Toward improved models of human cancer

Abstract

Human cancer is a complex and heterogeneous collection of diseases that kills more than 18 million people every year worldwide. Despite advances in detection, diagnosis, and treatments for cancers, new strategies are needed to combat deadly cancers. Models of human cancer continue to evolve for preclinical research and have culminated in patient-derived systems that better represent the diversity and complexity of cancer. Still, no model is perfect. This Perspective attempts to address ways that we can improve the clinical translatability of models used for cancer research, from the point of view of researchers who mainly conduct cancer studies in vivo.

FIG. 1.

Schematic illustrating multiple platforms available for patient-derived models of cancer. Ex vivo and in vitro models (left side) include organ or tissue slice cultures, three-dimensional (3D) organoids, and two-dimensional (2D) monolayer cultures. In vivo models (right side) include patient-derived xenografts (PDX) in mouse, zebrafish, and chicken egg chorioallantoic membrane (CAM) hosts. Information from these model systems can be interchanged to increase our understanding of human cancer biology, to perform drug screening or testing, and, in some cases, for functional precision oncology to inform patient care.