Maximizing response to intratumoral immunotherapy in mice by tuning local retention
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s41467-021-27390-6.pdf
Description
Published version
Size
3.61 MB
Format
Adobe PDF
Checksum (MD5)
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Author(s)
Momin, Noor
Palmeri, Joseph R
Lutz, Emi A
Jailkhani, Noor
Mak, Howard
Tabet, Anthony
Chinn, Magnolia M
Kang, Byong H
Spanoudaki, Virginia
Hynes, Richard O
Date Issued
2022
Journal
Nature Communications
Publisher
Springer Science and Business Media LLC
Citation
Momin, Noor, Palmeri, Joseph R, Lutz, Emi A, Jailkhani, Noor, Mak, Howard et al. 2022. "Maximizing response to intratumoral immunotherapy in mice by tuning local retention." Nature Communications, 13 (1).
Version
Final published version
Abstract
AbstractDirect injection of therapies into tumors has emerged as an administration route capable of achieving high local drug exposure and strong anti-tumor response. A diverse array of immune agonists ranging in size and target are under development as local immunotherapies. However, due to the relatively recent adoption of intratumoral administration, the pharmacokinetics of locally-injected biologics remains poorly defined, limiting rational design of tumor-localized immunotherapies. Here we define a pharmacokinetic framework for biologics injected intratumorally that can predict tumor exposure and effectiveness. We find empirically and computationally that extending the tumor exposure of locally-injected interleukin-2 by increasing molecular size and/or improving matrix-targeting affinity improves therapeutic efficacy in mice. By tracking the distribution of intratumorally-injected proteins using positron emission tomography, we observe size-dependent enhancement in tumor exposure occurs by slowing the rate of diffusive escape from the tumor and by increasing partitioning to an apparent viscous region of the tumor. In elucidating how molecular weight and matrix binding interplay to determine tumor exposure, our model can aid in the design of intratumoral therapies to exert maximal therapeutic effect.
MIT Department
Massachusetts Institute of Technology. Department of Biology
Terms of Use
Creative Commons Attribution 4.0 International license
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DOI of Published Version
https://doi.org/10.1038/S41467-021-27390-6
