Label-Free Quantitative Proteomic Screening of Candidate Plasma Biomarkers for the Prognosis of Breast Cancer with Different Lymph Node Statuses

PurposeLymph node status is a crucial predictor for the overall survival of invasive breast cancer. However, lymph node involvement is only detected in about half of HER2-positive patients. Since patients with lymph node involvement has less favorable prognosis and higher risk of recurrence, it is important to develop plasma protein biomarkers for distinguishing lymph node metastasis. Experimental designA label-free quantitative proteomic strategy to construct plasma proteomes of ten patients with small size HER2-positive breast cancer (five patients with lymph node metastasis versus five patients without lymph node metastasis) is applied. ResultsA total of 388 proteins are identified, of which 33 proteins are differentially expressed. Statistical analyses suggested the present strategy is low cost and highly efficient in initial screening of plasma biomarkers. In silico analyses using various bioinformatics databases show that these altered proteins are highly associated with breast disease, cancer pathway, lymph node morphology, metastasis, complement pathway, and immune regulation. Conclusions and clinical relevanceThe present dataset provides a list of candidate biomarkers that could be used for early differentiation diagnosis and prognosis of breast cancer with lymph node metastasis.