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Optimizing Strategies to Overcome Kidney Xenograft Rejection

Optimizing Strategies to Overcome Kidney Xenograft Rejection
克服肾异种移植排斥的优化策略
批准号:
10371783
负责人:
Andrew B Adams
金额:
$80.14万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2016
资助国家:
美国
项目状态:
已结题
起止时间:
2016-07-01 至 2021-06-30

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中文摘要
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英文摘要
With over 100,000 patients now on the waiting list for a kidney transplant it is obvious that there is a critical shortage of available donor organs. Xenotransplantation represents a promising solution. While pigs are viewed as the optimal non-human source of organs, the potency of the human immune response to pig organs has prevented the clinical application of pig-to-human kidney transplantation. In this application we propose using cutting-edge genetic engineering approaches in combination with the use of the next generation of agents targeting critical T cell costimulatory pathways to reduce both the humoral and cellular immune response of nonhuman primates (NHP) undergoing kidney transplantation as a preclinical model to inform future human trials. The first and dominant obstacle is the robust humoral immune response of primates to pig kidneys. Despite the gradual introduction of a number of genetic modification to pig donors including knocking out α-1,3-gal, the presence of pre-formed, naturally occurring antibodies as well as the de novo formation of xenoantigen-specific antibodies continues to result in early rejection. Here, we will use the powerful CRISPR/Cas9 system of genome editing to eliminate novel carbohydrate xenoantigens generated by the β4GAL-NT2 enzyme , and interrogate the impact of this gene deletion (layered onto GAL-/- hCD55 transgenic animals) on the survival of pig kidneys transplanted into NHP recipients. Beyond the humoral barrier to xenotransplantation, the robust cellular immune response to pig organs poses a second challenge to the clinical application of xenotransplantation. The development of immunosuppressive strategies based on the blockade of critical costimulatory signals that are required for T cell activation offers a potential strategy to more effectively control the cellular immune response with less toxicity in comparison to standard immunosuppressive regimens. However, current strategies targeting the two dominant costimulatory pathways, CD28 and CD154 using CTLA4-Ig and anti-CD154 mAb have been associated with issues of efficacy and safety. Importantly, our work has demonstrated the superior efficacy and safety of novel “next-generation costimulation blockers” compared to current costimulation blockers in both mouse and NHP models. Thus we will next interrogate the ability of these next generation reagents, or domain antibodies, to better control xeno- reactive immunity and prolong kidney xenograft survival. Finally, we will employ additional strategies that are synergistic with the blockade of T cell costimulation to consolidate graft acceptance: 1) genome-editing strategies to delete SLA class I/ class II on donor tissue and thereby mitigate T cell responses elicited via direct presentation following xenotransplantation, and 2) blockade of the cell adhesion molecule VLA-4 and cytokine signaling through CD122 as adjunct immunotherapeutic strategies to control the xeno-reactive, costimulation- independent T cell response xenotransplantation. In sum, this project uses cutting-edge technology to develop novel strategies to reduce both the humoral and cellular immunity barriers and prolong xenotransplant survival.
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Advancing Transplantation Tolerance in Nonhuman Primates
  • 批准号:
    10622205
  • 项目类别:
  • 资助金额:
    $363.53万
  • 财政年份:
    2023
  • 负责人:
    Andrew B Adams
  • 依托单位:
Advancing Transplantation Tolerance in Nonhuman Primates
  • 批准号:
    10622206
  • 项目类别:
  • 资助金额:
    $13.46万
  • 财政年份:
    2023
  • 负责人:
    Andrew B Adams
  • 依托单位:
Promoting Kidney Transplantation Tolerance Through Novel Immunomodulation and Cellular Therapy
  • 批准号:
    10622210
  • 项目类别:
  • 资助金额:
    $93.59万
  • 财政年份:
    2023
  • 负责人:
    Andrew B Adams
  • 依托单位:
Costimulation Blockade-Based Strategies for Tolerance Induction
  • 批准号:
    10609611
  • 项目类别:
  • 资助金额:
    $66.52万
  • 财政年份:
    2022
  • 负责人:
    Andrew B Adams
  • 依托单位:
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Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis