Document Type
Article
Version Deposited
Published Version
Publication Date
4-1-2024
Publication Title
SLAS Technology
DOI
10.1016/j.slast.2024.100121
Abstract
A major aim in the field of synthetic biology is developing tools capable of responding to user-defined inputs by activating therapeutically relevant cellular functions. Gene transcription and regulation in response to external stimuli are some of the most powerful and versatile of these cellular functions being explored. Motivated by the success of chimeric antigen receptor (CAR) T-cell therapies, transmembrane receptor-based platforms have been embraced for their ability to sense extracellular ligands and to subsequently activate intracellular signal transduction. The integration of transmembrane receptors with transcriptional activation platforms has not yet achieved its full potential. Transient expression of plasmid DNA is often used to explore gene regulation platforms in vitro. However, applications capable of targeting therapeutically relevant endogenous or stably integrated genes are more clinically relevant. Gene regulation may allow for engineered cells to traffic into tissues of interest and secrete functional proteins into the extracellular space or to differentiate into functional cells. Transmembrane receptors that regulate transcription have the potential to revolutionize cell therapies in a myriad of applications, including cancer treatment and regenerative medicine. In this review, we will examine current engineering approaches to control transcription in mammalian cells with an emphasis on systems that can be selectively activated in response to extracellular signals. We will also speculate on the potential therapeutic applications of these technologies and examine promising approaches to expand their capabilities and tighten the control of gene regulation in cellular therapies.
Recommended Citation
Recktenwald, Matthias et al.. Engineering transcriptional regulation for cell-based therapies. SLAS Technology, Volume 29, Issue 2, 100121. doi: 10.1016/j.slast.2024.100121
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Comments
© 2024 The Author(s). Published by Elsevier Inc. on behalf of Society for Laboratory Automation and Screening