bioRxivBioengineeringPreprint
Receptor-guided engineering of oncolytic vaccinia creates a synthetic support niche for off-the-shelf NK cell therapy
Reza RezaeiiD, Zhiyang Gan, Ngomu Akeem Akilimali, Jordan Reff, Meiyin Lin, Yansen Xiao, Kush Parikh, Darsh Vithlani, Bakir Valentic, Alexander A Shestov, Ugur Uslu, Taha Azad, Roddy S OConnor, Carl H. JuneiD, Neil C. SheppardiD
Abstract
Combining adoptive cell therapy with oncolytic viruses offers a means to provide localized support within solid tumors, yet viral chassis and therapeutic payloads are often selected independently of the biological state of the manufactured cell product. Here, we establish an engineering framework that uses the phenotypic and functional features of an adoptive cell product as design inputs for a complementary oncolytic niche. Using off-the-shelf expanded, frozen, and thawed (EFT) natural killer (NK) cells as a model system, we identified manufacturing-associated reductions in chemokine responsiveness, dependence on extrinsic cytokine support, and loss of sustained function at limiting effector-to-target ratios. In a head-to-head evaluation under human NK-cell antiviral pressure, oncolytic vaccinia virus (VV) retained replication and spread, whereas HSV-1 was rapidly restricted, establishing VV as a compatible viral chassis. Mapping endogenous receptor expression and applying sequential functional screening under increasingly limiting effector densities then prioritized a five-factor program comprising CXCL11, IL-15, IL-27, IL-2, and IL-1{beta} that supported NK-cell migration, survival, cytotoxicity, and metabolic fitness at effector-to-target ratios as low as 1:10. Consolidating these signals into a single viral chassis increased antitumor activity but revealed a systemic inflammatory liability associated with constitutive IL-1{beta} expression. We therefore placed the IL-2/IL-1{beta} module under chemically inducible control, retaining in vivo antitumor activity while limiting systemic toxicity. Together, these findings establish a framework in which the post-manufacturing state of an adoptive cell product guides viral chassis selection, payload prioritization, and programmable control of a complementary oncolytic support niche.
- organism: human
- assay: proteomics
- research focus: cell signaling & trafficking
- research focus: drug response / drug discovery
- approach: deep learning
- approach: statistical model
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