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Usage Information

Targeting macrophage checkpoint inhibitor SIRPα for anticancer therapy
Jie Liu, … , Irving L. Weissman, Jens-Peter Volkmer
Jie Liu, … , Irving L. Weissman, Jens-Peter Volkmer
Published May 19, 2020
Citation Information: JCI Insight. 2020;5(12):e134728. https://doi.org/10.1172/jci.insight.134728.
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Research Article Immunology Therapeutics

Targeting macrophage checkpoint inhibitor SIRPα for anticancer therapy

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Abstract

The CD47/signal regulatory protein α (Cd47/SIRPα)interaction provides a macrophage immune checkpoint pathway that plays a critical role in cancer immune evasion across multiple cancers. Here, we report the engineering of a humanized anti-SIRPα monoclonal antibody (1H9) for antibody target cancer therapy. 1H9 has broad activity across a wide range of SIRPα variants. Binding of 1H9 to SIRPα blocks its interaction with CD47, thereby promoting macrophage-mediated phagocytosis of cancer cells. Preclinical studies in vitro and in vivo demonstrate that 1H9 synergizes with other therapeutic antibodies to promote phagocytosis of tumor cells and inhibit tumor growth in both syngeneic and xenograft tumor models, leading to survival benefit. Thus, 1H9 can potentially act as a universal agent to enhance therapeutic efficacy when used in combination with most tumor-targeting antibodies. We report a comparison of anti-SIRPα and anti-CD47 antibodies in CD47/SIRPα double-humanized mice and found that 1H9 exhibits a substantially reduced antigen sink effect due to the limited tissue distribution of SIRPα expression. Toxicokinetic studies in nonhuman primates show that 1H9 is well tolerated, with no treatment-related adverse effects noted. These data highlight the clinical potential of 1H9 as a pan-therapeutic with the desired properties when used in combination with tumor-targeting antibodies.

Authors

Jie Liu, Seethu Xavy, Shirley Mihardja, Sharline Chen, Kavitha Sompalli, Dongdong Feng, Timothy Choi, Balaji Agoram, Ravindra Majeti, Irving L. Weissman, Jens-Peter Volkmer

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Usage data is cumulative from August 2021 through August 2022.

Usage JCI PMC
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PDF 546 129
Figure 342 15
Table 27 0
Supplemental data 82 7
Citation downloads 88 0
Totals 3,229 637
Total Views 3,866

Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.

Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.

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