Age-related immune changes have been described in cell subset frequencies and functions, as well as levels of serum cytokines and other factors. In many cases, these changes are accompanied by increasing heterogeneity with age. The frequency of most cancers also increases with age, and the immune system has a prominent role in controlling cancer. We therefore hypothesize that cancer incidence and/or progression is related to age-related immune deviation. In this project, we will test this hypothesis using a broad, highly- multiparameter CyTOF assay of immune phenotype and function. In our first specific aim, we will compare therapy-nave melanoma patients to matched healthy controls, to determine the degree of age-related immune deviation associated with this cancer in the absence of therapy. In our second specific aim, we will examine the degree of immune deviation of melanoma and lung cancer patients enrolled in selected immunotherapy trials. We will compare the degree of immune deviation of advanced/refractory melanoma patients to that of the therapy nave patients of Aim 1. In our third specific aim, we will compare the immune deviation of therapy responsive versus non-responsive patients, in the settings of lung cancer and melanoma, for two different immunotherapy regimens. We will also determine the degree to which predictive factors from Aim 2 are stable across tumor type and across immunotherapy regimens. We will look at early post-therapy samples to determine the stability of predictive markers and to discover dynamic markers that could be early predictors of response. We will analyze a total of 100 patients from two tumor types (melanoma and lung cancer) and two immunotherapies (anti-PD1 and anti-PD1+anti-CD137). We will use state-of-the-art analytical tools, including SPADE and Citrus, to mine for differences between groups. The data obtained from this study will lay a foundation for better understanding of the relationship of age-related immune deviation and cancer. It could also improve the implementation of currently available therapies, by determining which patients are good candidates for immunotherapy generally, and possibly allow better decisions of which immunotherapies will be efficacious in which patients. Moreover, this project could provide insight into the cellular mechanisms that underlie anti-tumor immunity and/or tumor-mediated immune suppression.