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Biology subjects

Klümper, N.

Publications and source records attributed to Klümper, N..

2 recordsLinked to original sources

Engineered endothelial cell grafts form functional anastomoses and enable recruitment of intravenously delivered human T cells in CAM tumor models

The development of cancer immunotherapies requires preclinical models that capture intravenous delivery, immune cell recruitment and intratumoral T cell activation. Conventional 3D in vitro systems lack perfused vascular networks, whereas mouse models are limited by throughput. The chick chorioallantoic membrane (CAM) assay enables rapid growth of vascularized tumors derived from human cancer cells in ovo, but its application to human T cell-based immunotherapy testing is constrained by CAM-derived vascularization and species-specific barriers between human immune cells and avian endothelium. Here, we establish an endothelial graft-enhanced CAM tumor model that incorporates an immortalized murine endothelial cell line capable of anastomosing with the chick vasculature. This generates a perfused and branched mammalian vascular interface within human tumor xenografts growing on the CAM. Human ICAM-1 expression on the grafted endothelial cells further enhances recruitment of intravenously delivered human T cells into CAM tumors. Using this platform, we demonstrate target-dependent intratumoral T cell activation by bispecific T cell engagers (TCEs) across tumor models, including evaluation of the clinically approved DLL3-targeting TCE tarlatamab in small cell lung cancer models.

bioengineering↗

Evolutionary algorithms accelerate de novo design of potent Nectin-4-specific cancer biologics

Recent advances in AI-based structural biology have made de novo protein binder design increasingly effective, yet performance remains highly target dependent. For instance, the cancer surface antigen Nectin-4, an immunoglobulin-like cell adhesion protein, proved particularly challenging for RFdiffusion-based minibinder generation, yielding substantially fewer high-quality candidates than related targets. To address this bottleneck, we integrated an evolutionary genetic algorithm (GA) with AI-driven design. GA selection with tunable stringency was coupled with diversification via partial diffusion or direct sequence editing, enabling efficient exploration of sequence-structure space and rapid enrichment of promising candidates. This AI-GA pipeline quickly produced large and diverse minibinder panels with very good in silico quality metrics and is compatible with inputs from multiple design algorithms. Pooled, large-scale experimental screening identified highly stable Nectin-4 minibinders with single-digit nanomolar down to subnanomolar affinities. Lead binders were further engineered into Nectin-4-specific flow cytometry detection reagents and potent bispecific T cell engagers, demonstrating functional activity beyond binding. Together, these results show that evolutionary refinement can unlock challenging targets and accelerate de novo protein design for next-generation cancer biologics.

bioengineering↗