CD47 destabilization via manipulating the SPOP-USP2 axis augments macrophage phagocytosis and cancer immunotherapy

Peiqiang Yan; Xia Bu; Tao Hou; Li Chen; Guoxuan Zhong; Daoyuan Huang; Jingchao Wang; Yihang Qi; Weiwei Jiang; Zhe Li; Xutong Xue; Yang Gao; Jing Liu; Hiroyuki Inuzuka; Gordon J Freeman; Wenyi Wei; Xiaoming Dai

doi:10.1136/jitc-2025-013498

. 2026 Jan 14;14(1):e013498. doi: 10.1136/jitc-2025-013498

CD47 destabilization via manipulating the SPOP-USP2 axis augments macrophage phagocytosis and cancer immunotherapy

Peiqiang Yan ^1,⁰, Xia Bu ^2,⁰, Tao Hou ^1,⁰, Li Chen ¹, Guoxuan Zhong ³, Daoyuan Huang ¹, Jingchao Wang ¹, Yihang Qi ¹, Weiwei Jiang ¹, Zhe Li ³, Xutong Xue ⁴, Yang Gao ⁵, Jing Liu ⁵, Hiroyuki Inuzuka ¹, Gordon J Freeman ^2,^*, Wenyi Wei ^1,^✉, Xiaoming Dai ^1,^3,^6,^*

¹Department of Pathology, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA

²Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA

³Institute of Modern Biology, Nanjing University, Nanjing, Jiangsu, China

⁴Department of Neurology & F.M. Kirby Neurobiology Center, Boston Children’s Hospital, Boston, Massachusetts, USA

⁵Department of Urology, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, China

⁶Division of Hepatobiliary and Transplantation Surgery, Department of General Surgery, Nanjing Drum Tower Hospital, Nanjing University, Nanjing, Jiangsu, China

Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

Supplement: Additional supplemental material is published online only. To view, please visit the journal online (https://doi.org/10.1136/jitc-2025-013498).

GJF has patents/pending royalties on the PD-L1/PD-1 pathway from Bristol-Myers Squibb, Roche, Eli Lilly, and Novartis. GJF has served on advisory boards for iTeos, NextPoint, IgM, GV20, IOME, Bioentre, Santa Ana Bio, Simcere of America, and Geode. GJF has equity in NextPoint, Triursus, Xios, iTeos, IgM, Trillium, Invaria, GV20, Bioentre, and Geode. WW is a co-founder and consultant for Rekindle Therapeutics. Other authors declare no competing financial interests.

^✉

Dr Wenyi Wei; wwei2@bidmc.harvard.edu

Dr Xiaoming Dai; xdai@nju.edu.cn

Dr Gordon J Freeman; gordon_freeman@dfci.harvard.edu

PY, XB and TH contributed equally.

PMCID: PMC12815083 PMID: 41534899

Abstract

Background

Macrophages can eliminate cancer cells through phagocytosis via the CD47/signal regulatory protein α axis, which provides promising targets for cancer immunotherapy as innate immune checkpoints. Although CD47 is overexpressed in multiple cancer types, it remains largely unknown whether and how CD47 can be targeted by manipulating its protein stability.

Experimental design

Multiple human cancer cell lines were used to identify the function of the ubiquitin-specific protease 2 (USP2) /speckle-type POZ protein (SPOP) axis and the USP2 inhibitor on CD47 protein stability by immunoblot and immunoprecipitation, real-time quantitative PCR, in vitro deubiquitination assay, cell fractionation assay, flow cytometry, and phagocytosis assay. We investigated the antitumor immune response and immunotherapy effects of the USP2 inhibitor using multiple syngeneic and orthotopic mouse tumor models, bioluminescence imaging, immune cell depletion, tumor-infiltrating lymphocyte (TIL) isolation, and flow cytometry.

Results

Here, we report that ML364, an inhibitor of the USP2 deubiquitinase, reduces the protein abundance of CD47. Mechanistically, USP2 deubiquitinates and protects CD47 from proteasome-mediated degradation. Furthermore, we reveal that USP2 itself can be ubiquitinated by the SPOP ubiquitin E3 ligase, which leads to USP2 degradation and decreased CD47 protein abundance. Functionally, ML364 promotes macrophage phagocytosis of cancer cells by reducing the expression of CD47 and enhances the efficacy of anti-programmed cell death protein-1 (PD-1) immunotherapy, thereby inhibiting tumor growth and improving the overall survival rate in multiple syngeneic and orthotopic mouse tumor models. Bioinformatic analyses indicate that low USP2 expression or high SPOP expression predicts a better response to anti-PD-1 treatment.

Conclusion

Hence, our findings reveal a pivotal role of the SPOP/USP2 axis in regulating CD47 protein stability and advocate for combining USP2 inhibitors with anti-PD-1 immunotherapy to combat cancer.

Keywords: Escape/evasion, Immune Checkpoint Inhibitor, Immune modulatory, Immunotherapy, Macrophage

WHAT IS ALREADY KNOWN ON THIS TOPIC

Although CD47 plays an important role in the immune evasion of cancer cells, the exact molecular mechanisms by which CD47 protein stability is regulated remain largely unknown.

WHAT THIS STUDY ADDS

Here, we report that ubiquitin-specific protease 2 (USP2) deubiquitinates and protects CD47 from degradation. USP2 itself can be ubiquitinated by the speckle-type POZ protein (SPOP) E3 ligase, leading to USP2 degradation and decreased CD47 expression. The USP2 inhibitor, ML364, promotes macrophage phagocytosis of cancer cells, enhances the efficacy of anti-programmed cell death protein-1 immunotherapy, and improves the survival rate in multiple mouse tumor models.

HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY

Our findings uncover an important role of the SPOP/USP2/CD47 axis in cancer immunotherapy and reveal USP2 as a novel target for immunotherapy.

Introduction

Cancer immunotherapies targeting adaptive immune checkpoints, such as PD-1/PD-L1 (programmed cell death protein 1/programmed cell death ligand 1) and CTLA-4 (cytotoxic T-lymphocyte-associated protein 4), have led to unprecedented success in cancer therapy.1,3 However, only a minority of patients with cancer benefit from these treatments, highlighting the urgent need to identify new therapeutic targets to increase the efficacy of immunotherapy.⁴ To this end, emerging studies show that innate immune checkpoints, serving as the first line of non-antigen-specific defenses against infection and malignant cell transformations, also play an important role in tumor-mediated immune escape and provide promising targets for cancer immunotherapy.⁵

Macrophages, key effectors of the innate immune system, can eliminate cancer cells through phagocytosis, which is mainly regulated by the CD47/SIRPα (signal regulatory protein α) axis.⁶ Mechanistically, the cell-surface protein CD47 is recognized by SIRPα on macrophages or dendritic cells, which provides a ‘‘don’t eat me’’ signal that protects healthy cells from macrophage engulfment.^{6 7} Elevated expression of CD47 has been observed in a wide range of human cancers and helps cancer cells evade phagocytosis.^{8 9} Hence, blockade of CD47 using monoclonal antibodies increases the phagocytosis of tumor cells by professional phagocytes and activates T-cell cytotoxicity, suggesting that CD47 expression is likely crucial for escape from macrophage-mediated phagocytic attack.8,12 Although CD47 plays an important role in the immune evasion of cancer cells, the exact molecular mechanisms by which CD47 protein stability is regulated at the post-translational level, such as the ubiquitination and deubiquitination process, remain largely unknown. Recently, the ubiquitin E3 ligase TRIM21 was identified as promoting CD47 poly-ubiquitination and degradation.¹³ However, the regulation of CD47 by deubiquitinating enzymes remains to be determined.

USP2 protects CD47 from proteasome-mediated degradation

Given the key role of CD47 in tumor immune evasion⁶ and its broad expression in multiple types of human cancers,^{8 9} we investigated whether CD47 protein abundance could be modified by targeting deubiquitinases using 12 different deubiquitinating enzyme inhibitors. Remarkably, we found that the ubiquitin-specific protease 2 (USP2) inhibitor ML364¹⁴ could significantly decrease CD47 protein abundance in different cancer cell lines (figure 1A–C, online supplemental figure 1A). Further experiments showed that ML364 could reduce the protein abundance of CD47 in a dose-dependent and time-dependent manner, but the messenger RNA (mRNA) levels of CD47 did not significantly change under these experimental conditions (figure 1D–H, online supplemental figure 1B–K). These results suggest that ML364 affects CD47 protein abundance largely through post-translational regulation. In keeping with the notion that CD47 mainly localizes on the plasma membrane, we found by flow cytometry that cell surface CD47 was reduced after ML364 treatment (figure 1I, online supplemental figure 1L). Consistent with the results, the cellular fractionation assay revealed that ML364 mainly reduced the abundance of membrane-localized CD47 (online supplemental figure 1M,N). Moreover, a novel USP2 inhibitor, MS102,¹⁵ which is an orally optimized USP2 inhibitor, could also decrease CD47 protein abundance and increase the protein abundance of p53 and PD-L1 (online supplemental figure 1O).¹⁶ Furthermore, echoing a previous report,¹⁴ ML364 decreased the protein abundance of USP2 substrate cyclin D1 in various cell lines we examined (figure 1D,F,G, online supplemental figure 1B,D,F–K). In addition, we found that ML364 treatment did not significantly increase cytotoxicity or calreticulin expression in multiple human cancer cells we examined (online supplemental figure 1P–U).

Because ML364 inhibits the enzymatic activity of USP2, which mediates deubiquitination,¹⁴ we further tested whether USP2 could protect CD47 from ubiquitination-mediated degradation. Consistent with this notion, ectopic overexpression of wild-type, but not the enzymatically inactive mutant form (C276A) of USP2, could elevate the protein abundance of CD47 (figure 1J). Moreover, ML364 could reduce the elevation of CD47 protein abundance induced by overexpression of wild-type USP2 (figure 1K). These results together suggest that USP2 activity positively regulates the protein abundance of CD47 in cells. In support of this notion, depletion of endogenous USP2 also led to decreased CD47 protein abundance (figure 1L, online supplemental figure 2B,D), but not mRNA levels (online supplemental figure 2A,C,E). Moreover, the half-life of CD47 was shortened after depleting endogenous USP2 (figure 1M–P, online supplemental figure 2F,G). On the other hand, overexpression of USP2 extended the protein half-life of CD47 (online supplemental figure 2H–K). Furthermore, in ML364-treated cells, the half-life of CD47 was shortened (online supplemental figure 2L,M). These data together suggest that ML364 could promote the degradation of CD47 by inhibiting the deubiquitinase enzymatic activity of USP2.

