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Get Free Access<div>Abstract<p>Despite widespread utilization of immunotherapy, treating immune-cold tumors has proved to be a challenge. Here, we report that expression of the immune checkpoint molecule B7-H4 is prevalent among immune-cold triple-negative breast cancers (TNBC), where its expression inversely correlates with that of PD-L1. Glycosylation of B7-H4 interferes with its interaction/ubiquitination by AMFR, resulting in B7-H4 stabilization. B7-H4 expression inhibits doxorubicin-induced cell death through the suppression of eIF2α phosphorylation required for calreticulin exposure vis-à-vis the cancer cells. NGI-1, which inhibits B7-H4 glycosylation causing its ubiquitination and subsequent degradation, improves the immunogenic properties of cancer cells treated with doxorubicin, enhancing their phagocytosis by dendritic cells and their capacity to elicit CD8<sup>+</sup> IFNγ-producing T-cell responses. In preclinical models of TNBC, a triple combination of NGI-1, camsirubicin (a noncardiotoxic doxorubicin analogue) and PD-L1 blockade was effective in reducing tumor growth. Collectively, our findings uncover a strategy for targeting the immunosuppressive molecule B7-H4.</p>Significance:<p>This work unravels the regulation of B7-H4 stability by ubiquitination and glycosylation, which affects tumor immunogenicity, particularly regarding immune-cold breast cancers. The inhibition of B7-H4 glycosylation can be favorably combined with immunogenic chemotherapy and PD-L1 blockade to achieve superior immuno-infiltration of cold tumors, as well as improved tumor growth control.</p><p><i>See related commentary by Pearce and Läubli, p. 1789</i>.</p><p><i>This article is highlighted in the In This Issue feature, p. 1775</i></p></div>
Xinxin Song, Zhuan Zhou, Hongchun Li, Yifan Xue, Xinghua Lu, İvet Bahar, Oliver Kepp, Mien‐Chie Hung, Guido Guido Kroemer, Yong Wan (2023). Data from Pharmacologic Suppression of B7-H4 Glycosylation Restores Antitumor Immunity in Immune-Cold Breast Cancers. , DOI: https://doi.org/10.1158/2159-8290.c.6547934.v1.
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Type
Preprint
Year
2023
Authors
10
Datasets
0
Total Files
0
Language
en
DOI
https://doi.org/10.1158/2159-8290.c.6547934.v1
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