title: 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.
authors.affiliation: Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, China.|Henan Key Laboratory of Tumor Epidemiology, College of Public Health, Zhengzhou University, Zhengzhou, China.
authors.forename: J
authors.initials: J
authors.lastname: Xia
authors.affiliation: Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, China.|Henan Key Laboratory of Tumor Epidemiology, College of Public Health, Zhengzhou University, Zhengzhou, China.
authors.forename: J
authors.initials: J
authors.lastname: Shi
authors.affiliation: Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, China.|Henan Key Laboratory of Tumor Epidemiology, College of Public Health, Zhengzhou University, Zhengzhou, China.
authors.forename: P
authors.initials: P
authors.lastname: Wang
authors.affiliation: Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, China.|Henan Key Laboratory of Tumor Epidemiology, College of Public Health, Zhengzhou University, Zhengzhou, China.
authors.forename: C
authors.initials: C
authors.lastname: Song
authors.affiliation: Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, China.|Henan Key Laboratory of Tumor Epidemiology, College of Public Health, Zhengzhou University, Zhengzhou, China.
authors.forename: K
authors.initials: K
authors.lastname: Wang
authors.affiliation: Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, China.|Henan Key Laboratory of Tumor Epidemiology, College of Public Health, Zhengzhou University, Zhengzhou, China.|Henan Province Academy of Medical and Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, China.
authors.forename: J
authors.initials: J
authors.lastname: Zhang
authors.affiliation: Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, China.|Henan Key Laboratory of Tumor Epidemiology, College of Public Health, Zhengzhou University, Zhengzhou, China.
authors.forename: H
authors.initials: H
authors.lastname: Ye
mesh_terms: D000818:Animals; D014408:Biomarkers, Tumor / Q000378:metabolism*; D001943:Breast Neoplasms / Q000175:diagnosis* / Q000276:immunology; D056744:Cyclin B1 / Q000276:immunology; D004797:Enzyme-Linked Immunosorbent Assay; D005260:Female; D006801:Humans; D008327:Mammography; D018396:Mucin-1 / Q000276:immunology; D011237:Predictive Value of Tests; D040081:Protein Array Analysis; D018719:Erb-b2 Receptor Tyrosine Kinases / Q000276:immunology; D012015:Reference Standards; D012680:Sensitivity and Specificity; D016159:Tumor Suppressor Protein p53 / Q000276:immunology
chemical_list: D014408:Biomarkers, Tumor; D056744:Cyclin B1; D018396:Mucin-1; D018719:Erb-b2 Receptor Tyrosine Kinases; D016159:Tumor Suppressor Protein p53; C534699:CCNB1 protein, human; C060192:MUC1 protein, human; C508053:ERBB2 protein, human