Prognostic Impact of MCPyV and TIL Subtyping in Merkel Cell Carcinoma: Evidence from a Large European Cohort of 95 Patients

Merkel cell carcinoma is a rare (∼ 2000 cases/year in the USA) but aggressive neuroendocrine neoplasm of the skin. In 2008, the Merkel cell polyomavirus (MCPyV) was found to be clonally integrated in approximately 80% of Merkel cell carcinomas. The remaining 20% have large numbers of UV-associated mutations. Importantly, both the UV-induced neoantigens in virus-negative Merkel cell carcinoma and the Merkel cell polyomavirus oncogenes that are required for virus-positive tumor growth are highly immunogenic. Indeed, antigen-specific T cells detected in patients are frequently “dysfunctional/exhausted,” and the inhibitory ligand PD-L1 is often expressed by Merkel cell carcinoma cells. These data led to point our attention on the quantity and the quality of the immune response in Merkel cell carcinoma. Here, we found CD8+ lymphocytes are the only singly evaluated lymphocyte subclass that strongly influenced overall survival and disease-specific survival in Merkel cell carcinoma. In addition, we highlighted as Merkel cell polyomavirus is a strong prognostic factor and as it prompts a host immune response involving various lymphocyte subclasses (CD3, CD8, FoxP3, and PD-L1 positive) in MCC. For this reason, we proposed a novel eye-based “immunoscore” model, obtained by tumor infiltrating lymphocytes subtyping (CD3, CD8, FoxP3, and PD-L1) that could provide additional prognostic information in Merkel cell carcinoma.     

Physical health indexes and mortality in a 70 to 75 year old Italian population living at home: A 6 year follow-up study

The aim of this 6 year follow-up study is to analyze the role of physical health indicators in predicting mortality. The data used were obtained from a multidimensional survey on a wide population of 70 to 75 year old subjects living at home. Baseline self-reported physical health information regarding the use of medical health services, diagnoses, and medications was collected. Multiple logistic regression analysis was used to define the multivariate association with mortality of the baseline presence of the diseases or of medications used while adjusting for sex and IADL score. The number of diseases and medications related to mortality, and the medical services use index were entered together in the same statistical model to assess which of these factors had a preeminent role in predicting mortality. Indicators such as medications and medical services use were more important mortality predictors than the diagnosis itself. A significant interaction of the variables with gender was also found.