# Use of allogeneic pMHCII-based 5MCAR-CTLs to eliminate alloreactive lymphocytes in transplant

> **NIH NIH R21** · UNIVERSITY OF CALIFORNIA, SAN DIEGO · 2024 · $209,750

## Abstract

PROJECT SUMMARY
The immune system is a significant barrier to successful clinical organ transplantation, requiring life-long
immunosuppression to prevent allograft rejection. Current immunosuppressive strategies rely primarily on broad
pharmacologic inhibition of lymphocyte function. This approach is limited by susceptibility to breakthrough
immune responses causing acute rejection episodes, with simultaneous unwanted impairment of protective
immune responses against infection and tumors. Thus, new approaches for specific and durable allograft-
specific immunosuppression are critically needed. We propose to utilize a pMHCII-based allogeneic 5-module
chimeric antigen receptor-cytotoxic T cell (5MCAR-CTL) system to target and eliminate alloreactive CD4+ T cells.
These investigations represent a conceptual advance in proposing to utilize cutting-edge cellular engineering
with 5MCAR technology to develop a novel approach aimed at specific and durable immunosuppression in
transplantation. Successful completion of the proposed experiments will generate tools and data to support
refinement and development of this clinically-translatable cell engineering approach.

## Key facts

- **NIH application ID:** 10890546
- **Project number:** 1R21AI183310-01
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN DIEGO
- **Principal Investigator:** Michael S Kuhns
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $209,750
- **Award type:** 1
- **Project period:** 2024-03-15 → 2026-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10890546

## Citation

> US National Institutes of Health, RePORTER application 10890546, Use of allogeneic pMHCII-based 5MCAR-CTLs to eliminate alloreactive lymphocytes in transplant (1R21AI183310-01). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10890546. Licensed CC0.

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