Background: Serum protein profiling seems promising for early detection of breast cancer. However, the approach is also criticized, partly because of difficulties in validating discriminatory proteins. This study's aim is to validate three proteins previously reported to be discriminative between breast cancer cases and healthy controls. These proteins had been identified as a fragment of inter-alpha trypsin inhibitor H4 (4.3 kDa), C-terminal-truncated form of C3a des arginine anaphylatoxin (8.1 kDa) and C3a des arginine anaphylatoxin (8.9 kDa).
Methods: Serum protein profiles of 48 breast cancer patients and 48 healthy controls were analyzed with surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS). Differences in protein intensity between breast cancer cases and controls were measured with the Mann-Whitney U test and adjusted for confounding in a multivariate logistic regression model.
Results: Four peaks, with mass-to-charge ratio (m/z) 4276, 4292, 8129 and 8941, were found that were assumed to represent the previously reported proteins. M/z 4276 and 4292 were statistically significantly decreased in breast cancer cases compared to healthy controls (p < 0.001). M/z 8941 was decreased in breast cancer cases (p < 0.001) and m/z 8129 was not related with breast cancer (p = 0.87). Adjustment for sample preparation day, sample storage duration and age did not substantially alter results.
Conclusion: M/z 4276 and 4292 both represented the previously reported 4.3 kDa protein and were both decreased in breast cancer patients, which is in accordance with the results of most previous studies. M/z 8129 was in contrast with previous studies not related with breast cancer. Remarkably, m/z 8941 was decreased in breast cancer cases whereas in previous studies it was increased. Differences in patient populations and pre-analytical sample handling could have contributed to discrepancies. Further research is needed before we can conclude on the relevance of these proteins as breast cancer biomarkers.