Tumor-on-a-chip: a new generation of tumor models for precision medicine

The treatment of cancer has benefited during the last decades from the implementation of in vitro and in vivo models to monitor the progression of the disease and its response to therapeutic drugs. However, these models are obsolete and display serious technological, economical, and ethical issues. A new generation of highly predictive, simple, and affordable tumor models are needed, in particular, if they are intended to be adopted by the clinics and healthcare market. Organ-on-chip technology has emerged as a promising alternative to develop highly reliable models of tumors due to their unprecedented capabilities to replicate in a microfluidic chip the cellular, structural, and rheological properties of organs and tissues [1]. Several organs-on-chip models of tumors, or tumor-on-a-chip, have been developed during the last years. These models have described several events occurring during tumor dissemination, such as angiogenesis, intra/extravasation, or organ specificity, contributing to assess the mechanistic determinants of the disease. Importantly, tumor-on-a-chip models can be combined with cells from patients to develop a personalized model of a patient´s tumor, and study its response to a specific therapy [2]. In this work, we show the main fields of application of tumor-on-a-chip devices showing how they can be used to investigate the mechano-chemical determinants of tumor growth and invasion. As an example, we use an organ-on-a-chip approach to analyze how A549 lung epithelial cells embedded within 3D collagen matrices use invading protrusions and mechanical forces to invade a blood vessel-like microfluidic channel. Altogether, it is expected that tumor-on-a-chip models may provide novel and valuable insights into the mechanism at work of cancer progression, boosting its clinical applicability in the near future.

Acknowledgements

This work is supported by the European Union Framework Programme for Research and Innovation Horizon 2020 under grant agreement nº 668983 — FoReCaST.