(621d) Inferring Tumor-Immune Interaction Networks Via Unbiased Secretome Profiling

Despite the variability of the disease, cancer cells exhibit a set of common traits. Tumor-escape from the cytotoxic action of the immune system is an emerging hallmark of cancer but the interaction between the tumor cell and the host is complex. We employ experimental procedures in limited length and time scales to elucidate the mechanisms by which tumors escape immunosurveillance, and predict the effect on physiology. On understanding the cross-talk between cancer and immune cells, more comprehensive targeted therapies may be developed. This study aims to compare the biochemical signals secreted in vitro by malignant cells to normal human cells. Two human mammary epithelial cancer cell lines, BT474 (HER2+/ER+) and SKBR3 (HER2+/ER-) and one normal human mammary epithelial cell line, 184A1 were investigated.  A proteomics workflow that includes two-dimensional gel electrophoreses, MALDI-TOF mass spectrometry and peptide mass finger-printing were used to analyze the secretome. Protein interaction networks and canonical pathways were extracted from the Ingenuity Knowledge Base to elucidate the role of tumor-derived secreted protein on immune cell function. The presence of tumor-derived exosomes was confirmed by SEM, and initial results suggest them as extra-cellular protein conveyers. Future studies will concentrate on inhibiting tumor cells from evading elimination. Proteomics provides a less biased approach to characterize the biochemical signals that malignant cells use to skew immunity and to better understand cell-to-cell communication in breast cancer.