Targeted Strategy for Selective Identification of Secreted Breast Tumor Proteins in Plasma Using Mouse Xenograft Models

Early detection of breast cancer is associated with improved patient survival. While early disease is commonly identified by patient self-examination and breast mammography, interpretation of these findings are highly subjective and often require significant disease burden to achieve sensitivity. Cancer screening utilizing blood-based assays, such as measurement of prostate-specific antigen (PSA) abundance for prostate cancer, has proven to be a minimally invasive method that aids in detecting early disease. The generation of a blood-based assay for the detection of early disease in breast cancer would enable more facile disease diagnosis and thus expedite patient care. The discovery of proteins actively shed or secreted by tumor cells into blood plasma by global proteomic analyses has proven analytically challenging, due mainly to the large dynamic range of protein abundances in blood. Common methods to enrich for tumor-specific proteins include depletion of abundant proteins from plasma samples, such as albumin and immunoglobulins. Furthermore, strategies are needed to detect blood-based candidates derived specifically from tumor cell populations to provide high-confidence candidates for further validation efforts. To this end, we have developed a method combining global proteomic analyses of plasma collected from a mouse xenograft model of primary human breast cancer with post-data acquisition filtering of species-specific peptide search results. Primary xenograft models enable analyses of human tumor tissue in non-native biological backgrounds. Therefore, species-specific protein and gene sequences can be exploited in discovery efforts to selectively identify tumor cell-specific characteristics. Preliminary studies of plasma analyzed from xenograft-bearing mice have resulted in the identification of human-specific peptides corresponding to proteins previously described as being secreted from breast tissue and associated with breast cancer pathogenesis. Application of this strategy to proteomic analyses from a cohort of xenograft mice bearing HER2+ and triple negative breast cancer tissues will be presented.