There is an urgent need to identify relevant tumor markers showing high sensitivity and specificity for early diagnosis and prognosis of breast cancer. Protein microarrays have demonstrated to be cost-effective, high through-put and powerful tools for screening and identifying tumor markers with only minute samples. Autoantibodies directed against tumor-associated antigens (TAAs) were shown to be relevant tumor markers. However, due to the variability of immune response from one individual to another and depending on the type of cancer, detection of only one type of anti-TAA autoantibody is not sufficient to give a reliable and precise diagnosis. It is necessary to use a set of several TAAs for determining specific autoimmune profiles. Therefore, combining various TAAs on different surfaces could improve sensitivity and specificity for anti-TAA autoantibody detection. Herein a panel of 10 proteins, including well-known tumor-associated antigens (TAAs) and potential new biomarkers of breast cancer, were immobilized onto microstructured microarray under optimized conditions (spotting pH buffer, surface chemistry, blocking procedure), in order to determine an autoimmune signature of breast cancer. Sera from 29 breast cancer patients and 28 healthy donors were screened in sandwich immunoassays on the miniaturized system to detect the eventual presence of anti-TAAs autoantibodies. Results indicated that the detection level of each anti-TAA autoantibody in a given serum sample was strongly dependant on the surface chemistry. Combining five TAAs (p53, Hsp60, Hsp70, Her2-Fc, NY-ESO-1) on two different surface chemistries (NHS and APDMES) allowed the significant detection of more than 82% breast cancer sera.