# Identification of progenitor CD4 T cells that support response to chronic antigen

> **NIH NIH R21** · WASHINGTON UNIVERSITY · 2022 · $196,875

## Abstract

Abstract
Durable immune response by both CD4 and CD8 T cells is required for the control of chronic infection or
tumors. In the past few years, multiple independent studies have identified a subset of progenitor-like or stem-
like TCF-1+ PD-1+ CD8 T cells in both chronic viral infections and tumors. These progenitor CD8 T cells
continue generating new effector CD8 T cells to support long-term CD8 T cell responses to persisting antigens
(Ags). They are also capable of eliciting robust effector responses by the immune checkpoint blockade
targeting the PD-1 to PD-L1 interaction. However, it remains unknown how CD4 T cell responses to persistent
Ag are maintained, or whether a specialized subset of progenitor-like CD4 T cells equivalent to TCF-1+
progenitor CD8 T cells exists to support the durability of CD4 T cell response or respond to the PD-1 blockade.
We have found that the transcription factor BCL6 is essential for the durable CD4 T cell effector response to
chronic LCMV infection, implying that an analogous progenitor CD4 T cells are present in the face of chronic
antigen stimulation. We propose to identify such a CD4 T cell population and conduct the initial
characterization of the unique CD4 T cell subset.

## Key facts

- **NIH application ID:** 10449403
- **Project number:** 5R21AI161040-02
- **Recipient organization:** WASHINGTON UNIVERSITY
- **Principal Investigator:** Takeshi Egawa
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $196,875
- **Award type:** 5
- **Project period:** 2021-07-12 → 2023-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10449403

## Citation

> US National Institutes of Health, RePORTER application 10449403, Identification of progenitor CD4 T cells that support response to chronic antigen (5R21AI161040-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10449403. Licensed CC0.

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