Brain-on-a-chip is new testing ground for cancer treatments
Brain-on-a-chip is new testing ground for cancer treatments lead image
Brain and central nervous system cancers are devastating and deadly, but despite the demand for cures, developing and testing new treatments is challenging. The brain sits behind the blood-brain barrier, a built-in defense that blocks many anti-cancer drugs. Even after crossing this barrier, a prospective drug must be selective enough to destroy cancerous cells without damaging healthy cells. If a medication is specially crafted and meets these demands, testing it is difficult because of the complexity of the human brain.
To tackle the last challenge, Marino et al. developed a brain-on-a-chip that replicates the environment and allows for in-depth, non-invasive testing for promising cancer treatments. .
“We designed our model by exploiting an innovative real-3D fabrication approach, named two-photon polymerization, which is characterized by submicrometric resolution and excellent reproducibility,” said author Gianni Ciofani. “We obtained biocompatible scaffolds with the desired architecture that can be colonized by cells, generated the 3D tumor model, the surrounding tumor niche, and the associated microvascular system.”
The authors put their model to work, testing the efficacy of anti-cancer drug Nutlin-3a. When they dispersed the drug, it crossed the blood-brain barrier and selectively targeted tumor cells, leaving little damage to healthy brain cells.
“This multifunctional system allows screening multiple important features, such as the amount of drug delivered to the brain, the efficacy of the drug against tumor cells after blood-brain barrier crossing, and side effects on normal healthy brain cells,” said Ciofani.
The brain-on-a-chip, fitted with human cells and realistic features, will aid the development of the next generation of brain cancer treatments.
Source: “Magnetic self-assembly of 3D multicellular microscaffolds: A biomimetic brain tumor-on-a-chip for drug delivery and selectivity testing,” by Attilio Marino, Matteo Battaglini, Alessio Carmignani, Francesca Pignatelli, Daniele De Pasquale, Omar Tricinci, and Gianni Ciofani, APL Bioengineering (2023). The article can be accessed at https://doi.org/10.1063/5.0155037 .
