High-resolution tracking of T cell differentiation to predict and control alloreactive disease
- Institution
- Stanford University, CA
- Principal investigator
- Cameron Scott Bader
- Funding
- $131K
- Duration
- 2025–2027
Moonbase score
Still being scored
Abstract
Allogeneic hematopoietic stem cell transplantation (allo-HSCT) remains the only curative therapy for many malignant and non-malignant diseases. Despite advances in allo-HSCT, graft-versus-host disease (GVHD) remains a significant cause of morbidity and mortality in patients. GVHD is marked by the activation of donor alloreactive T cells which target and damage healthy recipient tissues. This project’s central hypothesis is that donor alloreactive T cells differentiate into immunoregulatory or pro-inflammatory effectors depending on the environment into which they are transplanted and that identifying these alloreactive cells by high-resolution sequencing can predict clinical GVHD. My long-term career goal is to use high-resolution bioinformatics to dissect the distinct differentiation pathways which lead to tolerance versus alloreactivity after adoptive cell therapy. Consequently, this proposal has three main aims. During the mentored K99 phase of this award, we first hypothesize that alloreactive T cell subsets develop their phenotype after allo-HSCT and that the detection of anti-human T cells can predict GVHD after allo-HSCT. Second, during the independent R00 phase, we posit that these and other T cell subsets arise from naïve T cells in response to allo-antigen and we will investigate the mechanisms which drive this differentiation in both human and mouse. Third, we propose that specific T cells which mediate alloreactive GVHD responses will be identifiable after allo-HSCT and experiments in Aim 3 will utilize high-resolution sequencing techniques to identify and track alloreactive T cells in both xenogeneic and murine models of GVHD. These scientific aims will be explored alongside additional training in human experimental methods, advanced bioinformatics and machine learning, career development, and clinical translation with the support of a highly experienced, multidisciplinary mentoring team. The overall objective of this proposal will be to develop the ability to track alloreactive T cells in patients to predict disease onset prior to the emergence of deleterious symptoms. These novel results will be directly applicable to the field of allo-HSCT as well as other contexts involving alloreactive T cell responses including solid organ transplantation, chimeric antigen receptor T cell therapy, and other adoptive T cell therapies.
LOADING MOONBASE SCORE
Questions for Stanford University
Answered by the team behind this research.
No questions yet. Sign in to ask the first one
Related grants
Same institution, same topic, scored first.
- NIH · Stanford University60
Dissecting neocortical field potential dynamics using optical voltage imaging in genetically targeted cell-types
Mark J Schnitzer · $604K · 2021–2027
- NIH · Stanford University48
Clinical Translation of Ultrasonic Ketamine Uncaging for Non-Opioid Therapy of Chronic Pain
Raag D Airan · $1.3M · 2019–2026
- NIH · Stanford University46
Innovating next generation technologies to define mechanisms of neurodegenerative disease and devise therapeutic strategies
Aaron D. Gitler · $1.1M · 2024–2032