Novel prognostic biomarkers are imperatively needed to help direct treatment decisions by typing subgroups of node-negative breast cancer patients. The current study has used a proteomic approach of SELDI-TOF-MS screening to identify differentially cytosolic expressed proteins with a prognostic impact in 30 node-negative breast cancer patients with no relapse versus 30 patients with metastatic relapse. The data analysis took into account 73 peaks, among which 2 proved, by means of univariate Cox regression, to have a good cumulative prognostic-informative power. Repeated random sampling (n = 500) was performed to ensure the reliability of the peaks. Optimized thresholds were then computed to use both peaks as risk factors and, adding them to the St. Gallen ones, improve the prognostic classification of node-negative breast cancer patients. Identification of ubiquitin and ferritin light chain (FLC), corresponding to the two peaks of interest, was obtained using ProteinChip LDI-Qq-TOF-MS. Differential expression of the two proteins was further confirmed by Western blotting analyses and immunohistochemistry. SELDI-TOF-MS protein profiling clearly showed that a high level of cytosolic ubiquitin and/or a low level of FLC were associated with a good prognosis in breast cancer.