In recent years, utilizing the immune system to eliminate tumors has become an increasingly popular treatment option for numerous types of cancer. One example of this is the development of immune checkpoint inhibitors. Immune checkpoint inhibitors are monoclonal antibody drugs that block the interaction of T cell surface receptors, such as PD-1 and CTLA-4, with their respective ligands to alleviate immune suppression. The advent of immune checkpoint inhibitors has drastically improved overall survival in patients with metastatic melanoma. However, only a minority of patients achieve complete response to therapy, and adverse effects are common. Identifying features associated with response could allow for better treatment stratification of patients and could aid in the development of therapies to improve responsiveness. The overall goal of this work is to identify features that could be used to predict or increase responsiveness to immune checkpoint inhibition. Using proteomics to investigate metastatic melanoma patient tumors, we identified pathways that could potentially decrease anti-tumor immunity in metastatic melanoma and, in turn, contribute to disease progression. Additionally, features of innate immunity were found to be associated with responsiveness to immune checkpoint inhibition. Our results indicate that signatures of innate immunity could be used to predict patients most likely to benefit from immune checkpoint inhibition. Furthermore, amplifying the innate immune response could serve as means by which to increase responsiveness to therapy.