# Molecular Mechanisms Regulating PIK3CA-induced Venous Malformations

> **NIH NIH R01** · ALBANY MEDICAL COLLEGE · 2024 · $365,146

## Abstract

Summary
PI3’-Kinase (PI3K) signaling is critical for proper angiogenesis, the development of new blood
vessels. However, aberrant PI3K signaling is associated with a wide range of vascular
malformations (VMs), including venous malformations which can arise from somatic activating
mutations in PIK3CA. VMs are failures in proper endothelial cell development and
differentiation giving rise to dysfunctional blood vessels that leave affected patients with
significant morbidity and often disfigurement. Our long-term goal is to better understand the
molecular etiology of vascular malformations with the hope of contributing novel approaches to
the treatment of these conditions non-surgically. We have developed in vitro and in vivo models
of PIK3CA-driven VMs and find that the mTORC1 axis may be a critical component of improper
vascular morphogenesis. Our central hypothesis is that the mTORC1 axis is being regulated
through a novel mechanism; the induction of the mTORC1 regulating protein RHEB. This
proposal seeks to determine the role of RHEB in driving malformations arising from PIK3CA
mutations and reveal molecular insights into the mechanisms by which RHEB/mTORC1 axis
promotes the development of vascular malformations.

## Key facts

- **NIH application ID:** 10857352
- **Project number:** 5R01HL151679-04
- **Recipient organization:** ALBANY MEDICAL COLLEGE
- **Principal Investigator:** KEVIN M PUMIGLIA
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $365,146
- **Award type:** 5
- **Project period:** 2021-06-10 → 2026-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10857352

## Citation

> US National Institutes of Health, RePORTER application 10857352, Molecular Mechanisms Regulating PIK3CA-induced Venous Malformations (5R01HL151679-04). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10857352. Licensed CC0.

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