# Mucosal T cell memory to pathogens

> **NIH NIH R37** · UNIVERSITY OF MINNESOTA · 2024 · $571,485

## Abstract

Project Summary
T cell immunity may be exploited through vaccination, immunomodulating therapies, and
engineered adoptive cell therapies to immunize against or control infections and cancer. However
repeated or prolonged stimulation can result in T cell dysfunction and senescence which impairs
protective immunity or allows disease progression. Establishing numerically robust, durable, and
functional T cell immunity and preventing or reversing T cell exhaustion remain substantial goals
in immunology that have significant clinical ramifications. Our preliminary data demonstrates that
repeated stimulation, even when punctuated by periods of rest, can result in senescence.
However, we also show that this fate can be avoided, allowing indefinite boosting across multiple
mouse lifetimes, while preserving function and durability. Additional preliminary data indicates
that T cells can adapt to become inured to exhaustion. The goals of this proposal are to determine
the underlying mechanisms that permit T cells to undergo indefinite clonal expansion while
avoiding functional exhaustion or proliferative senescence. Successful execution of the proposal
will inform our understanding of the regulation of immunological memory, vaccine development,
and immune therapies for chronic diseases.
.

## Key facts

- **NIH application ID:** 10880987
- **Project number:** 2R37AI084913-15
- **Recipient organization:** UNIVERSITY OF MINNESOTA
- **Principal Investigator:** DAVID MASOPUST
- **Activity code:** R37 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $571,485
- **Award type:** 2
- **Project period:** 2010-02-01 → 2029-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10880987

## Citation

> US National Institutes of Health, RePORTER application 10880987, Mucosal T cell memory to pathogens (2R37AI084913-15). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10880987. Licensed CC0.

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