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Cited by 544

The DOI matches its Crossref record; 184 of the 184 references it cites were found in a registry or an index.

Recent advances in nanomedicines for photodynamic therapy (PDT)-driven cancer immunotherapy

Open access
Ji, Bin, Wei, Minjie, Yang, Bin·2022·Theranostics

Abstract

Cancer immunotherapy has made tremendous clinical progress in advanced-stage malignancies. However, patients with various tumors exhibit a low response rate to immunotherapy because of a powerful immunosuppressive tumor microenvironment (TME) and insufficient immunogenicity of tumors. Photodynamic therapy (PDT) can not only directly kill tumor cells, but also elicit immunogenic cell death (ICD), providing antitumor immunity. Unfortunately, limitations from the inherent nature and complex TME significantly reduce the efficiency of PDT. Recently, smart nanomedicine-based strategies could subtly modulate the pharmacokinetics of therapeutic compounds and the TME to optimize both PDT and immunotherapy, resulting in an improved antitumor effect. Here, the emerging nanomedicines for PDT-driven cancer immunotherapy are reviewed, including hypoxia-reversed nanomedicines, nanosized metal-organic frameworks, and subcellular targeted nanoparticles (NPs). Moreover, we highlight the synergistic nanotherapeutics used to amplify immune responses combined with immunotherapy against tumors. Lastly, the challenges and future expectations in the field of PDT-driven cancer immunotherapy are discussed.

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Metadata

Authors
Ji, B., Wei, M., & Yang, B.
Venue
Theranostics
Published
2022
Volume
12
Issue
1
Pages
434-458
ISSN
1838-7640 (ISSN-L)
OpenAlex
W4200537699
Cited by
544
References
184
FWCI
19.60
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: Recent advances in nanomedicines for photodynamic therapy (PDT)-driven cancer immunotherapy. https://app.cochat.ai/papers/10.7150/thno.67300
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Ji, B., Wei, M., & Yang, B. (2022). Recent advances in nanomedicines for photodynamic therapy (PDT)-driven cancer immunotherapy. Theranostics. https://doi.org/10.7150/thno.67300

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

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