Protein-based markers that classify tumor subtypes and predict therapeutic response would be clinically useful in guiding patient treatment. We investigated the LC-MS/MS-identified protein biosignatures in 39 baseline breast cancer specimens including 28 HER2-positive and 11 triple-negative (TNBC) tumors. Twenty proteins were found to correctly classify all HER2 positive and 7 of the 11 TNBC tumors. Among them, galectin-3-binding protein and ALDH1A1 were found preferentially elevated in TNBC, whereas CK19, transferrin, transketolase, and thymosin 4 and 10 were elevated in HER2-positive cancers. In addition, several proteins such as enolase, vimentin, peroxiredoxin 5, Hsp 70, periostin precursor, RhoA, cathepsin D preproprotein, and annexin 1 were found to be associated with the tumor responses to treatment within each subtype. The MS-based proteomic findings appear promising in guiding tumor classification and predicting response. When sufficiently validated, some of these candidate protein markers could have great potential in improving breast cancer treatment. 1. Introduction Chemotherapy has long been used to treat all types of cancer. Although survival benefits from adjuvant systemic chemotherapy in breast cancer have been thoroughly documented [1], success is not uniform with many still dying after the initial chemotherapy. The unpredictable tumor response to chemotherapy in any given patient and the significant toxicity manifested in all demand a better strategy for delivering cancer therapy. In selective subtypes of breast cancer, therapies targeting specific signal transduction and/or metabolic pathways have been successful. For example, Herceptin for HER2/neu positive breast cancer [2, 3] and poly(ADP ribose) polymerase (PARP) inhibitors for triple-negative breast cancer with defective DNA-repair [4, 5] are among the recent successes of targeted therapy. The success of target therapy has led to an explosion of interest in developing tailored systemic therapy. Breast cancer is a heterogeneous disease molecularly, histologically, and clinically. Clinical outcomes from the same treatment vary widely even among patients with tumors of identical stage and histology. Breast cancers developed from an accumulation of genetic alterations may partially explain the differences observed including tumor responses to anticancer agents [6]. Recently gene expression analysis has identified five subtypes of breast cancer which overlaps with clinical tumor classification according to the expression of three biomarkers, estrogen receptor (ER), progesterone
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