antibodies and stage of the disease. There was a significant negative correlation between presence of p53 antibodies and survival ( P = 0.003). A stepwise multivariate Cox regression analysis showed that T-stage, age and presence of anti-p53 antibodies were significant independent prognostic variables, with a dose-dependent negative effect on survival for all three variables. We conclude that presence of anti-p53 antibodies are of significance both for the risk of having breast cancer and the risk of dying from breast cancer. 1999 Cancer Research Campaign

Translocation of an Intracellular Antigen to the Surface of Medullary Breast Cancer Cells Early in Apoptosis Allows for an Antigen-Driven Antibody Response Elicited by Tumor-Infiltrating B Cells

“…In breast cancer, particular interest in such correlations has focused on anti-53 autoantibodies, where some studies observed a correlation between poor prognosis and increased levels of anti-53 autoantibodies (70,71), although these results could not always be confirmed by others (72). It may, therefore, seem surprising that the favorable prognosis of MCB correlates with anti-actin autoantibodies.…”

“…Autoantibodies observed in some tumors may be due to large tumor masses and necrosis exposing a large amount of autoantigen to the immune system. Alternatively, as suggested for p53, in which mutations have been found to be associated with more aggressive tumors and poorer prognosis of breast cancer, the mutated p53 tends to have a much longer half-life than the wild-type p53, leading to accumulation of the protein and anti-p53 Ab production (70,71). In contrast, the anti-actin Abs observed in MCB are probably a result of increased tumor cell apoptosis; thus, these Abs serve as a marker of a beneficial biologic process.…”

Serum p53 antibodies: predictors of survival in small-cell lung cancer?

“…These results have shown varying levels of positivity for p53-Abs in all cancer types but with less than 0.5% of healthy controls being positive. The presence of p53-Abs have been associated with a worse prognosis in breast (Peyrat et al, 1995;Lenner et al, 1999), head and neck (Bourhis et al, 1996) and colon cancer (Houbiers et al, 1995;Kressner et al, 1998). In NSCLC early reports of p53 mutation suggested a variable relationship to survival (McLaren et al, 1992;Quinlan et al, 1992;Lee et al, 1995).…”

Toward “Serolomics”: Papillomavirus Serology Is Taking a Technologic Lead in High-Throughput Multiplexed Antibody Analysis

“…Analysis of a broad spectrum of autoantibodies is increasingly used in predictive diagnostics of autoimmune diseases (3 ), and autoantibodies against oncogene products are being studied in predictive oncology (4 ). The most interesting medical application, however, would be to rapidly assay the spectrum of microbiological agents to which a person has been exposed because past infections can be highly predictive of the risk of future diseases.…”