USP2 is a physiological deubiquitinating enzyme for CD47

To further dissect the mechanism of how USP2 regulates the expression of CD47, we performed co-immunoprecipitation assays and found that USP2 interacted with CD47 (figure 2A, online supplemental figure 3A). CD47 mainly interacted with the N-terminal domain of USP2, but not with the C-terminal USP domain (figure 2B,C). More importantly, wild-type USP2, but not the catalytically inactive form, could reduce the ubiquitination of CD47 in cells (figure 2D, online supplemental figure 3B). In further support of USP2 as a possible deubiquitinating (DUB) for CD47, the deubiquitination of CD47 mediated by USP2 could be blocked by its inhibitor, ML364 (figure 2E). We further found that USP2 could reduce the formation of K48 linkage polyubiquitination of CD47 (figure 2F, online supplemental figure 3C,D). Notably, the protein half-life of CD47 was also extended when co-expressed with wild-type, but not the inactive form of USP2 (figure 2G and H). Small hairpin RNA (shRNA)-mediated depletion of USP2 induced a reduction in CD47 protein abundance, and this reduction was rescued by overexpression of USP2, thereby eliminating the possibility of off-target effects associated with shRNA treatment (figure 2I, online supplemental figure 3E–H). On the other hand, ML364 did not further reduce the protein abundance of CD47 in USP2-depleted cells, suggesting that USP2 is likely the major route through which ML364 regulates CD47 protein abundance (figure 2K). Moreover, we found that only the proteasome inhibitor MG132, but not the lysosomal-mediated degradation inhibitor chloroquine, could rescue CD47 protein levels in USP2-depleted cell lines (figure 2L, online supplemental figure 3I). Collectively, our data suggest that USP2 could enhance the protein stability of CD47 in part through reducing its ubiquitination.

SPOP interacts with and ubiquitinates USP2 to promote its degradation

Protein abundance is balanced by ubiquitination and deubiquitination. Although we have identified USP2 as a pivotal DUB enzyme that deubiquitinates and stabilizes the CD47 protein, the physiological ubiquitin E3 ligase responsible for promoting USP2 ubiquitination and subsequent degradation remains largely unknown. Notably, treatment of cells with both the proteasome inhibitor MG132 and the cullin-based ubiquitin E3 ligase inhibitor MLN4924 increased USP2 protein levels (figure 3A). Through analyzing the protein sequence of USP2, we found that there are two possible speckle-type POZ protein (SPOP) binding motifs, or ‘‘degrons’’ in USP2 (figure 3B).¹⁷ SPOP functions as a substrate adaptor of cullin 3-based E3 ligase and plays a crucial role in the development and progression of multiple human cancers via targeting a plethora of protein substrates for ubiquitination and subsequent proteasomal degradation.^{17 18} Hence, we tested whether SPOP could regulate USP2 protein stability and found that SPOP could interact with wild-type USP2 in cells (figure 3C,D, online supplemental figure 4A). Notably, deletion of degron 2 in USP2, but not degron 1, could reduce the interaction between SPOP and USP2 in this experimental setting (figure 3E). In further support of degron 2 as the critical motif recognized by SPOP, mutation of degron 2 also decreased the interaction between SPOP and USP2 (figure 3F). Consistent with the fact that the N-terminal MATH (meprin and TRAF-C homology) domain of SPOP recognizes substrates,¹⁹ we found that deletion of the MATH domain eliminated SPOP binding to USP2. Depletion of the BTB domain, which was previously reported to largely mediate the interaction with the cullin 3 complex,^{17 19} did not affect SPOP binding to USP2 (figure 3G,H).

SPOP somatic mutations identified in prostate cancers, such as Y87C, F102C, and W131G, are clustered in the MATH domain, which leads to impaired interactions with known substrates.20,22 Consistent with this, we found that cancer-associated SPOP mutants showed a reduced capability to bind USP2 (figure 3I). In addition, cancer-associated SPOP mutants showed reduced activity for promoting USP2 ubiquitination in cells (figure 3J). More importantly, ectopic expression of SPOP decreased the protein abundance of USP2 in a dose-dependent manner (figure 3K). We further confirmed that SPOP could promote the ubiquitination of wild-type USP2, but not the degron 2 mutant form of USP2 (figure 3L). Consistent with this, the protein half-life of wild-type, but not the degron 2 mutant form of USP2, was shortened after co-expression with SPOP (figure 3M–P). Together, these results support the notion that SPOP specifically regulates USP2 protein stability by promoting its ubiquitination.

Consistent with a critical role for SPOP in regulating USP2 protein stability, depletion of endogenous SPOP by shRNAs or CRISPR-mediated sgRNAs led to a noticeable increase in protein abundance (figure 4A, online supplemental figure 4B,D,F), but not the mRNA levels of USP2 (figure 4B, online supplemental figure 4C,E). Consistent with our previous finding that USP2 protects CD47 from degradation, depletion of endogenous SPOP increased CD47 protein abundance (figure 4A, online supplemental figure 4B,D,F). Furthermore, this accumulation could be reversed by overexpression of SPOP without changes in USP2 mRNA levels (figure 4C, online supplemental figure 4G–I). In keeping with this result, depletion of SPOP extended the protein half-life of USP2 (figure 4E–H). Moreover, we found that in shRNA-mediated USP2-knockdown cells, additional knocking down of endogenous SPOP led to a partial rescue of USP2 protein levels, which subsequently led to a partial rescue of endogenous CD47 protein abundance, indicating that USP2 is likely the major route through which SPOP modulates CD47 protein abundance (figure 4I). On the other hand, in SPOP-depleted cells, the CD47 protein level was further decreased after depletion of USP2 (figure 4G). Moreover, we also found that SPOP did not directly interact with CD47 (online supplemental figure 4J,K). These data indicate that the regulation of CD47 protein stability by SPOP is likely dependent on USP2 expression. Taken together, these data support a model in which SPOP acts as a bona fide upstream E3 ligase of USP2 that earmarks USP2 for proteasomal destruction to subsequently influence CD47 protein abundance (figure 4K).

USP2 inhibition activates macrophage phagocytosis and sensitizes tumors to cancer immunotherapy

Because CD47 is a key regulator of phagocytosis,⁶ we tested whether ML364-mediated downregulation of CD47 could functionally modulate phagocytosis. In keeping with the results showing that ML364 could decrease CD47 expression in human cancer cell lines (figure 1), we found that ML364 significantly enhanced primary human macrophage phagocytosis of MDA-MB-231 and HCT116 human cancer cell lines (figure 5A,B). We also confirmed that ML364 could decrease the protein abundance of CD47 in mouse cancer cell lines (online supplemental figure 5A,B). In keeping with results obtained from human cancer cells, in keeping with results obtained from human cancer cells, ML364 did not significantly increase cytotoxicity or calreticulin expression in multiple mouse cancer cells we examined (online supplemental figure 5C–H). Importantly, ML364 could enhance the phagocytic activity of murine macrophage cell lines Raw 264.7 and J774A.1 to engulf mouse cancer cell lines (figure 5C,D, and online supplemental figure 5I,J). Interestingly, ML364 treatment did not lead to a marked change in the protein abundance of either CD47 or SIRPα in the mouse Raw 264.7 macrophage cell line or human THP-1 monocytic cell line (online supplemental figure 5K–P). This was possibly due to the relatively low expression level of USP2 in these cells, which also suggests a possible USP2-independent regulation of CD47 in this cellular context (online supplemental figure 5Q,R). In addition, microscopy imaging also confirmed that ML364 could significantly show primary human macrophage phagocytosis of MDA-MB-231 and HCT116 human cancer cell lines (online supplemental figure 5S,T).

Given that the major side effects of current CD47 therapeutic antibodies include anemia and thrombocytopenia,²³ we assessed the blood toxicity of ML364 in BALB/cJ mice bearing CT26 tumors. We found that, except for a minor decrease in red blood cells (RBCs), no significant difference was observed in the counts of white blood cells and platelets in mice treated with ML364 or CD47-mAb (online supplemental figure 6A–C). Interestingly, while CD47 mAb treatment caused obvious splenomegaly,²⁴ ML364 did not significantly alter the weight of the spleens (online supplemental figure 6D,E). USP2 expression level in tumor cells is much higher than the blood cells (online supplemental figure 6F). Consistently, both ML364 and CD47 mAb treatment could suppress the growth of CT26 tumors (online supplemental figure 6G). In addition, we also identified that ML364 did not significantly reduce the expression of SIRPα in macrophages or CD47 in macrophages and T cells (online supplemental figure 6H–M). These results suggest that ML364 may suppress tumor growth with relatively minor side effects compared with CD47 blockade, as ML364 specifically reduces the expression of CD47 in tumor cells, but not immune cells.

Since both elevated phagocytosis by macrophages and decreased PD-1 signaling can contribute to enhancing the efficacy of PD-1-based immunotherapy,25,28 we hypothesized that combining ML364 and anti-PD-1 antibody could improve the efficacy in mouse tumor models. To test whether USP2 could regulate CD47 in vivo, we treated mice with ML364 for 2 weeks and found a noticeable decrease in CD47 protein levels in various organs of ML364-treated mice (online supplemental figure 7A). Moreover, we treated mice bearing murine CT26 tumors and observed that ML364 treatment decreased CD47 protein levels in this experimental setting (online supplemental figure 7B). Hence, we treated mice bearing CT26 tumors with ML364 and anti-PD-1 antibody separately and in combination (figure 5E). Notably, ML364 treatment alone modestly but significantly reduced tumor growth (figure 5F,H). In contrast, anti-PD-1 antibody alone resulted in 3 long-term survivors out of 15 treated mice (figure 5F,G). Moreover, ML364 and anti-PD-1 antibody combination demonstrated significant inhibition in tumor progression and resulted in a significant improvement in overall survival compared to single-agent treatment with 7 long-term survivors out of 13 treated mice (figure 5F,G). The ML364 combination with anti-PD-1 therapy significantly elevated dendritic cells and antitumor M1 macrophages, accompanied by a dramatic reduction in immunosuppressive M2 macrophages, monocytic myeloid-derived suppressor cell (MDSC), and granulocytic MDSCs, compared with the monotherapy control group (figure 5I, online supplemental figure 7C–G). Consistent with an important role of CD47 in antitumor T-cell immunity,^{10 11 29} ML364 combination with anti-PD-1 therapy also led to an increase in cytotoxic CD8+ T cells, but not regulatory T cells (online supplemental figure 7H,I).

