Dendritic Poly(<scp>l</scp>-lysine)-Based Nanoparticle Loading with siDNMT1 to Alleviate Basal Cell Carcinoma Progression by Inhibiting Methylation of AXIN2

Basal cell carcinoma (BCC) is a highly invasive and metastatic non-melanoma skin tumor. Traditional treatments, such as surgery, radiation, and chemotherapy, often result in severe side effects. Recent advances in RNA interference (RNAi) have highlighted its potential in targeting cancer-causing genes. To address the complex pathology of BCC, we developed a multifunctional gene delivery system using benzylthio-modified dendritic polylysine nanoparticles loaded with siDNMT1 (siDNMT1@PDPs). This system exhibits excellent dispersibility, with over 85% of particles measuring between 50 and 80 nm, and high stability, with a zeta potential of +57.10 mV. This design enables efficient penetration into tumor cells and controlled release of siDNMT1 in the tumor microenvironment (TME), thereby improving therapeutic outcomes. Our results demonstrate that siDNMT1@PDPs significantly inhibit tumor progression and metastasis in BCC by reducing AXIN2 promoter methylation, thereby increasing AXIN2 expression. Compared to existing treatments, siDNMT1@PDPs exhibit superior biocompatibility, both <i>in vitro</i> and <i>in vivo</i>, and provide a more targeted and effective therapeutic approach. These findings suggest that siDNMT1@PDPs represent a promising advancement in RNAi-based therapies for BCC, offering potential clinical benefits over current treatment modalities.

Authors

Institutions

Publication Details

Journal
ACS Applied Materials & Interfaces
Published
2025-05-08
DOI
https://doi.org/10.1021/acsami.5c00802
Primary Topic
RNA Interference and Gene Delivery
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Dendritic Poly(l-lysine)-Based Nanoparticle Loading with siDNMT1 to Alleviate Basal Cell Carcinoma Progression by Inhibiting Methylation of AXIN2

Yanqing Yang, Sha Xiong, Xue Wang, Y Gan et al.
ACS Applied Materials & Interfaces
RNA Interference and Gene Delivery
article

Dendritic Poly(l-lysine)-Based Nanoparticle Loading with siDNMT1 to Alleviate Basal Cell Carcinoma Progression by Inhibiting Methylation of AXIN2

Yanqing Yang, Sha Xiong, Xue Wang, Y Gan, Aili Gao
article en

Abstract

Basal cell carcinoma (BCC) is a highly invasive and metastatic non-melanoma skin tumor. Traditional treatments, such as surgery, radiation, and chemotherapy, often result in severe side effects. Recent advances in RNA interference (RNAi) have highlighted its potential in targeting cancer-causing genes. To address the complex pathology of BCC, we developed a multifunctional gene delivery system using benzylthio-modified dendritic polylysine nanoparticles loaded with siDNMT1 (siDNMT1@PDPs). This system exhibits excellent dispersibility, with over 85% of particles measuring between 50 and 80 nm, and high stability, with a zeta potential of +57.10 mV. This design enables efficient penetration into tumor cells and controlled release of siDNMT1 in the tumor microenvironment (TME), thereby improving therapeutic outcomes. Our results demonstrate that siDNMT1@PDPs significantly inhibit tumor progression and metastasis in BCC by reducing AXIN2 promoter methylation, thereby increasing AXIN2 expression. Compared to existing treatments, siDNMT1@PDPs exhibit superior biocompatibility, both <i>in vitro</i> and <i>in vivo</i>, and provide a more targeted and effective therapeutic approach. These findings suggest that siDNMT1@PDPs represent a promising advancement in RNAi-based therapies for BCC, offering potential clinical benefits over current treatment modalities.

ACS Applied Materials & InterfacesVol. 17(20)
Foshan Hospital of TCM (CN)
Guangzhou Municipal Science and Technology Project
Openalex Percentile: Top 91%
RNA Interference and Gene Delivery
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.