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Cited by 286

The DOI matches its Crossref record; 27 of the 27 references it cites were found in a registry or an index.

Tailoring Biomaterials for Cancer Immunotherapy: Emerging Trends and Future Outlook

Open access
Wang, Chao, Ye, Yanqi, Hu, Quanyin, Bellotti, Adriano, Gu, Zhen·2017·Advanced Materials

Abstract

Cancer immunotherapy, as a paradigm shift in cancer treatment, has recently received tremendous attention. The active cancer vaccination, immune checkpoint blockage (ICB) and chimeric antigen receptor (CAR) for T‐cell‐based adoptive cell transfer are among these developments that have achieved a significant increase in patient survival in clinical trials. Despite these advancements, emerging research at the interdisciplinary interface of cancer biology, immunology, bioengineering, and materials science is important to further enhance the therapeutic benefits and reduce side effects. Here, an overview of the latest studies on engineering biomaterials for the enhancement of anticancer immunity is given, including the perspectives of delivery of immunomodulatory therapeutics, engineering immune cells, and constructing immune‐modulating scaffolds. The opportunities and challenges in this field are also discussed.

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Crossref · 10.1002/adma.201606036

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Metadata

Authors
Wang, C., Ye, Y., Hu, Q., Bellotti, A., & Gu, Z.
Venue
Advanced Materials
Publisher
Wiley
Published
2017-05-26
Volume
29
Issue
29
ISSN
  • 0935-9648 (ISSN-L)
  • 1521-4095
OpenAlex
W2616983963
Cited by
286
References
27
FWCI
14.44
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Tailoring Biomaterials for Cancer Immunotherapy: Emerging Trends and Future Outlook. https://app.cochat.ai/papers/10.1002/adma.201606036
The paper
Wang, C., Ye, Y., Hu, Q., Bellotti, A., & Gu, Z. (2017). Tailoring Biomaterials for Cancer Immunotherapy: Emerging Trends and Future Outlook. Advanced Materials. https://doi.org/10.1002/adma.201606036

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

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

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.