Tumour-Associated Autoantibodies as Diagnostic Biomarkers for Breast Cancer: A Systematic Review and Meta-Analysis

Abstract

Tumour-associated autoantibodies may be promising biomarkers that could facilitate breast cancer (BC) diagnosis and improve patient outcomes. This review aims to identify the tumour-associated autoantibodies with the greatest diagnostic potential. Systematic searches were conducted using PubMed and Web of Science. The most studied tumour-associated autoantibody was included in a meta-analysis, and its clinical value was determined using Fagan's nomogram. The analysis included 84 studies regarding tumour-associated autoantibodies with the diagnostic value. Anti-p53 antibody was the most frequently studied autoantibody, followed by autoantibodies against MUC1, HER2 and cyclin B1. Although individual tumour-associated autoantibodies showed low diagnostic sensitivity, combinations of autoantibodies offered relatively high sensitivity. Enzyme-linked immunosorbent assay (ELISA) was the most common detection method, and nucleic acid programmable protein microarrays appeared preferable to common protein microarrays. As the most commonly studied autoantibody, anti-p53 antibody was included in a meta-analysis. When it had been detected using ELISA and cut-off values were defined as the mean +2 or 3 standard deviations, the summary area under the receiver operating characteristic curve for the presence of BC was 0.78. Fagan's nomogram showed post-test probabilities of 32% and 6% for positive and negative results, respectively. Mammography might be supplemented by the use of tumour-associated autoantibodies as biomarkers for BC diagnosis in younger women with increased risks of BC. Even though several studies have investigated the diagnostic use of tumour-associated autoantibodies as biomarkers for BC detection, a high-quality prospective study is needed to validate their diagnostic value in practice.