Issue 26, 2020

A COF-based nanoplatform for highly efficient cancer diagnosis, photodynamic therapy and prognosis

Abstract

Covalent organic frameworks (COFs) have emerged as a kind of promising material for analytical and biomedical purposes. However, simultaneous cancer diagnosis and therapy with COFs remain a challenge. We report here a COF-based theranostic nanoplatform by integrating a dye-labeled oligonucleotide onto porphyrin-based COF nanoparticles for highly efficient cancer diagnosis and therapy. The fluorescence of the dye was effectively quenched by the COF through fluorescence resonance energy transfer (FRET). In the presence of biomarker survivin mRNA, more stable duplexes were formed and separated from the COF NPs, enabling the recovery of the fluorescence signal and selective cancer imaging. Under NIR laser irradiation, COF NPs generated abundant reactive oxygen species (ROS) to induce cancer cell apoptosis owing to their crystalline reticular structure. In vitro and in vivo experiments revealed that the nanoplatform has a high specificity and inhibition effect toward cancer cells and solid tumors. Interestingly, prognostic evaluation was also realized with COF-survivin. This work will offer new insights into COF-based probes and inspire the development of more versatile tools for biomedical applications.

Graphical abstract: A COF-based nanoplatform for highly efficient cancer diagnosis, photodynamic therapy and prognosis

Supplementary files

Article information

Article type
Edge Article
Submitted
12 Feb 2020
Accepted
15 Jun 2020
First published
16 Jun 2020
This article is Open Access

All publication charges for this article have been paid for by the Royal Society of Chemistry
Creative Commons BY license

Chem. Sci., 2020,11, 6882-6888

A COF-based nanoplatform for highly efficient cancer diagnosis, photodynamic therapy and prognosis

P. Gao, M. Wang, Y. Chen, W. Pan, P. Zhou, X. Wan, N. Li and B. Tang, Chem. Sci., 2020, 11, 6882 DOI: 10.1039/D0SC00847H

This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. You can use material from this article in other publications without requesting further permissions from the RSC, provided that the correct acknowledgement is given.

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