We further used the LLC1 syngeneic mouse model, a murine lung cancer model known for its relative resistance to anti-PD-1 monoclonal antibody (mAb) treatment.³⁰ We found that ML364 alone slowed the growth of LLC1 tumors (online supplemental figure 7J,K). More importantly, ML364 synergized with anti-PD-1 mAb treatment to enhance the survival of mice bearing LLC1 tumors, though there were no long-term survivors (online supplemental figure 7K). We evaluated the phagocytic efficiency of macrophages for tumor cells by inoculation of LLC1-GFP cells in C57BL/6 mice. We found that LLC1-GFP tumor cells were highly phagocytosed after combined treatment with ML364 and anti-PD-1 mAb (figure 5J,K, online supplemental figure 7L,M). This indicated that tumor cells were phagocytosed both by macrophage cell lines and in vivo upon ML364 treatment. These results suggest that targeting USP2 could synergize with anti-PD-1 mAb blockade treatment of murine colon and lung cancers, likely through reshaping the antitumor immune microenvironment and enhancing phagocytosis, which is consistent with a recent report demonstrating that USP2 inhibition sensitizes tumors to PD-1 blockade in breast tumor models via regulating p53 and PD-L1.¹⁶

Furthermore, we also used a breast cancer mouse model, the clinically relevant orthotopic 4T1 tumors, and treated mice with ML364, an anti-PD-1 antibody, alone or in combination, to assess if the USP2 inhibitor can augment the PD-1 blockade efficacy in vivo (figure 5L). Notably, bioluminescence imaging (BLI) of tumor growth showed that a combination of ML364 and anti-PD-1 antibody dramatically suppressed tumor development, compared with ML364 or anti-PD-1 monotherapy (figure 5M,N). These results suggest that inhibition of USP2 by ML364 treatment likely sensitizes tumors to anti-PD-1 immunotherapy in the syngeneic 4T1 breast tumor model.

To further determine whether the tumor suppressive effects mediated by ML364 and anti-PD-1 mAb combination therapy depend on macrophages and/or CD8⁺ T cells in mice bearing subcutaneous CT26 tumors or orthotopic 4T1 tumors, we used the anti-F4/80 antibody and the anti-CD8α antibody to deplete macrophages or CD8+ T cells, respectively (online supplemental figure 7N,O). The tumor growth and BLI imaging analysis showed that depletion of either macrophages or CD8 T cells could significantly reduce the tumor suppressive effects of ML364 and anti-PD-1 mAb combination therapy. Depleting both macrophages and CD8⁺ T cells could completely abolish the tumor suppressive effects of ML364 and anti-PD-1 mAb combination therapy (figure 5O–Q, online supplemental figure 7P–R). These results suggest that the ML364 and anti-PD-1 mAb combination therapy inhibits tumor growth through the cooperative functions of both macrophage-mediated phagocytosis and CD8⁺ T cell-mediated tumor killing.

To further investigate whether the therapeutic benefits of ML364 treatment are mainly mediated through CD47, we generated Cd47 KO CT26 cells. In these Cd47-null CT26 cells, we found that the USP2 inhibitor ML364 did not significantly inhibit tumor growth or enhance the efficacy of anti-PD-1 mAb treatment (figure 6A–C). These results indicate that CD47 likely plays an important role in mediating the efficacy of ML364 and anti-PD-1 combination treatment. Moreover, given that macrophages can eliminate cancer cells through phagocytosis, which is regulated by the CD47/SIRPα axis,⁶ we depleted macrophages in mice bearing CT26 tumors with anti-F4/80 mAb. We observed that tumor growth was increased in macrophage-depleted mice compared to the control groups (figure 6D–F). More importantly, ML364 could not further increase the efficacy of anti-PD-1 mAb treatment in macrophage-depleted mice (figure 6D–F). These data suggest that macrophages likely play an important role in USP2 inhibition-mediated tumor suppression. Bioinformatics database analysis showed that low expression of USP2 mRNA or high expression of SPOP mRNA was correlated with worse overall survival rate in some cancers (online supplemental figure 8A–I). On the other hand, lower USP2 expression or higher SPOP expression was correlated with a better response to anti-PD-1 antibody therapy (online supplemental figure 8J–P). These data are consistent with our results that USP2 deubiquitinates CD47, thereby protecting it from proteasome-mediated degradation, while the upstream SPOP tumor suppressor regulates the degradation of USP2 to indirectly reduce CD47 protein stability. This balance of activities regulates CD47 biological activity in macrophage phagocytosis and cancer immunotherapy (figure 6G).

Discussion

Innate immune checkpoints such as the “don’t eat me signal” of CD47/ SIRPα provide promising targets for cancer immunotherapy.⁵ Targeting the CD47-SIRPα axis using blocking antibodies has been shown to suppress tumor progression in several preclinical studies,^{8 9 12} and several clinical trials are in progress to assess the efficacy and safety of the CD47 mAb blockade in treating human cancers.^{31 32} Some trials have been discontinued due to disappointing data or safety concerns (eg, NCT05079230, NCT06046482), and the broad expression pattern of CD47 may contribute to an antigen sink for antibodies. Hence, understanding how the expression of CD47 is regulated provides a new avenue to target the “don’t eat me” signal. CD47 can be regulated by Myc,³³ HIF-1α,³⁴ and NF-κB³⁵ at the transcriptional level, but the regulation of CD47 at the post-translational modification level is just emerging. One such mechanism is the pyroglutamate modification catalyzed by glutaminyl-peptide cyclotransferase-like (QPCTL, also named isoQC), which is essential for the binding of SIRPα to CD47.^{36 37}

Ubiquitination is a reversible enzymatic post-translational modification in which a ubiquitin protein is attached to a substrate protein by ubiquitin E3 ligases but can be removed by DUB enzymes.^{38 39} Ubiquitination plays versatile roles in protein function, ranging from protein degradation to localization and activity.^{38 39} Recently, TRIM21 was identified as an E3 ligase that promotes CD47 poly-ubiquitination and degradation, which is regulated by c-Src-mediated phosphorylation of CD47.¹³ However, the role of DUB enzymes in regulating CD47 is unknown. Here, we identified USP2 as a bona fide DUB enzyme that protects CD47 from proteasome-mediated degradation (figures1 2), which is consistent with a recent independent report.⁴⁰ Compared with the report by Dai et al,⁴⁰ we further revealed a new layer of USP2 regulation mediated by the upstream SPOP E3 ubiquitin ligase. Moreover, we demonstrated that SPOP interacts with USP2, promoting its ubiquitination and subsequent degradation, which in turn facilitates CD47 degradation (figures3 4). These results establish the SPOP/USP2 signaling axis as an important upstream regulator of CD47 protein stability.

The recent development of highly specific DUB inhibitors heralds their emergence as a new class of therapeutic targets.^{41 42} USP2 has been shown to promote tumorigenesis through DUB and stabilizing MDM2⁴³ and cyclin D1.⁴⁴ Targeting USP2 with its inhibitor, ML364, sensitizes tumors to PD-1 blockade in syngeneic mouse breast tumor models via VPRBP-mediated degradation of p53 and PD-L1.¹⁶ We found that both commercially available USP2 inhibitor, ML364, and an orally active, optimized USP2 inhibitor, MS102, could promote the degradation of CD47 by suppressing the catalytic activity of USP2 (figure 1). ML364 enhances macrophage phagocytosis of cancer cells and improves the efficacy of anti-PD-1 blockade for wild-type tumor cells but not for CD47-depleted cells, suggesting an important role of CD47 in the mechanism of ML364-mediated tumor suppression (figures5 6). However, it remains to be evaluated whether other substrates of USP2, such as MDM2,⁴³ cyclin D1,⁴⁴ and VPRBP,¹⁶ also coordinately contribute to the benefits of ML364 treatment.

Taken together, our study not only provides a molecular mechanism for how USP2 directly regulates CD47 protein levels but also reveals the underlying mechanism of SPOP-mediated USP2 degradation, thereby highlighting the rationale for combining USP2 inhibitor treatment with anti-PD-1 immunotherapy to improve the efficacy of cancer treatment.

Materials and methods

Cell culture, transfection, and virus infection

HEK293T, SUM159, MDA-MB-231, HCT116, BT549, MCF-7, H1650, CT26, 4T1, LLC1, Raw 264.7, J774A.1 cells were cultured in Dulbecco’s Modified Eagle’s Medium (Gibco) containing 10% fetal calf serum (Gibco), 100 U penicillin and 100 μg/mL streptomycin (Gibco) in 5% CO₂ at 37°C. Cells at 60–70% confluences were transfected using Lipofectamine 2000 (Invitrogen) or polyethylenimine (Polysciences) transfection reagent in Opti-MEM medium (31985-070, Gibco) according to the manufacturer’s instructions. After 36 hours of transfection, cells were collected and lysed in EBC buffer (50 mM Tris pH 7.5, 120 mM NaCl, 0.5% NP40) supplemented with protease inhibitors (Thermo Fisher) and phosphatase inhibitors (Calbiochem) for immunoblotting and immunoprecipitation analysis. For the lentiviral packaging, HEK293T cells were co-transfected with lentiviral pLKO.1 construct for shRNAs together with packaging plasmids. At 48 and 72 hours post-transfection, the supernatant was harvested and filtered through a 0.45 μm syringe filter and used for infecting cells in the presence of 4 μg/mL polybrene. Infected cells were further selected using hygromycin B (200 μg/mL) or puromycin (1 μg/mL) for 3 days.

Plasmids

CD47 complementary DNA (cDNA) was subcloned into the pEnCMV-HA vector. Flag-USP2 was subcloned into the pEF-Flag-C vector. His-Ub construct was purchased from Addgene (107392). pCMV-GST-SPOP and pcDNA3-HA-SPOP were generated by subcloning SPOP cDNAs into pCMV-GST and pcDNA3 vectors. Various SPOP and USP2 mutants were generated using the QuikChange XL Site-Directed Mutagenesis Kit (Stratagene), according to the manufacturer’s instructions. The following USP2 and SPOP shRNA sequences were inserted into the pLKO.1 vector, respectively.

