Using surface-enhanced laser desorption/ionization-time of flight (SELDI-TOF), Li et al. [Clin Chem 48(8): 1296-1304, 2002] identified 3 serum biomarkers, BC1 (4.3 kDa), BC2 (8.1 kDa) and BC3 (8.9 kDa), whose combination significantly detects breast cancer patients from non-cancer controls. This work aimed to validate these biomarkers in an independent prospective study. We screened 89 serum samples including 49 breast cancers at pT1-4N0M0 (n = 23), pT1-4N1-3M0 (n = 17) or pT1-4N0-3M1 (n = 9) stages, 13 benign breast diseases and 27 healthy women. The BC2 biomarker significance was not recovered. However, we found 2 peaks that we named BC1a (4286 Da) and BC1b (4302 Da), that could correspond to Li's BC1 since they significantly decrease in breast cancers (p < 0.00007 and p < 0.0002, respectively). Similarly, BC3a (8919 Da) and BC3b (8961 Da) are significantly increased in breast cancers (p < 0.02 and p < 0.0002, respectively) and could correspond to the Li's BC3. For each biomarker we defined stringent (no errors) and flexible (less than 10% errors) cut-off values and tested the power of the combined BC1a/BC1b/BC3a/BC3b stringent and flexible profiles to discriminate breast cancers. They identified 33% and 45% cancers, respectively. Applied to the same series, Ca 15.3 test identified 22% patients. Interestingly, in association with the BC1a/BC1b/BC3a/BC3b profiles, Ca 15.3 improved the number of detected cancers indicating that it is an independent parameter. Collectively, our data partially validate those of Li's study and confirm that the BC1 and BC3 biomarkers are helpful for breast cancer diagnosis.