Issue 4, 2025

A cRGD-modified liposome for targeted delivery of artesunate to inhibit angiogenesis in endometriosis

Abstract

Currently, hormonal therapy for endometriosis faces challenges in achieving a balance between treatment and preserving the chance of pregnancy. Therefore, the development of non-hormonal therapy holds significant clinical importance. Angiogenesis is a hallmark of endometriosis, and anti-angiogenic therapies targeting the hypoxia-inducible factor-1α (HIF-1α) pathway are considered potential approaches for endometriosis. However, angiogenesis is also involved in numerous physiological processes, including pregnancy, and systemic anti-angiogenesis may lead to severe adverse effects. To address this, a cRGD-modified liposome nanodrug (cRGD-LP-ART) is synthesized, which enhances drug efficacy while reducing adverse reactions. Artesunate (ART), a non-hormonal drug used to treat malaria, has shown anti-angiogenic effects beyond its original indications in various benign and malignant diseases. With cRGD modification, cRGD-LP-ART can target ectopic lesions and inhibit local angiogenesis by suppressing the HIF-1α/vascular endothelial growth factor (VEGF) pathway. Furthermore, cRGD-LP-ART exhibits better therapeutic effects than free ART, without affecting ovarian function or causing atrophy of the eutopic endometrium, making it a promising new option for non-hormonal therapy of endometriosis. As a combination of liposomes and a clinically approved drug, cRGD-LP-ART holds great potential and clinical prospects for the treatment of endometriosis.

Graphical abstract: A cRGD-modified liposome for targeted delivery of artesunate to inhibit angiogenesis in endometriosis

Supplementary files

Article information

Article type
Paper
Submitted
11 Nov 2024
Accepted
03 Jan 2025
First published
20 Jan 2025

Biomater. Sci., 2025,13, 1045-1058

A cRGD-modified liposome for targeted delivery of artesunate to inhibit angiogenesis in endometriosis

J. Ma, Z. Liao, J. Li, X. Li, H. Guo, Q. Zhong, J. Huang, X. Shuai and S. Chen, Biomater. Sci., 2025, 13, 1045 DOI: 10.1039/D4BM01506A

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