Breast cancer is worldwide the second most common type of cancer after lung cancer. The plasma proteome profiling may have a higher chance to identify protein changes between plasma samples such as normal and breast cancer tissues. Breast cancer cell lines have long been used by researches as model system for identifying protein biomarkers. A comparison of this set of proteins which change in plasma with previously published finding from proteomic analysis of human breast cancer cell lines may identify with a higher confidence a subset of candidate protein biomarker. In this study, we analyzed liquid chromatography (LC) coupled tandem mass spectrometry (MS/MS) proteomics dataset from plasma samples of 40 healthy women and 40 breast cancer women. Using two-sample tstatistics and permutation procedure, we identified 254 statistically significant differentially expressed proteins, among which 208 are over-expressed and 46 are under-expressed in breast cancer plasma. We validated this result against previously published proteomic results of human breast cancer cell lines and signaling pathways to derive 26 candidate protein biomarkers in a panel. Using the Ingenuity Pathways Knowledge Base, we observed that the 26 "activated" plasma proteins were present in several cancer canonical pathways, including acute phase response signaling, complement system, coagulation system, PPAR signaling, and glutathione metabolism, and match well with previously reported studies. Additional gene ontology analysis of the 26 proteins also showed that cellular metabolic process and response to external stimulus (especially proteolysis and acute inflammatory response) were enriched functional annotations found in the breast cancer plasma samples.