# iSYNAPSE:  Early signals of the transition from immune quiescence to activation in the liver allograft microenvironment and in the circulation

> **NIH NIH R34** · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · 2023 · $270,673

## Abstract

iSYNAPSE Summary
Children with liver transplants with excellent graft function according to clinical, biochemical, and histological
criteria enjoy a harmonious equilibrium between the host immune system and the allograft. Reducing
immunosuppression is challenge that, for some but not all, precipitates alloimmune activation that can result in
graft injury. Previously, we have shown that objective quantification of inflammatory load using next generation
pathology techniques can meaningfully differentiate allografts that appear normal by standard histological
evaluation. The density of various inflammatory cells essentially maps allografts onto an alloreactivity spectrum
that extends from quiescent to activated. Among inflammatory metrics, the density of immunologic synapses,
defined as a lymphocyte proximal to and interacting with an antigen-presenting cell based on positional,
morphometric, and molecular parameters, was the best predictor of those who could withstand the challenge of
immunosuppression dose reduction to complete cessation. These data suggest that, within an apparently
quiescent allograft, the intrahepatic microenvironment, comprised of immune cells and their cell-to-cell
interactions, determines the likelihood of maintaining quiescence or succumbing to activation when IS is
reduced. Our primary hypothesis is that the number and nature of interactions between intrahepatic immune
cells at quiescence constitutes the basis of liver allograft immunogenicity and is the key determinant of
outcome, when quiescence is challenged.
To test this hypothesis, iSYNAPSE proposes the following specific aims: 1) Conduct a multicenter, single-arm
trial for stable children with healthy liver allografts on calcineurin inhibitor monotherapy. Immunosuppression
will be reduced by 50%, from twice to once daily dosing. This intervention offers direct prospect of benefit by
reducing medication exposure and simplifying administration. 2) Determine how intrahepatic immune cell
networks regulate liver allograft immunogenicity at baseline and following immunosuppression reduction. Using
next generation pathology and single cell transcriptomics, we will characterize the phenotype and the
transcriptome of the lymphocytes and the antigen-presenting cells participating in immunological synapses.
The iterative analyses of these two data streams will fully inventory the immune cell subsets that comprise the
liver microenvironment and elucidate the impact of cell-to-cell interactions on the maintenance or loss of
quiescence when challenged. 3) Ascertain whether the nature of intrahepatic cell-to-cell interactions predict
changes in donor-specific humoral and cellular responses in the circulation.
Liver transplantation provides a unique context to safely study the host and graft respond when the equilibrium
achieved by immunosuppression is challenged. Understanding these basic mechanisms of how allograft
quiescence is maintained or lost when stressed is essential to na...

## Key facts

- **NIH application ID:** 10622220
- **Project number:** 1R34AI174988-01
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
- **Principal Investigator:** Sandy Feng
- **Activity code:** R34 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $270,673
- **Award type:** 1
- **Project period:** 2023-08-02 → 2024-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10622220

## Citation

> US National Institutes of Health, RePORTER application 10622220, iSYNAPSE:  Early signals of the transition from immune quiescence to activation in the liver allograft microenvironment and in the circulation (1R34AI174988-01). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10622220. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*