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CD300ld on pathologically activated neutrophils promotes tumor immune suppression by binding phosphatidylserine on CD8+ T cells

Nature Cancer (2026) Cite this article

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Abstract

The immunosuppressive tumor microenvironment remains a major obstacle to successful immunotherapy. Pathologically activated neutrophils, alternatively termed polymorphonuclear myeloid-derived suppressor cells (PMN-MDSCs), drive tumor immune evasion primarily by inducing CD8+ T cell tolerance. While direct intercellular contact between neutrophils and CD8+ T cells is essential for immunosuppressive activity, the mechanisms mediating this interaction need deeper understanding. We previously reported that CD300ld is required for recruiting PMN-MDSCs into tumors, suppressing T cell activation. Here we show that CD300ld mediates neutrophil-driven contact-dependent suppression of cytotoxic CD8+ T cells by binding to phosphatidylserine (PS). Mice with mutant CD300ld lacking PS-binding capacity exhibit reduced immunosuppressive activity. Blockade of the CD300ld–PS interaction by neutralizing antibodies demonstrates therapeutic efficacy against established tumors and synergizes with anti-PD1. Our findings establish CD300ld–PS-mediated cell contact as a critical mechanism of neutrophil-driven immune evasion, revealing a targetable checkpoint pathway to overcome tumor immune resistance and improve immunotherapy outcomes.

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Fig. 1: CD300ld specifically binds PS.
The alternative text for this image may have been generated using AI.
Fig. 2: CD300ld promotes tumor progression through PS recognition.
The alternative text for this image may have been generated using AI.
Fig. 3: PMN-MDSCs contact PShigh CD8+ T cells through CD300ld.
The alternative text for this image may have been generated using AI.
Fig. 4: PMN-MDSCs impair PShigh CD8+ T cells through CD300ld.
The alternative text for this image may have been generated using AI.
Fig. 5: CD300ld–PS interaction-blocking Ab exhibits antitumor effects.
The alternative text for this image may have been generated using AI.
Fig. 6: Potential clinical benefits by targeting human CD300LD.
The alternative text for this image may have been generated using AI.

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Data availability

The scRNA-seq profile of CD8+ T cells generated in this study was deposited to the Gene Expression Omnibus (GEO) database under accession code GSE295996. The RNA-seq publicly available data used in this study are available from the GEO database under accession codes GSE93157 and GSE199601, European Molecular Biology Laboratory European Bioinformatics Institute database under accession code PRJEB23709 and the Database of Genotypes and Phenotypes under accession code phs000452. All remaining data supporting the findings of this study are available within the article and its Supplementary Information and/or available upon request from the corresponding author. Source data are provided with this paper.

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Acknowledgements

We extend our gratitude to the Core Facility of Shanghai Institute of Biochemistry and Cell Biology for their technical assistance, J. Song at the Hangzhou Institute of Medicine and P. Liu at the Shanghai Jiaotong University for their expertise in liposome preparation, W. Wu at the Chinese Academy of Sciences Center for Excellence in Molecular Cell Science for providing technical support in bioinformatics analysis and J. Ding at the Chinese Academy of Sciences Center for Excellence in Molecular Cell Science for his suggestions on protein purification. We thank OE Biotech for their assistance in the sequencing and bioinformatics analysis. This study was supported by funding from the National Key Research and Development Program of China (2020YFA0509003 to Y.Z. and 2023YFA1801300 to S.H.), the National Natural Science Foundation of China (32521007, 32130024, 32130025 and 32293232 to Y.Z., 32400757 to C.W., 92368102 and 22377126 to S.H. and 22203089 and 22573043 to A.W.), the Strategic Priority Research Program of the Chinese Academy of Science (XDB0990000 to Y.Z.), the LiaoNing Revitalization Talents Program (XLYC2402023 to G.L.) and the China Postdoctoral Science Foundation (2023M743489 to C.W.). We gratefully acknowledge the Support of SANOFI Scholarship Program. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