Human USP2 shRNAs: #1, 5ʹ- CCGCGCTTTGTTGGCTATAAT-3ʹ, #2, 5ʹ- CCATGCTGTTTACAACCTGTA-3ʹ; human SPOP shRNAs: #1, 5ʹ- GATTCAAGAAATTCATCCGTA-3ʹ, #2, 5ʹ- CACAAGGCTATCTTAGCAGCT-3ʹ, #3, 5ʹ- GCAGTGGATTTCATCAACTAT-3ʹ.

Reagents

ML364 (HY-100900), BAY 11-7082 (HY-13453), PR-619 (HY-13814), IU1 (HY-13817), P22077 (HY-13865), ML323 (HY-17543), LDN-57444 (HY-18637), DUB-IN-2 (HY-50737A) and MF-0094 (HY-112438) were purchased from MedChemExpress. ML364 (S6748) and TCID (S7140) were purchased from Selleckchem. HY-13487 and GRL0617 were purchased from MedChemExpress. MG132 (BML-PI102-0005) was purchased from Enzo Life Science, and cycloheximide (C7698-5G) was purchased from Acros Organics. In vivo anti-mouse PD-1 mAb (29F.1A12, BE0273) and control antibody rat IgG2a clone 2A3 (BE0089) were purchased from Bio X Cell.

Immunoblot and immunoprecipitation

For the immunoblotting assay, cells were lysed with EBC buffer (0.5% NP-40, 120 mM NaCl, 50 mM Tris, pH 7.5, phosphatase inhibitors (Calbiochem), and protease inhibitors (Roche). Protein concentrations were measured on a Beckman Coulter DU-800 spectrophotometer using Bio-Rad protein assay reagent (Bio-Rad, name of the kit), and protein samples were added to the loading buffer, followed by boiling for 10 min. For the immunoprecipitation assay, 2 mg of whole-cell lysate protein was incubated with HA-conjugated/Flag/GST-conjugated agarose in a rotator for 4 hours at 4 °C. The immunocomplexes were washed four times with NETN buffer (0.5% NP-40, 1 mM EDTA, 100 mM NaCl, and 20 mM Tris; pH 8.0). Each sample was added to 60 µL 1×loading buffer and boiled for 10 min. Protein samples were resolved by 8–15% sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and transferred to a polyvinylidene difluoride (PVDF) membrane in transfer buffer (25 mM Tris, pH 8.0, 200 mM glycine, 20% methanol). After incubation in blocking solution (5% milk, 20 mM Tris, pH 8.0, 150 mM NaCl, and 0.1% Tween-20) for 1 hour at room temperature, the PVDF membrane was incubated with primary antibodies at 4°C overnight. After washing three times with TBST (tris-buffered saline with 0.1% Tween-20), the PVDF membrane was incubated with a secondary antibody for 1 hour at room temperature. The PVDF membrane was washed three times with TBST buffer before further development of the film. Immunoblotting images were collected with the Epson Scan (V.3.9.3.0US) and quantified with ImageJ software.

Analysis of membrane CD47 by flow cytometry

For cultured tumor cells treated with or without ML364, including CT26, MC38, 4T-1, LLC1, and MDA-MB-231 cells, cells were detached after treatment using 2 mM EDTA in phosphate-buffered saline (PBS) and harvested in a 15 mL tube. Cells were washed once with fluorescence-activated cell sorting (FACS) buffer (PBS, 2% fetal bovine serum (FBS), 0.1 mM EDTA, 0.02% Azide), filtered with a 70 μm cell strainer, adjusted to a cell concentration of 10×10⁶/mL, added 1 μL (1 μg) of mouse Fc block (CD16/32 antibody, clone 2.4G2, Bio X Cell) (for CT26, MC38, 4T-1, LLC1 cells) or 5 μL (2.5 μg) of human Fc block (BD) (for MDA-MB-231 cells) in 100 μL cell suspension, mixed well, and left at room temperature for 10 min. Cells (100 μL) were distributed into each of the FACS tubes, with a total of 1×10⁶ or fewer cells. Add 1 μL of LIVE/DEAD near infrated (NIR) to each tube. (Dissolve Live/Dead NIR in 50 μL dimethylsulfoxide, then 1:20 dilution in FACS buffer), and incubate at room temperature for 15 min. Cells were washed with FACS buffer, centrifuged, and resuspended in 50 μL of FACS buffer. In another tube, the appropriate antibodies were added to 50 μL of FACS buffer to make an antibody solution. Then, 50 μL of cells were combined with 50 μL of antibody solution. Cells were incubated for 30 min at 4°C in the dark, washed two times with FACS buffer. Then, 2% formaldehyde solution (0.5 mL) was added to each tube. The tubes were stored at 4°C in the dark until FACS analysis (BD LSRFortessa X-20). Data were analyzed by FlowJo and GraphPad.

Antibodies

Anti-CD47 (D3O7P) rabbit mAb (63000, 1:1000), PD-L1 Rabbit antibody (13684, 1:3000), p53 Rabbit antibody (2625, 1:3000), Caspase-3 rabbit mAb (9662, 1:1000), Cleaved caspase-3 (Asp175) (5A1E) rabbit mAb (9664, 1:1000), PARP rabbit mAb (9542, 1:1000), Cleaved PARP rabbit mAb (9541, 1:1000) and GST rabbit antibody (2625, 1:3000) were purchased from Cell Signaling Technology. Anti-USP2 Rabbit antibody (AP2131c, 1:1000) was purchased from Abent. Anti-SPOP antibody (16 750–1-AP) was purchased from Proteintech. Anti-Vinculin (VIN-11–5) mouse mAb (V4505, 1:100000), anti-Flag M2 mouse antibody (F3165, 1:3000), anti-Flag rabbit antibody (F7425, 1:3000), and anti-HA rabbit antibody (H6908, 1:3000) were purchased from Sigma-Aldrich. InVivoMAb anti-mouse F4/80 (CI: A3-1, 100 µg per mouse) was purchased from Bio X Cell. InVivoMAb anti-mouse CD8α (clone 2.43, catalog A2102, 200 µg per mouse) was purchased from Bio X Cell.

The following antibodies were used for the flow cytometry analysis. Anti-mouse CD47 (563585, 1:100), anti-mouse FoxP3 (563902, 1:100), and anti-human CD47 (556046, 1:20) were purchased from BD Biosciences. Anti-mouse CD45 (103140, 1:100), anti-mouse CD3 (100355, 1:100), anti-mouse CD4 (100469, 1:200), anti-mouse CD8 (100748, 1:100), anti-mouse F4/80 (123141, 1:100), anti-mouse CD11b (101259, 1:50), anti-mouse CD11c (117353, 1:200), anti-mouse CD86 (105012, 1:200), and anti-mouse CD80 (104724, 1:400), anti-mouse I-A/I-E (107636, 1:50), anti-mouse H-2K^d/H-2D^d (114720, 1:100), anti-mouse Ly-6G (127616, 1:80), anti-mouse Ly-6C (128018, 1:333), anti-mouse CD163 (155316, 1:80), PE anti-human CD172ab (323806, 1:100), mouse IgG1 isotype control (400114, 1:100) antibodies were purchased from BioLegend. Phycoerythrin (PE)-conjugated Calreticulin antibody (CST 19780S) and the PE-conjugated control antibody (CST 5742S) were purchased from Cell Signaling Technology.

Cell fractionation assay

Cells were washed with cold PBS and trypsinized, then counted to adjust the cell numbers for each sample. The whole-cell lysates (WCL) samples were sonicated for 15 s at 20% power three times with 3×SDS loading buffer to obtain the WCL samples. Cell fractionation was performed using a Cell Fractionation Kit (9038, Cell Signaling Technology) to enrich the cytosolic, membrane, and nuclear fractions. The pellet was washed once with cold PBS at each step. Finally, different cellular fractions were analyzed by western blotting.

In vitro deubiquitination assay

HEK293T cells were transfected with His-Ub construct and the indicated constructs. At 36 hours post-transfection, cells were treated with 10 mM MG132 for 12 hours. Cells were lysed in buffer A (6 M guanidine-HCl, 0.1 M Na₂HPO₄/NaH₂PO₄, and 10 mM imidazole, pH 8.0) and sonicated. Lysates were incubated with nickel-nitrilotriacetic acid matrices (QIAGEN) for 4 hours at room temperature. The pull-down samples were washed two times with buffer A, two times with buffer A/TI (one volume of buffer A and three volumes of buffer TI), and once with buffer TI (25 mM Tris-HCl and 20 mM imidazole, pH 6.8).

Protein half-life analysis

Cells were treated with or without cycloheximide (200 µg/mL) (C7698, Sigma) for the indicated times. Cells were collected at the indicated time points, and proteins were resolved by SDS-PAGE for immunoblot analysis. CD47 or USP2 protein band densities were quantified, normalized to vinculin, and then compared with the t=0 time point.

In vitro phagocytosis assay

Human primary macrophages were isolated from peripheral blood mononuclear cells (PBMC). PBMCs were isolated from a healthy donor by adding blood on top of Ficoll-Paque Plus (Cytiva), spinning at 2,000 rpm with no brake. CD14⁺ cells were isolated from PBMC using a CD14⁺ MicroBeads (Miltenyi Biotec). Briefly, resuspend 10×10⁶ PBMC in 80 µL cold magnetic-activated cell sorting (MACS) buffer (PBS, pH 7.2, 0.5% bovine serum albumin (BSA), 2 mM EDTA), and 20 µL of CD14⁺ MicroBeads (Miltenyi) was added to 10×10⁶ total cells. Mix well, incubate at 4°C for 15 min. Cells were washed with 2 mL MACS buffer, centrifuged at 300 g for 10 min. The supernatant was discarded, and the cells were resuspended in 500 µL MACS buffer. The large separation (LS) column (Miltenyi) was assembled in the MACS magnetic separator (Miltenyi) and rinsed with 3 mL MACS buffer. Cell-beads mixture was applied to the column, and the column was washed three times with 3 mL MACS buffer each time. After adding 5 mL MACS buffer onto the column, bead-labeled cells were immediately flushed out, washed once with MACS buffer, and counted. Cells were seeded 0.25×10⁶ CD14⁺ cells per well in a 6-well plate with 20 ng/mL human macrophage colony-stimulating factor (M-CSF) and cultured for 7 days to induce macrophage differentiation; human lipopolysaccharide (LPS) (100 ng/mL) and human interferon-gamma (40 ng/mL) were added, and cells were cultured for an additional 24 hours to activate macrophages.

