A Systems Framework for Quantifying Programmability and Persistence Across Mammalian Cell Types

Authors

Chauhan, V., Chen, M., Sridharan, A. T., Pan, L.

Abstract

Cellular therapies, toxicity screening, and regenerative medicine depend on selecting mammalian cell types with optimal lifespan, persistence post-transplant, immunogenicity, and chemical resilience. This review synthesizes data from over 50 immune, parenchymal, stem, and emerging engineered cell populations - including gamma-delta T cells, iNKT cells, CAR-macrophages, and hypoimmune iPSC derivatives - drawing from in vivo lifespan studies (including 14C birth-dating and deuterium labeling), engraftment dynamics, immune rejection risk, and stress sensitivity profiles. We introduce a Programmability and Persistence Score (PPS; 0-20) that integrates these features into a unified metric, complemented by Pareto frontier analysis to visualize multi-objective trade-offs. High-PPS cell types (e.g., HLA-matched HSCs, hypoimmune iPSCs, chondrocytes) are suited for long-term regenerative applications, while low-PPS sentinels (e.g., neutrophils, enterocytes) serve acute assays. We discuss mathematical extensions including multi-criteria decision analysis, fuzzy membership functions, and Bayesian frameworks that address limitations of linear additive scoring. Together, these integrated profiles support cell selection for gene editing, organ-on-chip systems, in vivo cell programming, and immunotherapy, bridging cell biology with translational engineering.

Preprint server: bioRxiv
The authors list and abstract were imported from bioRxiv on 31 Mar 2026.

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