This dataset is analyses of identified proteins between MCPyV-negative (MCC13, MCC26, and UISO) and -positive (MKL1, MKL2, MS1, and WaGa) MCC cell line.

Abstract: Proteomics have become an important tool in discovery and understanding pathological processes at the cellular level. Comparing the proteome of normal cells with diseased (malignant and other pathological conditions) or pathogen-infected cells allows identification of proteins and processes involved in the disease and recognition of possible biomarkers and targets for treatment. Merkel cell carcinoma (MCC) is an aggressive type of cutaneous cancer that affects mostly elderly people. Approximately 80% of the tumors are caused by Merkel cell polyomavirus (MCPyV), while the remaining are caused by UV-induced mutations in the DNA of the cell. To understand the underlying mechanisms of virus-independent and virus-dependent MCC, we compared the proteome of MCPyV-negative (MCC13, MCC26, and UISO) and MCPyV-positive (MKL-1, MKL-2, MS-1, and WaGa) MCC cell lines. In total 4898 proteins were identified, of which 3312 were differentially expressed between the virus-negative and virus-positive cell lines. The viral oncoproteins large T- and small t-antigens were detected in the MCPyV-positive cells, but also in exosomes derived from these cells. Our proteomic data may identify unique biomarkers for MCPyV-negative and –positive MCCs and may allow the design of specific therapeutic strategies against the two types of MCC with a different origin. Moreover, our results suggest that exosomal transmission of MCPyV oncoproteins to recipient cells in the tumor microenvironment contributes to tumorigenesis. Data are available via ProteomeXchange with identifier PXD012909.