# Biochemistry of Leukemia Virus Core Binding Factor

> **NIH NIH R01** · UNIVERSITY OF PENNSYLVANIA · 2020 · $548,328

## Abstract

Summary
The goal of this proposal is to understand how innate immune signaling contributes to the formation of
hematopoietic stem cells (HSCs) in the embryo. Understanding how HSCs form, and in particular the signaling
pathways that are involved in embryonic HSC formation will be essential for producing and expanding HSCs
from other cell sources ex vivo, which is a major goal in regenerative medicine. All adult HSCs are derived
from hemogenic endothelial cells in the embryo. Hemogenic endothelium is located in several anatomic sites
including the yolk sac and the major arteries, but only hemogenic endothelium in the major arteries produces
HSCs. We and others discovered that multiple innate immune and inflammatory signaling pathways regulate
HSC formation in the major arteries of mouse and zebrafish embryos. This proposal focuses on the
contribution of toll-like receptor (TLR) signaling to embryonic HSC formation. We will determine which arms of
toll-like receptor signaling pathways, and which toll-like receptors regulate HSC formation, and at which steps
in the process they act. We will also examine whether toll-like receptor signaling during HSC formation in the
embryo introduces long-term alterations to the function, transcriptome, and epigenome of adult HSCs.

## Key facts

- **NIH application ID:** 9969531
- **Project number:** 5R01HL091724-27
- **Recipient organization:** UNIVERSITY OF PENNSYLVANIA
- **Principal Investigator:** NANCY SPECK
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $548,328
- **Award type:** 5
- **Project period:** 1993-08-10 → 2021-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9969531

## Citation

> US National Institutes of Health, RePORTER application 9969531, Biochemistry of Leukemia Virus Core Binding Factor (5R01HL091724-27). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/9969531. Licensed CC0.

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