Title

AI-powered chimeric receptors to overcome therapeutic resistance in myeloma

Research Area

Immunology, Cell Engineering

Project Summary

Multiple myeloma remains a challenging malignancy to treat, as most patients eventually relapse following CAR-T cell therapy targeting B-cell maturation antigen (BCMA), often due to antigen escape mechanisms and reduced antigen expression. To address these limitations, we propose a novel approach that integrates artificial intelligence (AI)-guided protein design with genome editing to develop physiologically regulated, multi-specific AI-powered Chimeric Receptors (AI-CRs) capable of simultaneously targeting BCMA, transmembrane activator and CAML interactor (TACI), and G protein-coupled receptor family C group 5 member D (GPRC5D). These targets are clinically validated but prone to downregulation under therapeutic pressure. Building on our prior development of a trimeric APRIL-based CAR (TriPRIL) currently under clinical evaluation, and our recent success in generating high-affinity, compact de novo binders using AI-based design tools, we aim to overcome antigen escape by engineering multi-targeting chimeric receptors that are precisely integrated into the endogenous T cell receptor (TCR) loci.

In Aim 1, we will identify and characterize high-affinity, low-immunogenicity binders against BCMA, TACI, and GPRC5D, and select lead candidates for functional testing. In Aim 2, these binders will be incorporated into standardized CAR backbones to assess individual functionality, and the most promising candidates will be further developed into multi-specific AI-CRs integrated into the TRAC and TRBC loci via CRISPR/Cas9. In Aim 3, we will evaluate these AI-CR-T cells in vitro and in vivo, using both xenograft and syngeneic multiple myeloma models, to assess efficacy, persistence, and safety in clinically relevant settings. Importantly, this project is closely aligned with the CRC’s translational mission, and we will work with the central platform Z02 to advance the most promising AI-CR configuration toward first-in-human application. By combining next-generation protein design with precise receptor integration and multi-antigen targeting, this project aims to establish a novel and durable immunotherapy platform that can overcome current resistance mechanisms in multiple myeloma and improve long-term patient outcomes.
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