Murine macrophage cell lines (RAW 264.7 and J774A.1) were purchased from the American Type Culture Collection (ATCC TIB-71 and TIB-67). RAW 264.7 and J774A.1 were seeded in 6-well plates and stimulated with LPS (100 ng/mL) for 24 hours. The cells were then stained with CellTracker CMFDA (Invitrogen C7025). The cell culture media was aspirated from each well of the 6-well plate, and 1.5 mL culture media was added with 1×5-chloromethylfluorescein diacetate (CMFDA) (2 µM). Cells were incubated for 30 min under culture conditions (37°C, 5% CO₂). The media in each well was aspirated from, 3 mL pre-warmed culture media was added, and the cells were incubated for another 30 min under culture conditions and washed three times with pre-warmed culture medium. The remaining media was aspirated, 3 mL of fresh pre-warmed culture media was added in a 1:1 ratio cell number of a different dye (pHrodo, Invitrogen P36600) labeled tumor cells (MDA-MB-231, HCT116, LLC1, and CT26, respectively) treated with 10 μM ML364 for 24 hours (1 µM pHrodo in PBS, staining for 30 min, followed by washing three times with PBS). Cells were then incubated for 3 hours under culture conditions. The culture was gently shaken, the culture medium was aspirated, and 3 mL PBS+2% FBS+0.1 mM EDTA was added to each well, gently shaken, and aspirated immediately. After washing plates three times, for FACS analysis, cells were detached by adding 3 mL of PBS+0.5 mM EDTA, by placing in a 37°C CO₂ incubator for 3–5 min until cells detached, and then harvested by pipetting up and down and transferring into a tube. After centrifugation at 1,000 rpm for 5 min, the supernatant was aspirated. Cells were fixed with 2% formaldehyde (0.5 mL) in PBS for 10 min, filtered with a 70 µm cell strainer, and analyzed using the BD Fortessa X-20 for the percentage of phagocyte cells containing pHrodo+cells. The data were analyzed by FlowJo and GraphPad software. For confocal imaging, macrophages were seeded onto coverslips and subjected to the phagocytosis assay as described above. After co-incubation with tumor cells for 3 hours, the cells were washed three times with PBS and fixed in 4% paraformaldehyde in PBS for 10 min at room temperature. The cells were then washed three additional times with PBS. Coverslips were mounted onto glass slides, and images were acquired using a Zeiss LSM 980 confocal microscope. Image analysis was performed using Fiji software.

In vivo experimental therapy for mouse tumor models

All mouse studies were conducted under a protocol approved by the Harvard Medical School and Beth Israel Deaconess Medical Center (BIDMC) Institutional Animal Care and Use Committee (IACUC) guidelines. Mice were maintained in a pathogen-free environment at a BIDMC animal facility and were handled in strict accordance with Good Animal Practice as defined by the Office of Laboratory Animal Welfare. LLC1 or CT26 tumors were established by subcutaneously injecting 1×10⁵ LLC1 or CT26 tumor cells in 100 µL PBS into the right flank of 6-week-old C57BL/6J (LLC1) or BALB/cJ (CT26) female mice (Jackson Laboratory). Tumor size was measured every 3 days using calipers after implantation, and tumor volume was calculated as length×width²×0.5.

On the 7th day after injection, the tumor-bearing mice were randomly divided into four groups: (1) control antibody group, (2) ML364 group, (3) anti-PD-1 mAb group, and (4) combination therapy with ML364 and anti-PD-1 mAb. Mice were treated by intraperitoneal (i.p.) injection of anti-PD-1 mAb (clone 29F.1A12, 200 µg per mouse) or control antibody (rat IgG2a, clone 2A3, 200 µg per mouse) every 3 days for a total of five treatments or ML364 (10 mg/kg mouse body weight) i.p. injection, once a day for a total of 14 treatments. At the indicated time points after treatment, mice were euthanized, and tumors were harvested, weighed, or prepared for analysis. For survival analysis, the health of mice was monitored daily. Mice were euthanized when the tumor volume reached 1,500 mm³ and were deemed dead. Kaplan-Meier survival curves were analyzed using the log-rank test.

Orthotopic injection of 4T-1-luc2 cells and bioluminescence imaging

4T1-luc2 breast cancer cells stably expressing the firefly luciferase gene (luc2) were orthotopically implanted into the mammary fat pad of 6-week-old female BALB/c mice (Jackson Lab 000651). The mice are anesthetized using the isoflurane method by following the standard operating procedure. A cotton swab with 70% ethanol was used to clean the injection area at the fourth mammary fat pad. Using sterile forceps to gently lift the skin slightly, insert a 27-gage needle subcutaneously near the nipple, then carefully direct the needle tip into the mammary fat pad and slowly inject 50 mL of 0.2 million 4T-1-luc2 cells in PBS into the mammary fat pad. Remove the needle and apply gentle pressure to the injection site with a sterile cotton swab. BLI was performed using the Revvity IVIS Spectrum Imaging System (Revvity, USA) to monitor tumor growth in the 4T1-luc2 mouse orthotopic tumor model. To visualize tumor burden, mice were i.p. injected with D-luciferin at a dose of 150 mg/kg body weight (15.0 mg/mL D-luciferin solution was made by reconstituting 1 g of D-luciferin in 66.6 mL of sterile Ca²⁺ and Mg²⁺-free dulbecco's phosphate-buffered saline (DPBS)). After injection, animals were anesthetized using 2.5% isoflurane and imaged 11 min post-injection, ensuring peak substrate bioavailability by following the imaging time of pioneer experiments. Images were acquired using the IVIS Spectrum under the following standard settings: (exposure time: automatic, binning: 1–16, field of view: adjusted to include all animals, emission filter: open, subject height: 1.5 cm). Images were analyzed using Living Image software (V.4.8.2) (Revvity, USA). Regions of interest (ROIs) were drawn manually over the tumor sites, and total photon flux (photons/sec) was quantified for each ROI. The background signal was subtracted using an ROI placed over a non-tumor-bearing region of the same mouse. A consistent ROI size and fixed color scale (Min/Max) were applied across all time points and groups. All animal experiments and in vivo BLI imaging procedures were performed under sterile conditions in accordance with the IACUC of Dana-Farber Cancer Institute.

Tumor-infiltrated macrophage phagocytosis analysis

Green fluorescent protein (GFP)-labeled LLC cells (1×10⁶) were implanted subcutaneously into the right flank of 6-week-old C57BL/6J mice. Following the indicated treatments, mice were sacrificed using CO_₂ asphyxiation, and the tumors were collected. The isolated tumors were fixed in formalin and embedded in paraffin, and 2 µm sections were generated. After dewaxing and rehydration, sections were post-fixed with 4% paraformaldehyde and subjected to antigen retrieval. Staining of tumor tissues was performed according to the multiplex immunohistochemistry (mIHC) protocol. Primary antibodies (rabbit anti-mouse F4/80 mAb and anti-GFP pAb) were applied either for 1 hour at 37°C or overnight at 4°C. Following TBST washes, slides were incubated with the corresponding secondary antibodies and fluorophores using the mIHC kit (NEL811001KT, Akoya Biosciences) according to the manufacturer’s protocol. Imaging was carried out on an Akoya Vectra 3 system. Macrophage phagocytosis of tumor cells was quantified by identifying fused yellow cells generated by the overlap of GFP-positive tumor cells (green) and F4/80-positive macrophages (red) in high-power fields.

TIL isolation and flow cytometry

Tumor-bearing mice were euthanized, and tumors were resected on day 16 after tumor cell inoculation. Each tumor tissue was chopped and minced into approximately 1–3 mm pieces and transferred into a 15 mL tube. Tumor dissociation buffer (Roswell Park Memorial Institute medium (RPMI)-1640, 5% FBS, 1 mg/mL Collagenase IV (Sigma), 200 U/mL DNase I (Roche)) was added to each tube containing minced tumor tissue samples. All samples were incubated at 37°C for 20 min on a rotator with mild rotation. Then, all samples were passed through a 70 µM cell strainer and centrifuged at 1,900 rpm for 5 min. The supernatant was discarded, and 2 mL of RBC (red blood cell) lysis buffer was added to each sample. Mix well and leave at room temperature for 2 min. Samples were then washed with MACS buffer and centrifuged at 1,400 rpm for 5 min. After Percoll (GE HealthCare) gradient centrifugation (2,000 rpm, 30 min, room temperature, no brake), the mononuclear cell layer was harvested. The pellet was washed with MACS buffer, cell numbers were counted, and the cells were distributed in 96-well plates and stained with antibodies.

The tumor-infiltrating lymphocytes (TILs) were isolated and distributed to a 96-well plate with cell numbers <1×10⁶/well in 100 µL of MACS buffer. The cells were then stained with Zombie LIVE-DEAD Fixable NIR dye (BioLegend) to distinguish between live and dead cells. After washing once, the cells were incubated with an Fc block (anti-mouse CD16/CD32 mAb, clone 2.4G2, Bio X Cell) for 15 min at room temperature. Without washing, the cells were stained for cell surface markers and intracellular staining. For cell surface markers staining, the antibody master mix (mix all antibodies together) was added to each of the samples, incubated for 30 min at room temperature in the dark, and washed two times with MACS buffer. The cell pellet was resuspended in 100 µL of 1×fixation/permeabilization buffer (eBioscience) and incubated for 30 min at room temperature in the dark. After incubation, 200 µL of 1×permeabilization buffer was added to each sample, and the supernatant was removed and washed once with 200 µL 1×permeabilization buffer. Then, 50 µL of 1×permeabilization buffer was added to each of the samples to resuspend the cells, and then 50 µL of antibody master mix in 1×permeabilization buffer was added for intracellular and nuclear proteins. Each sample was washed two times with 200 µL of 1×permeabilization buffer. After the last wash, the cells were resuspended in 200 MACS buffer, and flow cytometry analysis was performed using a BD LSRFortessa X-20 Analyzer with BD FACSDiva software to collect data. FlowJo V.10.10.0 was used to analyze the flow cytometry data.

