Sign in
Cancer BiologyACS Applied Materials & Interfaces
Peer-reviewed journal article

Bola-amphiphilic dendrimer empowers imatinib to target metastatic ovarian cancer stem cells via beta-catenin-HRP2 signaling axis

Zeyu ShiiD, Margarita ArtemenkoiD, Weiyu Yu, Ming ZhangiD, Canhui Yi, Peng CheniD, Shuting LiniD, Zhancun Bian, Baoping LianiD, Fanzhen Meng, Jiaxuan CheniD, Tom RousseliD, Ying LiiD, Karen K. L. ChaniD, Philip P.C. IpiD, Hung-Cheng Lai, Sally K. Y. ToiD, Xiaoxuan LiuiD, Ling PengiD, Alice S.T. WongiD

Abstract

Ovarian cancer is the leading cause of death among all gynecological malignancies, and drug resistance renders the current chemotherapy agents ineffective for patients with advanced metastatic tumors. We report an effective treatment strategy for targeting metastatic ovarian cancer involving a nanoformulation (Bola/IM) - bola-amphiphilic dendrimer (Bola)-encapsulated imatinib (IM) - to target the critical mediator of ovarian cancer stem cells (CSCs) CD117 (c-Kit). Bola/IM offered significantly more effective targeting of CSCs compared to IM alone, through a novel and tumor-specific {beta}-catenin/HRP2 axis, allowing potent inhibition of cancer cell survival, stemness and metastasis in metastatic and drug-resistant ovarian cancer cells. Promising results were also obtained in clinically relevant patient-derived ascites and organoids, alongside high tumor-oriented accumulation and favorable pharmacokinetic properties in mouse models. Furthermore, Bola/IM displayed synergistic anticancer activity when combined with the first-line chemotherapeutic drug cisplatin in patient-derived xenograft mouse models, without any adverse effects. Our findings support the use of Bola/IM as a nanoformulation to empower IM, providing targeted and potent treatment of metastatic ovarian cancer. Our study thus represents a significant advancement towards addressing the unmet medical need for improved therapies targeting this challenging disease.

PDFDOI

02 /Specification & Classification

Click any tag to browse matching papers

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISWang '26Fang '23Sharrow '23Muralikrish '22Pires '25Raja '22
64% semantic matchCancer Biology
Yong Wang, Jie Pi, Yuzi Zhao+1 more·Journal of Drug Delivery Science and Technology·Jan 2, 2026