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Cited by 440

The DOI matches its Crossref record; 48 of the 48 references it cites were found in a registry or an index.

Precision glycocalyx editing as a strategy for cancer immunotherapy

Open access
Xiao, Han, Woods, Elliot C., Vukojicic, Petar, Bertozzi, Carolyn R.·2016·Proceedings of the National Academy of Sciences

Abstract

Significance: Successful tumors are able to evade the immune system, which is otherwise capable of killing transformed cells. Therapies that prevent this evasion have become revolutionary treatments for incurable cancers. One mechanism of evasion is the presentation of sugars, called sialic acids, within the cell surface’s sugar coating, or glycocalyx. Here, we designed biotherapeutic molecules, termed “antibody–enzyme conjugates,” that selectively remove sialic acids from tumor cells. The antibody directs the enzyme to the cancer cells, the enzyme cleaves the sugars, and then the antibody directs immune cells to kill the desialylated cancer cells. The conjugate increased tumor cell killing compared with the antibody alone. Editing the cancer cell glycocalyx with an antibody–enzyme conjugate represents a promising approach to cancer immune therapy.

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Metadata

Authors
Xiao, H., Woods, E. C., Vukojicic, P., & Bertozzi, C. R.
Venue
Proceedings of the National Academy of Sciences
Published
2016-08-22
Volume
113
Issue
37
Pages
10304-10309
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
OpenAlex
W2508974650
Cited by
440
References
48
FWCI
12.19
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Precision glycocalyx editing as a strategy for cancer immunotherapy. https://app.cochat.ai/papers/10.1073/pnas.1608069113
The paper
Xiao, H., Woods, E. C., Vukojicic, P., & Bertozzi, C. R. (2016). Precision glycocalyx editing as a strategy for cancer immunotherapy. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.1608069113

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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.