Going with the Flow: Modeling the Tumor Microenvironment Using Microfluidic Technology

SIMPLE SUMMARY: The clinical success of cancer immunotherapy targeting immune checkpoints (e.g., PD-1, CTLA-4) has ushered in a new era of cancer therapeutics aimed at promoting antitumor immunity in hopes of offering durable clinical responses for patients with advanced, metastatic cancer. This success has also reinvigorated interest in developing tumor model systems that recapitulate key features of antitumor immune responses to complement existing in vivo tumor models. Patient-derived tumor models have emerged in recent years to facilitate study of tumor–immune dynamics. Microfluidic technology has enabled development of microphysiologic systems (MPSs) for the evaluation of the tumor microenvironment, which have shown early promise in studying tumor–immune dynamics. Further development of microfluidic-based “tumor-on-a-chip” MPSs to study tumor–immune interactions may overcome several key challenges currently facing tumor immunology. ABSTRACT: Recent advances in cancer immunotherapy have led a paradigm shift in the treatment of multiple malignancies with renewed focus on the host immune system and tumor–immune dynamics. However, intrinsic and acquired resistance to immunotherapy limits patient benefits and wider application. Investigations into the mechanisms of response and resistance to immunotherapy have demonstrated key tumor-intrinsic and tumor-extrinsic factors. Studying complex interactions with multiple cell types is necessary to understand the mechanisms of response and resistance to cancer therapies. The lack of model systems that faithfully recapitulate key features of the tumor microenvironment (TME) remains a challenge for cancer researchers. Here, we review recent advances in TME models focusing on the use of microfluidic technology to study and model the TME, including the application of microfluidic technologies to study tumor–immune dynamics and response to cancer therapeutics. We also discuss the limitations of current systems and suggest future directions to utilize this technology to its highest potential.