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Usage Information

Molecular glue degrader function of SPOP inhibitors enhances STING-dependent immunotherapy efficacy in melanoma models
Zhichuan Zhu, Xin Zhou, Max Xu, Jianfeng Chen, Kevin C. Robertson, Gatphan Atassi, Mark G. Woodcock, Allie C. Mills, Laura E. Herring, Gianpietro Dotti, Pengda Liu
Zhichuan Zhu, Xin Zhou, Max Xu, Jianfeng Chen, Kevin C. Robertson, Gatphan Atassi, Mark G. Woodcock, Allie C. Mills, Laura E. Herring, Gianpietro Dotti, Pengda Liu
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Research Article Cell biology Oncology

Molecular glue degrader function of SPOP inhibitors enhances STING-dependent immunotherapy efficacy in melanoma models

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Abstract

The E3 ligase SPOP plays a context-dependent role in cancer by targeting specific cellular proteins for degradation, thereby influencing cell behavior. However, its role in tumor immunity remains largely unexplored. In this study, we revealed that SPOP targeted the innate immune sensor STING for degradation in a CK1γ phosphorylation-dependent manner to promote melanoma growth. Stabilization of STING by escaping SPOP-mediated degradation enhanced antitumor immunity by increasing IFN-β production and ISG expression. Notably, small-molecule SPOP inhibitors not only blocked STING recognition by SPOP, but also acted as molecular glues, redirecting SPOP to target neosubstrates such as CBX4 for degradation. This CBX4 degradation led to increased DNA damage, which in turn activated STING and amplified innate immune responses. In a xenografted melanoma B16 tumor model, single-cell RNA-seq analysis demonstrated that SPOP inhibition induced the infiltration of immune cells associated with anti–PD-1 responses. Consequently, SPOP inhibitors synergized with immune checkpoint blockade to suppress B16 tumor growth in syngeneic murine models and enhanced the efficacy of CAR.CD19-T cell therapy. Our findings highlight a molecular glue degrader property of SPOP inhibitors, with potential implications for other E3 ligase–targeting small molecules designed to disrupt protein–protein interactions.

Authors

Zhichuan Zhu, Xin Zhou, Max Xu, Jianfeng Chen, Kevin C. Robertson, Gatphan Atassi, Mark G. Woodcock, Allie C. Mills, Laura E. Herring, Gianpietro Dotti, Pengda Liu

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Usage data is cumulative from October 2025 through September 2026.

Usage JCI PMC
Text version 3,856 394
PDF 1,029 149
Figure 1,772 0
Supplemental data 659 17
Citation downloads 314 0
Totals 7,630 560
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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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ISSN: 0021-9738 (print), 1558-8238 (online)

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