This study aimed to integrate cancer pharmacogenomics with structure-based modeling to identify natural compounds capable of selectively targeting AKT1 or AKT2.<h4>Methods</h4>Public cancer genomics datasets from TCGA and the Kaplan-Meier Plotter were analyzed to characterize mutation patterns, copy number alterations, and survival associations of AKT1 and AKT2 across malignancies. This evidence concerns the gene AKT2 and cancer.