Cascade-Responsive Upconversion Nanoplatform for Efficient Cell Nucleus Targeting and Boosted Photodynamic Tumor Therapy

In order to increase tumor tissue penetration, enhance phototherapy efficiency, and reduce off-target toxicity, we have developed a dual-locked upconversion nanoplatform (UCNP@Glu-DMMA) with a charge-reversal property for tumor-specific, cell nucleus-penetrating photodynamic therapy (PDT). The negative charge on the surface of UCNP@Glu-DMMA ensured excellent stability during blood circulation and accumulation in the tumor microenvironment (TME). Subsequently, the combined effect of the acidic TME and γ-glutamyl transpeptidase (GGT) triggered a reversal of the surface charge from negative to positive. This reversal enhanced the uptake efficiency of UCNP, leading to an increased intracellular drug concentration, deep tumor penetration, and direct nucleus delivery for the localized release of reactive oxygen species, resulting in robust DNA damage. As a result, the efficacy of PDT was significantly and precisely boosted for GGT-overexpressed tumors. This work provides a promising strategy to engineer therapeutic platforms for managing a variety of diseases based on different biomarkers.

Authors

Institutions

Publication Details

Journal
ACS Materials Letters
Published
2024-10-31
DOI
https://doi.org/10.1021/acsmaterialslett.4c01614
Citations
4
Primary Topic
Nanoplatforms for cancer theranostics
Type
article
Field-Weighted Citation Impact
0.74

Funders

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

Cascade-Responsive Upconversion Nanoplatform for Efficient Cell Nucleus Targeting and Boosted Photodynamic Tumor Therapy

Lun Wang, Yue Yuan, Lijiao Yang, Jia Zhang et al.
4 citations
ACS Materials Letters
Nanoplatforms for cancer theranostics
0.74
article

Cascade-Responsive Upconversion Nanoplatform for Efficient Cell Nucleus Targeting and Boosted Photodynamic Tumor Therapy

Lun Wang, Yue Yuan, Lijiao Yang, Jia Zhang, Chenchen Wang, Bo Ling, Ling Dong, Yanyun Yang
article en
4 citations

Abstract

In order to increase tumor tissue penetration, enhance phototherapy efficiency, and reduce off-target toxicity, we have developed a dual-locked upconversion nanoplatform (UCNP@Glu-DMMA) with a charge-reversal property for tumor-specific, cell nucleus-penetrating photodynamic therapy (PDT). The negative charge on the surface of UCNP@Glu-DMMA ensured excellent stability during blood circulation and accumulation in the tumor microenvironment (TME). Subsequently, the combined effect of the acidic TME and γ-glutamyl transpeptidase (GGT) triggered a reversal of the surface charge from negative to positive. This reversal enhanced the uptake efficiency of UCNP, leading to an increased intracellular drug concentration, deep tumor penetration, and direct nucleus delivery for the localized release of reactive oxygen species, resulting in robust DNA damage. As a result, the efficacy of PDT was significantly and precisely boosted for GGT-overexpressed tumors. This work provides a promising strategy to engineer therapeutic platforms for managing a variety of diseases based on different biomarkers.

ACS Materials LettersVol. 6(12)
University of Science and Technology of China (CN), Hefei Normal University (CN), Anhui Normal University (CN), China Medical University (CN)
National Natural Science Foundation of China, University Natural Science Research Project of Anhui Province, National Key Research and Development Program of China, Fundamental Research Funds for the Central Universities
Openalex Percentile: Top 32%
Nanoplatforms for cancer theranostics
0.74
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.