JOURNAL ARTICLE
Target Reprogramming the 3′UTR of Tumor‐Suppressor Genes by a siRNA Composite Nanoparticle for Glioblastoma Therapy.
Published In: Advanced Functional Materials, 2024, v. 34, n. 30. P. 1 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Gu, Bin; Zeng, Xianyan; Gong, Ming; Li, Xiangyu; Yu, Qian; Tan, Zhengzong; Lou, Zheqi; Jiang, Tinghui; Che, Yu; Ao, Yiran; Zhu, Yong 3 of 3
Abstract
Glioblastoma multiforme (GBM) is the most aggressive and common adult brain tumor. Current therapies primarily involve surgical resection, followed by chemotherapy and radiotherapy. However, the low survival rate due to high toxicity, side effects, and poor targeting necessitates novel treatments. Post‐transcriptional regulation pathways, particularly the regulation of alternative polyadenylation based on the mRNA 3′UTR, play a critical role in cell growth and development and the progression of tumors. Targeting tumor cells and reprogramming the 3′UTR of tumor suppressor genes to achieve post‐transcriptional regulation is expected to be a new channel for GBM therapy. Herein, a novel siRNA delivery system is developed based on mesoporous silica nanoparticles: siRNA composite nanoparticles (siRNA CNP). Encapsulation in MSNs overcomes siRNA degradation and cellular entry issues, while lipid bilayer coating improves biocompatibility and stability. Surface‐modified nucleic acid aptamer SL1 (Apt‐SL1) significantly enhances GBM targeting, offering therapeutic potential. The findings show that siRNA CNP effectively silences the promoter CFIm25 of distal poly(A) in tumor cells, inducing gene reprogramming, inhibiting tumor growth, and promoting apoptosis in nude mice. The siRNA CNP demonstrates a significant effect in reprogramming tumor suppressor genes and treating GBM. It offers a novel and promising therapeutic avenue for GBM. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Advanced Functional Materials. 2024/07, Vol. 34, Issue 30, p1
- Document Type:Article
- Subject Area:Health and Medicine
- Publication Date:2024
- ISSN:1616-301X
- DOI:10.1002/adfm.202400837
- Accession Number:178592394
- Copyright Statement:Copyright of Advanced Functional Materials is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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