Apoptosis assay

Apoptosis assay was performed using BD Apoptosis Annexin V Detection Assay kit (Catalog number 556547). Briefly, the tumor cells were treated with indicated ML364 concentration for 24 hours. Cells were washed twice with PBS, detached by incubating 5 minutes at 37ºC with 2 mM EDTA in PBS, and filtered with 70 µm cell strainer. Cells were washed with cold PBS and resuspended in 1 x Annexin V binding buffer at 1x10⁶ cells/ml. 100 µL of the cell suspension (0.1x 10 cells) was transferred to a 5 ml tube. 5 µL of FITC Annexin V solution and 5 µL PI solution were added, mixed by gently vortexing, and incubated for 15 minutes at room temperature in the dark. 400 µL of 1 x Annexin V binding buffer was added and the cells analyzed by Flow cytometry within one hour. Data was analyzed with Flow Jo 10.10.0.

RNA isolation and reverse transcription quantitative PCR assay

Total RNA from cultured cells was extracted from cultured cells using TRIzol (15596018, Invitrogen). Reverse transcription was performed using the PrimeScript RT Reagent Kit (RR470A, TaKaRa) to generate cDNA. Quantitative PCR was performed using the Bio-Rad CFX Connect Real-Time PCR Detection System (Bio-Rad) after mixing the cDNA templates with primers and PerfectStart Green qPCR SuperMix (AQ601; TransGen Biotech). The primers used for reverse transcription quantitative PCR are as follows: Human CD47, forward primer, 5’-TGCGGTTCAGCTCAACTACTG-3’; reverse primer, 5’-GCTTTGCGCCTCCACATTAC-3’; human GAPDH, forward primer, 5’- GGAGCGAGATCCCTCCAAAAT-3’; reverse primer, 5’-GGCTGTTGTCATACTTCTCATGG-3’; human USP2 forward primer, 5’-GGGCTCCATAACGAGGTGAAC-3’; reverse primer, 5’- CTCCACATCTGTCGGCCTTTC-3’.

Quantification and statistical analysis

The majority of the experiments were repeated two or three times. Statistical analyses were performed using GraphPad Software. All quantitative experiments are presented as the mean±SD, as indicated for at least three independent experiments or biological replicates. Statistical analysis was performed using Student’s t-test for group differences. Statistical comparisons of the tumor growth curves were performed using two-way analysis of variance. For animal survival analysis, Kaplan-Meier survival curves were analyzed using the log-rank test. P value <0.05 was considered statistically significant.

Supplementary material

online supplemental file 1

jitc-14-1-s001.docx^{(4.2MB, docx)}

DOI: 10.1136/jitc-2025-013498

Acknowledgements

We thank F Dang, A-H Rezaeian, Z Wang, and other Wei laboratory members for critical reading of the manuscript, as well as members of Dr Wei’s, Dr Freeman’s, and Dr Dai’s laboratories for helpful discussions. We thank Molecular Imaging Core of Dana-Farber Cancer Institute for the assistance on imaging analysis of confocal microscope.

We thank Molecular Imaging Core of Dana-Farber Cancer Institute for the assistance on imaging analysis of confocal microscope.

Footnotes

Funding: This work was supported in part by the NIH grants (R35CA253027 to WW; P50CA101942 to GJF; R00CA259329 to XD) and grants to XD from the National Natural Science Foundation of China (32570843), Jiangsu Province Distinguished Professor fund, and the Fundamental Research Funds for the Central Universities (090614380002; KG202504).

Provenance and peer review: Not commissioned; externally peer reviewed.

Patient consent for publication: Not applicable.

Ethics approval: The Institutional Animal Care and Use Committee (IACUC) at Beth Israel Deaconess Medical Center approved the carried out studies (animal protocol number: 019-2021-24).

Data availability statement

No data are available.

References

1.Freeman GJ, Long AJ, Iwai Y, et al. Engagement of the PD-1 immunoinhibitory receptor by a novel B7 family member leads to negative regulation of lymphocyte activation. J Exp Med. 2000;192:1027–34. doi: 10.1084/jem.192.7.1027. [DOI] [PMC free article] [PubMed] [Google Scholar]
2.Sharma P, Allison JP. The future of immune checkpoint therapy. Science. 2015;348:56–61. doi: 10.1126/science.aaa8172. [DOI] [PubMed] [Google Scholar]
3.Sharpe AH, Pauken KE. The diverse functions of the PD1 inhibitory pathway. Nat Rev Immunol. 2018;18:153–67. doi: 10.1038/nri.2017.108. [DOI] [PubMed] [Google Scholar]
4.Pitt JM, Vétizou M, Daillère R, et al. Resistance Mechanisms to Immune-Checkpoint Blockade in Cancer: Tumor-Intrinsic and -Extrinsic Factors. Immunity. 2016;44:1255–69. doi: 10.1016/j.immuni.2016.06.001. [DOI] [PubMed] [Google Scholar]
5.Demaria O, Cornen S, Daëron M, et al. Harnessing innate immunity in cancer therapy. Nature New Biol. 2019;574:45–56. doi: 10.1038/s41586-019-1593-5. [DOI] [PubMed] [Google Scholar]
6.Feng M, Jiang W, Kim BYS, et al. Phagocytosis checkpoints as new targets for cancer immunotherapy. Nat Rev Cancer. 2019;19:568–86. doi: 10.1038/s41568-019-0183-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
7.Logtenberg MEW, Scheeren FA, Schumacher TN. The CD47-SIRPα Immune Checkpoint. Immunity. 2020;52:742–52. doi: 10.1016/j.immuni.2020.04.011. [DOI] [PMC free article] [PubMed] [Google Scholar]
8.Majeti R, Chao MP, Alizadeh AA, et al. CD47 is an adverse prognostic factor and therapeutic antibody target on human acute myeloid leukemia stem cells. Cell. 2009;138:286–99. doi: 10.1016/j.cell.2009.05.045. [DOI] [PMC free article] [PubMed] [Google Scholar]
9.Willingham SB, Volkmer J-P, Gentles AJ, et al. The CD47-signal regulatory protein alpha (SIRPa) interaction is a therapeutic target for human solid tumors. Proc Natl Acad Sci U S A. 2012;109:6662–7. doi: 10.1073/pnas.1121623109. [DOI] [PMC free article] [PubMed] [Google Scholar]
10.Tseng D, Volkmer J-P, Willingham SB, et al. Anti-CD47 antibody-mediated phagocytosis of cancer by macrophages primes an effective antitumor T-cell response. Proc Natl Acad Sci U S A. 2013;110:11103–8. doi: 10.1073/pnas.1305569110. [DOI] [PMC free article] [PubMed] [Google Scholar]
11.Soto-Pantoja DR, Terabe M, Ghosh A, et al. CD47 in the tumor microenvironment limits cooperation between antitumor T-cell immunity and radiotherapy. Cancer Res. 2014;74:6771–83. doi: 10.1158/0008-5472.CAN-14-0037-T. [DOI] [PMC free article] [PubMed] [Google Scholar]
12.Weiskopf K, Jahchan NS, Schnorr PJ, et al. CD47-blocking immunotherapies stimulate macrophage-mediated destruction of small-cell lung cancer. J Clin Invest. 2016;126:2610–20. doi: 10.1172/JCI81603. [DOI] [PMC free article] [PubMed] [Google Scholar]
13.Du L, Su Z, Wang S, et al. EGFR-Induced and c-Src-Mediated CD47 Phosphorylation Inhibits TRIM21-Dependent Polyubiquitylation and Degradation of CD47 to Promote Tumor Immune Evasion. Adv Sci (Weinh) 2023;10:2206380. doi: 10.1002/advs.202206380. [DOI] [PMC free article] [PubMed] [Google Scholar]
14.Davis MI, Pragani R, Fox JT, et al. Small Molecule Inhibition of the Ubiquitin-specific Protease USP2 Accelerates cyclin D1 Degradation and Leads to Cell Cycle Arrest in Colorectal Cancer and Mantle Cell Lymphoma Models. J Biol Chem. 2016;291:24628–40. doi: 10.1074/jbc.M116.738567. [DOI] [PMC free article] [PubMed] [Google Scholar]
15.Dang F, Bai L, Dong J, et al. USP2 inhibition prevents infection with ACE2-dependent coronaviruses in vitro and is protective against SARS-CoV-2 in mice. Sci Transl Med. 2023;15:eadh7668. doi: 10.1126/scitranslmed.adh7668. [DOI] [PMC free article] [PubMed] [Google Scholar]
16.Yi J, Tavana O, Li H, et al. Targeting USP2 regulation of VPRBP-mediated degradation of p53 and PD-L1 for cancer therapy. Nat Commun. 2023;14:1941. doi: 10.1038/s41467-023-37617-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
17.Wang Z, Song Y, Ye M, et al. The diverse roles of SPOP in prostate cancer and kidney cancer. Nat Rev Urol. 2020;17:339–50. doi: 10.1038/s41585-020-0314-z. [DOI] [PubMed] [Google Scholar]
18.Guo Z-Q, Zheng T, Chen B, et al. Small-Molecule Targeting of E3 Ligase Adaptor SPOP in Kidney Cancer. Cancer Cell. 2016;30:474–84. doi: 10.1016/j.ccell.2016.08.003. [DOI] [PubMed] [Google Scholar]
19.Zhuang M, Calabrese MF, Liu J, et al. Structures of SPOP-substrate complexes: insights into molecular architectures of BTB-Cul3 ubiquitin ligases. Mol Cell. 2009;36:39–50. doi: 10.1016/j.molcel.2009.09.022. [DOI] [PMC free article] [PubMed] [Google Scholar]
20.Geng C, He B, Xu L, et al. Prostate cancer-associated mutations in speckle-type POZ protein (SPOP) regulate steroid receptor coactivator 3 protein turnover. Proc Natl Acad Sci U S A. 2013;110:6997–7002. doi: 10.1073/pnas.1304502110. [DOI] [PMC free article] [PubMed] [Google Scholar]
21.Gan W, Dai X, Lunardi A, et al. SPOP Promotes Ubiquitination and Degradation of the ERG Oncoprotein to Suppress Prostate Cancer Progression. Mol Cell. 2015;59:917–30. doi: 10.1016/j.molcel.2015.07.026. [DOI] [PMC free article] [PubMed] [Google Scholar]
22.Zhang J, Bu X, Wang H, et al. Cyclin D–CDK4 kinase destabilizes PD-L1 via cullin 3–SPOP to control cancer immune surveillance. Nature New Biol. 2018;553:91–5. doi: 10.1038/nature25015. [DOI] [PMC free article] [PubMed] [Google Scholar]
23.Advani R, Flinn I, Popplewell L, et al. CD47 Blockade by Hu5F9-G4 and Rituximab in Non-Hodgkin’s Lymphoma. N Engl J Med. 2018;379:1711–21. doi: 10.1056/NEJMoa1807315. [DOI] [PMC free article] [PubMed] [Google Scholar]
24.Kojima Y, Volkmer J-P, McKenna K, et al. CD47-blocking antibodies restore phagocytosis and prevent atherosclerosis. Nature New Biol. 2016;536:86–90. doi: 10.1038/nature18935. [DOI] [PMC free article] [PubMed] [Google Scholar]
25.Sharma P, Allison JP. Immune checkpoint targeting in cancer therapy: toward combination strategies with curative potential. Cell. 2015;161:205–14. doi: 10.1016/j.cell.2015.03.030. [DOI] [PMC free article] [PubMed] [Google Scholar]
26.Yu G-T, Bu L-L, Huang C-F, et al. PD-1 blockade attenuates immunosuppressive myeloid cells due to inhibition of CD47/SIRPα axis in HPV negative head and neck squamous cell carcinoma. Oncotarget. 2015;6:42067–80. doi: 10.18632/oncotarget.5955. [DOI] [PMC free article] [PubMed] [Google Scholar]
27.Tao H, Qian P, Wang F, et al. Targeting CD47 Enhances the Efficacy of Anti-PD-1 and CTLA-4 in an Esophageal Squamous Cell Cancer Preclinical Model. Oncol Res. 2017;25:1579–87. doi: 10.3727/096504017X14900505020895. [DOI] [PMC free article] [PubMed] [Google Scholar]
28.Dai X, Gao Y, Wei W. Post-translational regulations of PD-L1 and PD-1: Mechanisms and opportunities for combined immunotherapy. Semin Cancer Biol. 2022;85:246–52. doi: 10.1016/j.semcancer.2021.04.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
29.Schwartz AL, Nath PR, Allgauer M, et al. Antisense targeting of CD47 enhances human cytotoxic T-cell activity and increases survival of mice bearing B16 melanoma when combined with anti-CTLA4 and tumor irradiation. Cancer Immunol Immunother. 2019;68:1805–17. doi: 10.1007/s00262-019-02397-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
30.Sun C, Nagaoka K, Kobayashi Y, et al. Neoantigen Dendritic Cell Vaccination Combined with Anti-CD38 and CpG Elicits Anti-Tumor Immunity against the Immune Checkpoint Therapy-Resistant Murine Lung Cancer Cell Line LLC1. Cancers (Basel) 2021;13:5508. doi: 10.3390/cancers13215508. [DOI] [PMC free article] [PubMed] [Google Scholar]
31.Jiang Z, Sun H, Yu J, et al. Targeting CD47 for cancer immunotherapy. J Hematol Oncol. 2021;14:180. doi: 10.1186/s13045-021-01197-w. [DOI] [PMC free article] [PubMed] [Google Scholar]
32.Yang H, Xun Y, You H. The landscape overview of CD47-based immunotherapy for hematological malignancies. Biomark Res. 2023;11:15. doi: 10.1186/s40364-023-00456-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
33.Casey SC, Tong L, Li Y, et al. MYC regulates the antitumor immune response through CD47 and PD-L1. Science. 2016;352:227–31. doi: 10.1126/science.aac9935. [DOI] [PMC free article] [PubMed] [Google Scholar]
34.Zhang H, Lu H, Xiang L, et al. HIF-1 regulates CD47 expression in breast cancer cells to promote evasion of phagocytosis and maintenance of cancer stem cells. Proc Natl Acad Sci USA. 2015;112:E6215–6223. doi: 10.1073/pnas.1520032112. [DOI] [PMC free article] [PubMed] [Google Scholar]
35.Betancur PA, Abraham BJ, Yiu YY, et al. A CD47-associated super-enhancer links pro-inflammatory signalling to CD47 upregulation in breast cancer. Nat Commun. 2017;8:14802. doi: 10.1038/ncomms14802. [DOI] [PMC free article] [PubMed] [Google Scholar]
36.Logtenberg MEW, Jansen JHM, Raaben M, et al. Glutaminyl cyclase is an enzymatic modifier of the CD47- SIRPα axis and a target for cancer immunotherapy. Nat Med. 2019;25:612–9. doi: 10.1038/s41591-019-0356-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
37.Wu Z, Weng L, Zhang T, et al. Identification of Glutaminyl Cyclase isoenzyme isoQC as a regulator of SIRPα-CD47 axis. Cell Res. 2019;29:502–5. doi: 10.1038/s41422-019-0177-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
38.Komander D, Rape M. The ubiquitin code. Annu Rev Biochem. 2012;81:203–29. doi: 10.1146/annurev-biochem-060310-170328. [DOI] [PubMed] [Google Scholar]
39.Cruz Walma DA, Chen Z, Bullock AN, et al. Ubiquitin ligases: guardians of mammalian development. Nat Rev Mol Cell Biol. 2022;23:350–67. doi: 10.1038/s41580-021-00448-5. [DOI] [PubMed] [Google Scholar]
40.Dai P, Sun Y, Huang Z, et al. USP2 inhibition unleashes CD47-restrained phagocytosis and enhances anti-tumor immunity. Nat Commun. 2025;16:4564. doi: 10.1038/s41467-025-59621-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
41.Harrigan JA, Jacq X, Martin NM, et al. Deubiquitylating enzymes and drug discovery: emerging opportunities. Nat Rev Drug Discov. 2018;17:57–78. doi: 10.1038/nrd.2017.152. [DOI] [PMC free article] [PubMed] [Google Scholar]
42.Clague MJ, Urbé S, Komander D. Breaking the chains: deubiquitylating enzyme specificity begets function. Nat Rev Mol Cell Biol. 2019;20:338–52. doi: 10.1038/s41580-019-0099-1. [DOI] [PubMed] [Google Scholar]
43.Stevenson LF, Sparks A, Allende-Vega N, et al. The deubiquitinating enzyme USP2a regulates the p53 pathway by targeting Mdm2. EMBO J. 2007;26:976–86. doi: 10.1038/sj.emboj.7601567. [DOI] [PMC free article] [PubMed] [Google Scholar]
44.Shan J, Zhao W, Gu W. Suppression of cancer cell growth by promoting cyclin D1 degradation. Mol Cell. 2009;36:469–76. doi: 10.1016/j.molcel.2009.10.018. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

