PO.IM01.06 · 免疫学

Structure-guided protein engineering and humanization of GPC1-targeted nanobody CAR T cells for treating pancreatic cancer

海报缩略图:Structure-guided protein engineering and humanization of GPC1-targeted nanobody CAR T cells for treating pancreatic cancer
编号 4269 展板 5 时间 4/21 09:00–12:00 区域 Section 7 主讲 Hsi En Tsao, PhD
分会场 CAR T Cell Functional Enhancement
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作者与单位

Hsi En Tsao, Mitchell Ho

National Cancer Institute, Bethesda, MD

摘要 Abstract

Glypican-1 (GPC1) is a heparan sulfate proteoglycan that is overexpressed in pancreatic ductal adenocarcinoma (PDAC). We previously developed GPC1 CARs using the dromedary VHH nanobody D4 and the mouse monoclonal IgG antibody HM2, which recognize a membrane-distal epitope and a membrane-proximal epitope, respectively. Here, we integrate structural modeling with CAR functional data and animal experiments to define how epitope position and CAR geometry jointly determine GPC1 CAR efficacy. Modeling of CAR ectodomains incorporating CD8 or IgG4 hinges and CD8 or CD28 transmembrane (TM) domains indicated that only specific combinations yield an intermembrane spacing comparable to that of the TCR-pMHC immune synapse for a given epitope. These geometric predictions aligned with functional data in which D4-IgG4H-CD28TM CAR T cells rapidly regressed tumor bioluminescent in a T3M4 intraperitoneal PDAC model. Together, these results support a model in which epitope spatial location on GPC1 and CAR hinge/TM architecture are key design parameters for GPC1-targeting CAR T cells. To facilitate clinical development of D4 CAR T cells, humanization of the VHH D4 is highly desirable, although humanization of nanobodies such as VHHs is not well established. In addition to the CDR grafting to the nearest germline framework as we described previously for humanization of rabbit and mouse antibodies, we used AI-predicted structural models from multiple platforms to compare both the spatial geometry and sequence similarity of predicted D4 framework and CDR regions with available antibody and nanobody structures. Humanized constructs with the highest humanness scores, geometry, and similarity scores were back-mutated to preserve critical residues in the nanobody framework sequences and were then evaluated for GPC1 binding affinity and cell-surface binding. Using this AI-assisted, structure-guided strategy, we aim to generate clinically suitable humanized VHH nanobody scaffolds for GPC1 CAR T therapy and other nanobody-based clinical applications.
利益披露 Disclosure
H. Tsao, None.

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