# Signaling Mechanisms in Lens Development

> **NIH NIH R01** · COLUMBIA UNIVERSITY HEALTH SCIENCES · 2021 · $392,850

## Abstract

PROJECT SUMMARY
Defective lens development is a major cause of congenital eye diseases, because the human lens is the
culmination of elaborate cell proliferation, differentiation and morphogenesis, requiring precise regulation by
signaling pathways. A molecular understanding of lens development could potentially lead to new ways of
diagnosing and treating congenital eye diseases originating from defective lens genesis. We have previously
demonstrated that Shp2 protein tyrosine phosphatase and Crk adaptor proteins are important for transmitting
FGF signaling in lens morphogenesis. In this application, we will investigate the molecular mechanism of Shp2
and Crk functions. Using conditional mutant mice and cell culture models, we will also identify Abl kinases as
novel negative regulators of FGF signaling. Furthermore, we will test the hypothesis that FGF signaling,
mediated by Crk, regulates the separation of the lens from the surface ectoderm, which underlies the human
congenital disease, Peter’s anomaly. As a major signaling pathway, perturbation in FGF signaling can cause
not only congenital diseases, but also metabolic syndromes and cancer. Therefore, study of FGF signaling has
far reaching implications for both human health and vision research.

## Key facts

- **NIH application ID:** 10129387
- **Project number:** 5R01EY017061-16
- **Recipient organization:** COLUMBIA UNIVERSITY HEALTH SCIENCES
- **Principal Investigator:** Xin Zhang
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $392,850
- **Award type:** 5
- **Project period:** 2006-01-01 → 2025-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10129387

## Citation

> US National Institutes of Health, RePORTER application 10129387, Signaling Mechanisms in Lens Development (5R01EY017061-16). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10129387. Licensed CC0.

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