online supplemental file 1

jitc-14-1-s001.docx^{(4.2MB, docx)}

DOI: 10.1136/jitc-2025-013498

Data Availability Statement

No data are available.

[R1] 1.Freeman GJ, Long AJ, Iwai Y, et al. Engagement of the PD-1 immunoinhibitory receptor by a novel B7 family member leads to negative regulation of lymphocyte activation. J Exp Med. 2000;192:1027–34. doi: 10.1084/jem.192.7.1027. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R2] 2.Sharma P, Allison JP. The future of immune checkpoint therapy. Science. 2015;348:56–61. doi: 10.1126/science.aaa8172. [DOI] [PubMed] [Google Scholar]

[R3] 3.Sharpe AH, Pauken KE. The diverse functions of the PD1 inhibitory pathway. Nat Rev Immunol. 2018;18:153–67. doi: 10.1038/nri.2017.108. [DOI] [PubMed] [Google Scholar]

[R4] 4.Pitt JM, Vétizou M, Daillère R, et al. Resistance Mechanisms to Immune-Checkpoint Blockade in Cancer: Tumor-Intrinsic and -Extrinsic Factors. Immunity. 2016;44:1255–69. doi: 10.1016/j.immuni.2016.06.001. [DOI] [PubMed] [Google Scholar]

[R5] 5.Demaria O, Cornen S, Daëron M, et al. Harnessing innate immunity in cancer therapy. Nature New Biol. 2019;574:45–56. doi: 10.1038/s41586-019-1593-5. [DOI] [PubMed] [Google Scholar]

[R6] 6.Feng M, Jiang W, Kim BYS, et al. Phagocytosis checkpoints as new targets for cancer immunotherapy. Nat Rev Cancer. 2019;19:568–86. doi: 10.1038/s41568-019-0183-z. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R7] 7.Logtenberg MEW, Scheeren FA, Schumacher TN. The CD47-SIRPα Immune Checkpoint. Immunity. 2020;52:742–52. doi: 10.1016/j.immuni.2020.04.011. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R8] 8.Majeti R, Chao MP, Alizadeh AA, et al. CD47 is an adverse prognostic factor and therapeutic antibody target on human acute myeloid leukemia stem cells. Cell. 2009;138:286–99. doi: 10.1016/j.cell.2009.05.045. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R9] 9.Willingham SB, Volkmer J-P, Gentles AJ, et al. The CD47-signal regulatory protein alpha (SIRPa) interaction is a therapeutic target for human solid tumors. Proc Natl Acad Sci U S A. 2012;109:6662–7. doi: 10.1073/pnas.1121623109. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R10] 10.Tseng D, Volkmer J-P, Willingham SB, et al. Anti-CD47 antibody-mediated phagocytosis of cancer by macrophages primes an effective antitumor T-cell response. Proc Natl Acad Sci U S A. 2013;110:11103–8. doi: 10.1073/pnas.1305569110. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R11] 11.Soto-Pantoja DR, Terabe M, Ghosh A, et al. CD47 in the tumor microenvironment limits cooperation between antitumor T-cell immunity and radiotherapy. Cancer Res. 2014;74:6771–83. doi: 10.1158/0008-5472.CAN-14-0037-T. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R12] 12.Weiskopf K, Jahchan NS, Schnorr PJ, et al. CD47-blocking immunotherapies stimulate macrophage-mediated destruction of small-cell lung cancer. J Clin Invest. 2016;126:2610–20. doi: 10.1172/JCI81603. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R13] 13.Du L, Su Z, Wang S, et al. EGFR-Induced and c-Src-Mediated CD47 Phosphorylation Inhibits TRIM21-Dependent Polyubiquitylation and Degradation of CD47 to Promote Tumor Immune Evasion. Adv Sci (Weinh) 2023;10:2206380. doi: 10.1002/advs.202206380. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R14] 14.Davis MI, Pragani R, Fox JT, et al. Small Molecule Inhibition of the Ubiquitin-specific Protease USP2 Accelerates cyclin D1 Degradation and Leads to Cell Cycle Arrest in Colorectal Cancer and Mantle Cell Lymphoma Models. J Biol Chem. 2016;291:24628–40. doi: 10.1074/jbc.M116.738567. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R15] 15.Dang F, Bai L, Dong J, et al. USP2 inhibition prevents infection with ACE2-dependent coronaviruses in vitro and is protective against SARS-CoV-2 in mice. Sci Transl Med. 2023;15:eadh7668. doi: 10.1126/scitranslmed.adh7668. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R16] 16.Yi J, Tavana O, Li H, et al. Targeting USP2 regulation of VPRBP-mediated degradation of p53 and PD-L1 for cancer therapy. Nat Commun. 2023;14:1941. doi: 10.1038/s41467-023-37617-3. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R17] 17.Wang Z, Song Y, Ye M, et al. The diverse roles of SPOP in prostate cancer and kidney cancer. Nat Rev Urol. 2020;17:339–50. doi: 10.1038/s41585-020-0314-z. [DOI] [PubMed] [Google Scholar]

