The driving force behind oncoproteomics is to identify biomarker signatures associated with a particular malignancy. Here, we have for the first time used large-scale recombinant scFv antibody microarrays in an attempt to classify metastatic breast cancer versus healthy controls, based on differential protein expression profiling of whole serum samples. Using this multiplexed and miniaturised assay set-up providing pM range sensitivities, breast cancer could be classified with a specificity and sensitivity of 85% based on 129 serum analytes. However, by adopting a condensed 11 analyte biomarker signature, composed of nine non-redundant serum proteins, we were able to distinguish cancer versus healthy serum proteomes with a 95% sensitivity and specificity, respectively. When a subgroup of patients, not receiving anti-inflammatory drugs, was analysed, a novel eight analyte biomarker signature with a further improved predictive power was indicated. In a longer perspective, antibody microarray analysis could provide a tool for the development of improved diagnostics and intensified biomarker discovery for breast cancer patients.