Programmed cell death protein-1 (PD-1)/programmed death ligand-1 (PD-L1) checkpoint blockade has led to remarkable and durable objective responses in a number of different tumor types. A better understanding of factors associated with the PD-1/PD-L axis expression is desirable, as it informs their potential role as prognostic and predictive biomarkers and may suggest rational treatment combinations. In the current study, we analyzed PD-L1, PD-L2, PD-1, and cytolytic activity (CYT) expression, as well as mutational density from melanoma and eight other solid tumor types using The Cancer Genome Atlas database. We found that in some tumor types, PD-L2 expression is more closely linked to Th1/IFNG expression and PD-1 and CD8 signaling than PD-L1 In contrast, mutational load was not correlated with a Th1/IFNG gene signature in any tumor type. PD-L1, PD-L2, PD-1, CYT expression, and mutational density are all positive prognostic features in melanoma, and conditional inference modeling revealed PD-1/CYT expression (i.e., an inflamed tumor microenvironment) as the most impactful feature, followed by mutational density. This study elucidates the highly interdependent nature of these parameters, and also indicates that future biomarkers for anti-PD-1/PD-L1 will benefit from tumor-type-specific, integrated, mRNA, protein, and genomic approaches.