[R18] 18.Guo Z-Q, Zheng T, Chen B, et al. Small-Molecule Targeting of E3 Ligase Adaptor SPOP in Kidney Cancer. Cancer Cell. 2016;30:474–84. doi: 10.1016/j.ccell.2016.08.003. [DOI] [PubMed] [Google Scholar]

[R19] 19.Zhuang M, Calabrese MF, Liu J, et al. Structures of SPOP-substrate complexes: insights into molecular architectures of BTB-Cul3 ubiquitin ligases. Mol Cell. 2009;36:39–50. doi: 10.1016/j.molcel.2009.09.022. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R20] 20.Geng C, He B, Xu L, et al. Prostate cancer-associated mutations in speckle-type POZ protein (SPOP) regulate steroid receptor coactivator 3 protein turnover. Proc Natl Acad Sci U S A. 2013;110:6997–7002. doi: 10.1073/pnas.1304502110. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R21] 21.Gan W, Dai X, Lunardi A, et al. SPOP Promotes Ubiquitination and Degradation of the ERG Oncoprotein to Suppress Prostate Cancer Progression. Mol Cell. 2015;59:917–30. doi: 10.1016/j.molcel.2015.07.026. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R22] 22.Zhang J, Bu X, Wang H, et al. Cyclin D–CDK4 kinase destabilizes PD-L1 via cullin 3–SPOP to control cancer immune surveillance. Nature New Biol. 2018;553:91–5. doi: 10.1038/nature25015. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R23] 23.Advani R, Flinn I, Popplewell L, et al. CD47 Blockade by Hu5F9-G4 and Rituximab in Non-Hodgkin’s Lymphoma. N Engl J Med. 2018;379:1711–21. doi: 10.1056/NEJMoa1807315. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R24] 24.Kojima Y, Volkmer J-P, McKenna K, et al. CD47-blocking antibodies restore phagocytosis and prevent atherosclerosis. Nature New Biol. 2016;536:86–90. doi: 10.1038/nature18935. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R25] 25.Sharma P, Allison JP. Immune checkpoint targeting in cancer therapy: toward combination strategies with curative potential. Cell. 2015;161:205–14. doi: 10.1016/j.cell.2015.03.030. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R26] 26.Yu G-T, Bu L-L, Huang C-F, et al. PD-1 blockade attenuates immunosuppressive myeloid cells due to inhibition of CD47/SIRPα axis in HPV negative head and neck squamous cell carcinoma. Oncotarget. 2015;6:42067–80. doi: 10.18632/oncotarget.5955. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R27] 27.Tao H, Qian P, Wang F, et al. Targeting CD47 Enhances the Efficacy of Anti-PD-1 and CTLA-4 in an Esophageal Squamous Cell Cancer Preclinical Model. Oncol Res. 2017;25:1579–87. doi: 10.3727/096504017X14900505020895. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R28] 28.Dai X, Gao Y, Wei W. Post-translational regulations of PD-L1 and PD-1: Mechanisms and opportunities for combined immunotherapy. Semin Cancer Biol. 2022;85:246–52. doi: 10.1016/j.semcancer.2021.04.002. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R29] 29.Schwartz AL, Nath PR, Allgauer M, et al. Antisense targeting of CD47 enhances human cytotoxic T-cell activity and increases survival of mice bearing B16 melanoma when combined with anti-CTLA4 and tumor irradiation. Cancer Immunol Immunother. 2019;68:1805–17. doi: 10.1007/s00262-019-02397-7. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R30] 30.Sun C, Nagaoka K, Kobayashi Y, et al. Neoantigen Dendritic Cell Vaccination Combined with Anti-CD38 and CpG Elicits Anti-Tumor Immunity against the Immune Checkpoint Therapy-Resistant Murine Lung Cancer Cell Line LLC1. Cancers (Basel) 2021;13:5508. doi: 10.3390/cancers13215508. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R31] 31.Jiang Z, Sun H, Yu J, et al. Targeting CD47 for cancer immunotherapy. J Hematol Oncol. 2021;14:180. doi: 10.1186/s13045-021-01197-w. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R32] 32.Yang H, Xun Y, You H. The landscape overview of CD47-based immunotherapy for hematological malignancies. Biomark Res. 2023;11:15. doi: 10.1186/s40364-023-00456-x. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R33] 33.Casey SC, Tong L, Li Y, et al. MYC regulates the antitumor immune response through CD47 and PD-L1. Science. 2016;352:227–31. doi: 10.1126/science.aac9935. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R34] 34.Zhang H, Lu H, Xiang L, et al. HIF-1 regulates CD47 expression in breast cancer cells to promote evasion of phagocytosis and maintenance of cancer stem cells. Proc Natl Acad Sci USA. 2015;112:E6215–6223. doi: 10.1073/pnas.1520032112. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R35] 35.Betancur PA, Abraham BJ, Yiu YY, et al. A CD47-associated super-enhancer links pro-inflammatory signalling to CD47 upregulation in breast cancer. Nat Commun. 2017;8:14802. doi: 10.1038/ncomms14802. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R36] 36.Logtenberg MEW, Jansen JHM, Raaben M, et al. Glutaminyl cyclase is an enzymatic modifier of the CD47- SIRPα axis and a target for cancer immunotherapy. Nat Med. 2019;25:612–9. doi: 10.1038/s41591-019-0356-z. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R37] 37.Wu Z, Weng L, Zhang T, et al. Identification of Glutaminyl Cyclase isoenzyme isoQC as a regulator of SIRPα-CD47 axis. Cell Res. 2019;29:502–5. doi: 10.1038/s41422-019-0177-0. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R38] 38.Komander D, Rape M. The ubiquitin code. Annu Rev Biochem. 2012;81:203–29. doi: 10.1146/annurev-biochem-060310-170328. [DOI] [PubMed] [Google Scholar]

[R39] 39.Cruz Walma DA, Chen Z, Bullock AN, et al. Ubiquitin ligases: guardians of mammalian development. Nat Rev Mol Cell Biol. 2022;23:350–67. doi: 10.1038/s41580-021-00448-5. [DOI] [PubMed] [Google Scholar]

[R40] 40.Dai P, Sun Y, Huang Z, et al. USP2 inhibition unleashes CD47-restrained phagocytosis and enhances anti-tumor immunity. Nat Commun. 2025;16:4564. doi: 10.1038/s41467-025-59621-5. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R41] 41.Harrigan JA, Jacq X, Martin NM, et al. Deubiquitylating enzymes and drug discovery: emerging opportunities. Nat Rev Drug Discov. 2018;17:57–78. doi: 10.1038/nrd.2017.152. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R42] 42.Clague MJ, Urbé S, Komander D. Breaking the chains: deubiquitylating enzyme specificity begets function. Nat Rev Mol Cell Biol. 2019;20:338–52. doi: 10.1038/s41580-019-0099-1. [DOI] [PubMed] [Google Scholar]

[R43] 43.Stevenson LF, Sparks A, Allende-Vega N, et al. The deubiquitinating enzyme USP2a regulates the p53 pathway by targeting Mdm2. EMBO J. 2007;26:976–86. doi: 10.1038/sj.emboj.7601567. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R44] 44.Shan J, Zhao W, Gu W. Suppression of cancer cell growth by promoting cyclin D1 degradation. Mol Cell. 2009;36:469–76. doi: 10.1016/j.molcel.2009.10.018. [DOI] [PMC free article] [PubMed] [Google Scholar]

PERMALINK

CD47 destabilization via manipulating the SPOP-USP2 axis augments macrophage phagocytosis and cancer immunotherapy

Peiqiang Yan

Xia Bu

Tao Hou

Li Chen

Guoxuan Zhong

Daoyuan Huang

Jingchao Wang

Yihang Qi

Weiwei Jiang

Zhe Li

Xutong Xue

Yang Gao

Jing Liu

Hiroyuki Inuzuka

Gordon J Freeman

Wenyi Wei

Xiaoming Dai

Abstract

Background

Experimental design

Results

Conclusion

WHAT IS ALREADY KNOWN ON THIS TOPIC

WHAT THIS STUDY ADDS

HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY

Introduction

USP2 protects CD47 from proteasome-mediated degradation

USP2 is a physiological deubiquitinating enzyme for CD47

SPOP interacts with and ubiquitinates USP2 to promote its degradation

USP2 inhibition activates macrophage phagocytosis and sensitizes tumors to cancer immunotherapy

Discussion

Materials and methods

Cell culture, transfection, and virus infection

Plasmids

Reagents

Immunoblot and immunoprecipitation

Analysis of membrane CD47 by flow cytometry

Antibodies

Cell fractionation assay

In vitro deubiquitination assay

Protein half-life analysis

In vitro phagocytosis assay

In vivo experimental therapy for mouse tumor models

Orthotopic injection of 4T-1-luc2 cells and bioluminescence imaging

Tumor-infiltrated macrophage phagocytosis analysis

TIL isolation and flow cytometry

Apoptosis assay

RNA isolation and reverse transcription quantitative PCR assay

Quantification and statistical analysis

Supplementary material

Acknowledgements

Footnotes

Data availability statement

References

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

Similar articles

Cited by other articles

Links to NCBI Databases