Protein-based identification of quantitative trait loci associated with malignant transformation in two HER2+ cellular models of breast cancer

A proteomic workflow was used to identify proteins in two HER2 positive tumorigenic cell lines (BT474 and SKBR3) that were differentially expressed relative to a normal human mammary epithelial cell line (184A1). A total of 64 (BT474-184A1) and 69 (SKBR3-184A1) proteins were uniquely identified that were differentially expressed by at least 1.5-fold. Pathway inference tools were used to interpret these proteins in terms of functionally enriched pathways in the tumor cell lines. We observed "protein ubiquitination" and "apoptosis signaling" pathways were both enriched in the two breast cancer models while "IGF signaling" and "cell motility" pathways were enriched in BT474 and "amino acid metabolism" were enriched in the SKBR3 cell line.While "protein ubiquitination" and "apoptosis signaling" pathways were common to both the cell lines, the observed patterns of protein expression suggest that the evasion of apoptosis in each tumorigenic cell line occurs via different mechanisms. Evidently, apoptosis is regulated in BT474 via down regulation of Bid and in SKBR3 via up regulation of Calpain-11 as compared to 184A1.Cancer cells exhibit a number of common traits that differentiate themselves from normal cells, including sustained proliferative signaling, resisting cell death, and evading growth suppressors [1]. Acquiring one of the hallmarks of cancer is associated with activating/deactivating particular genes, called oncogenes/tumor suppressors. The focus on identifying specific oncogenes or tumor suppressors that drive malignant transformation embodies the genomic era in cancer research [2]. However, a series of recent developments challenge this oncogene paradigm. Next generation sequencing efforts have revealed that, instead of a small number of genetic alteration associated with malignant transformation [3], genomic landscapes are extensively modified in solid tumors [4,5]. These massive rearrangements suggest that there might not be single driver mutations, but that