ReviewFrontiers in bioengineering and biotechnology2022
Application of photo-responsive metal-organic framework in cancer therapy and bioimaging.
Review in Frontiers in bioengineering and biotechnology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
11 citing papers in PubMed.
- Zn(ii)-based metal-organic frameworks with tailored architectures: optimizing fluorescence performance for cell imaging and cancer therapy.RSC advances · 2026Article
- Metal-Organic Framework-Based Drug Delivery Systems for Cancer Therapy: A Review.International journal of molecular sciences · 2026Review
- Combined Photothermal and mTOR-Targeted Therapy Overcomes Immune Evasion and Enhances Checkpoint Blockade Efficacy in Metastatic Triple-Negative Breast Cancer.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Photoactivation in Chemotherapeutic Compounds for Cancer Treatment: Opportunities Beyond Photodynamic Therapy.Bioinorganic chemistry and applications · 2026Review
- Metal organic framework-based variable-size nanoparticles for tumor microenvironment-responsive drug delivery.Drug delivery and translational research · 2024Review
- Nanomaterials: leading immunogenic cell death-based cancer therapies.Frontiers in immunology · 2024Review
- MOFs for next-generation cancer therapeutics through a biophysical approach-a review.Frontiers in bioengineering and biotechnology · 2024Review
- Porous Framework Materials for Bioimaging and Cancer Therapy.Molecules (Basel, Switzerland) · 2023Review
- Photothermally sensitive gold nanocage augments the antitumor efficiency of immune checkpoint blockade in immune "cold" tumors.Frontiers in immunology · 2023Article
- Application and Development Prospect of Nanoscale Iron Based Metal-Organic Frameworks in Biomedicine.International journal of nanomedicine · 2023Review
- Modulating the tumor immune microenvironment with nanoparticles: A sword for improving the efficiency of ovarian cancer immunotherapy.Frontiers in immunology · 2022Review
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Metal-organic frameworks (MOFs) are a class of hybrid porous crystalline materials that are assembled with metal ions/clusters and organic linkers. The fungibility of organic ligands and metal centers endow MOFs that are easy to design and synthesize. Based on their unique structure, multifarious MOFs with diverse functionalities have recently been widely applied in various research areas. Particularly striking is the application of photo-responsive MOFs in biological sensing and imaging. Notably, the photoelectronic properties make photo-responsive MOFs an ideal platform for cancer phototherapy. Moreover, ultrahigh porosities and tunable pore sizes allow MOFs to load anticancer drugs, further enhancing the antitumor efficiency. In this review, the categories and developing strategies of MOFs are briefly introduced. The application fields of MOFs in bioimaging, such as up-conversion fluorescence imaging, single/two-photon fluorescence bioimaging, magnetic resonance imaging, etc., are summarized. The working mechanism of MOFs in photo-responsive, photothermal therapy (PTT), and photodynamic therapy (PDT) are expounded. Examples of using MOFs for cancer treatment, including PTT, PDT, chemotherapy, and radiotherapy, are also demonstrated. Lastly, current limitations, challenges, and future perspectives for bioimaging and cancer treatment of MOFs are discussed. We believe that the versatile MOF will bring the dawn to the next generation of cancer treatment.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.