Signatures of protein expression revealed by secretome analyses of cancer associated fibroblasts and melanoma cell lines

The imbalance of cellular homeostasis during oncogenesis together with the high heterogeneity of tumor-associated stromal cells have a marked effect on the repertoire of the proteins secreted by malignant cells (the secretome). Hence, the study of tumoral secretomes provides insights for understanding the cross-talk between cells within the tumor microenvironment as well as the key effectors for the establishment of the pre-metastatic niche in distant tumor sites. In this context, we performed a proteomic analysis of the secretomes derived from four cell lines: a paired set of fibroblasts - Hs 895. T, a cell line obtained from a lung node metastatic site from a patient who had melanoma and Hs 895.Sk, a skin fibroblast cell line (derived from the same patient); two malignant metastatic melanoma cell lines - A375, a malignant melanoma cell line from primary source and SH-4, a cell line derived from pleural effusion of a patient with metastatic melanoma. Clustering of expression profiles together with functional enrichment analysis resulted in patterns that mirrored each cell type. In addition, these patterns might be the result of cell-specific protein expression programs and reveal the emergence of trends in the co-expression of functionally related proteins in cellular melanoma models. Significance Melanoma is an aggressive skin cancer and a lethal melanocytic neoplasm with increasing annual number of cases, faster than any other solid tumor. In this context, the imbalance of cellular homeostasis during oncogenesis together with the high heterogeneity of tumor-associated stromal cells have a marked effect on the repertoire of the proteins secreted by malignant cells (the secretome). Therefore, the identification of protein expression patterns in malignant cells together with functional enrichment analysis provide insights into cell-specific protein expression programs and may reveal the emergence of trends in the co-expression of functionally related proteins regardless of cell type. Moreover, the identification of networks of protein interactions together with their expression profiles can be used for the targeted analysis of co-expressed proteins, allowing the identification of regulatory motifs in melanoma protein-protein interaction networks.