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 analyzedPD-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-L2expression is more closely linked toTh1/IFNGexpression and PD-1 and CD8 signaling thanPD-L1. In contrast, mutational load was not correlated with aTh1/IFNGgene signature in any tumor type.PD-L1,PD-L2,PD-1,CYTexpression, and mutational density are all positive prognostic features in melanoma, and conditional inference modeling revealedPD-1/CYTexpression (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.