Enhancing the transduction efficiency of lentiviral vectors in CAR-T cell therapy through an optimization workflow

TL;DR

This paper introduces a step-by-step method to improve lentiviral transduction efficiency in CAR-T cell therapy, significantly boosting performance in lab settings.

Contribution

A modular optimization workflow that systematically enhances lentiviral transduction efficiency for CAR-T cell engineering.

Findings

Transduction efficiency of an underperforming anti-FITC-CAR increased from ~1% to ~40–50% using the workflow.

A well-performing HER2 CAR improved from ~76% to ~88% transduction efficiency with the same workflow.

Primary PBMCs achieved ~10% transduction efficiency, showing the workflow's potential for further refinement.

Abstract

Efficient lentiviral (LV) transduction is a cornerstone of CAR-T manufacturing, yet performance is often construct-specific and highly sensitive to production and delivery parameters. We developed a stepwise optimization workflow using an underperforming anti-FITC-CAR in Jurkat E6-1 cells and validated generalizability with a well-performing HER2 CAR (pHR_SFFv_4D5-WT-Highest), followed by translational testing in primary PBMCs. The strategy sequentially tuned LV concentration, brief agitation during transduction, packaging system, DNA input balance, and addition of a transduction enhancer, with outcomes quantified by flow cytometry (tdTomato and HA or c-myc tags). Concentrated supernatants and a short 2-h shaking step improved signal definition and yield; incorporating an alternative packaging plasmid and a modest DNA rebalance further increased performance. With a low-dose enhancer, Jurkat transduction with the anti-FITC-CAR arose from ∼1% to ∼40–50% tdTomato+HA+ cells (∼5–50-fold improvement, 96 h). The comparator HER2 construct—already efficient—also benefited, increasing from ∼76 to ∼88%, indicating the workflow’s utility even for high-baseline vectors. In PBMCs, the same conditions achieved ∼10% transduction at 96 h, consistent with the greater refractoriness of primary T cells and highlighting avenues for future gains via complementary steps. Overall, this modular, low-complexity optimization provides a reproducible template to rescue underperforming constructs and incrementally boost robust vectors, supporting more reliable lab-scale CAR-T engineering and offering a tractable starting point for primary T-cell protocols.

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