Author information

Author notes

  1. These authors contributed equally: Chaoxiong Wang, Peixuan Zheng, Anhui Wang, Xinrui Fan, Tianxiang Li.

  2. These authors jointly supervised this work: Dianfan Li, Moubin Lin, Jiayin Peng, Guohui Li, Shuo Han, Yun Zhao.

Authors and Affiliations

  1. Key Laboratory of Multi-Cell Systems, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China

    Chaoxiong Wang  (王超雄), Peixuan Zheng  (郑培宣), Xinrui Fan  (樊昕瑞), Tianxiang Li  (李天翔), Jingjing Hong  (洪晶晶), Runze Wang  (王润泽), Chunyan Zhang  (张春艳), Chaogui Luo  (罗朝桂), Weiwei Yang  (杨巍维), Dong Gao  (高栋), Jiayin Peng  (彭甲银), Shuo Han  (韩硕) & Yun Zhao  (赵允)

  2. College of Basic Medicine, Inner Mongolia Medical University, Hohhot, China

    Chaoxiong Wang  (王超雄)

  3. Interdisciplinary Research Center for Biology and Chemistry, Liaoning Normal University, Dalian, China

    Anhui Wang  (王安辉) & Guohui Li  (李国辉)

  4. Second Department of Thoracic Surgery, Tumor Hospital Affiliated to Xinjiang Medical University, Wulumuqi, China

    Adili Salai  (阿迪力·萨来)

  5. Institute of Pediatrics of Children’s Hospital of Fudan University, the Shanghai Key Laboratory of Medical Epigenetics, the International Co-laboratory of Medical Epigenetics and Metabolism, Ministry of Science and Technology, Institutes of Biomedical Sciences, Fudan University, Shanghai, China

    Min Luo  (罗敏) & Zhigang Lu  (卢智刚)

  6. School of Agriculture and Biotechnology, Sun Yat-Sen University, Shenzhen, China

    Dianfan Li  (李典范)

  7. Center for Clinical Research and Translational Medicine, Yangpu Hospital, Tongji University School of Medicine, Shanghai, China

    Moubin Lin  (林谋斌)

  8. School of Life Science and Technology, ShanghaiTech University, Shanghai, China

    Yun Zhao  (赵允)

  9. School of Life Science, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou, China

    Yun Zhao  (赵允)

Authors
  1. Chaoxiong Wang  (王超雄)
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  2. Peixuan Zheng  (郑培宣)
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  3. Anhui Wang  (王安辉)
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  4. Xinrui Fan  (樊昕瑞)
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  5. Tianxiang Li  (李天翔)
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  6. Jingjing Hong  (洪晶晶)
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  7. Runze Wang  (王润泽)
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  8. Chunyan Zhang  (张春艳)
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  9. Chaogui Luo  (罗朝桂)
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  10. Weiwei Yang  (杨巍维)
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  11. Dong Gao  (高栋)
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  12. Adili Salai  (阿迪力·萨来)
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  13. Min Luo  (罗敏)
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  14. Zhigang Lu  (卢智刚)
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  15. Dianfan Li  (李典范)
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  16. Moubin Lin  (林谋斌)
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  17. Jiayin Peng  (彭甲银)
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  18. Guohui Li  (李国辉)
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  19. Shuo Han  (韩硕)
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  20. Yun Zhao  (赵允)
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Contributions

Y.Z., S.H., G.L., M. Lin, J.P. and D.L. conceptualized the project. C.W., P.Z. and A.W. performed lipid screen experiments and MD simulations analysis. C.W. and P.Z., with help from T.L., R.W., C.Z., C.L., M. Luo and Z.L., performed the subcutaneous and spontaneous tumor models and analyzed the TME. P.Z. and C.W., with help from T.L., R.W., C.Z. and C.L., performed the in vitro molecular and cell experiments. P.Z., with help from J.H., performed the protein purification. C.W. and X.F. performed the proximity labeling-related experiments. M. Lin, W.Y., D.G. and A.S. provided the clinical samples. C.W. and T.L. performed the bioinformatics analysis and analyzed the data. Y.Z., S.H., G.L., M. Lin, J.P., D.L. and C.W. wrote the paper.

Corresponding authors

Correspondence to Dianfan Li  (李典范), Moubin Lin  (林谋斌), Jiayin Peng  (彭甲银), Guohui Li  (李国辉), Shuo Han  (韩硕) or Yun Zhao  (赵允).

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Nature Cancer thanks Vincenzo Bronte, Xiang Zhang and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

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Extended data

Extended Data Fig. 1 CD300ld specifically recognizes and binds phosphatidylserine.

a: Phylogenetic analysis of the CD300 protein family and their lipid-binding characteristics. b: All candidate lipid ligands for CD300ld calculated by induced fit docking and PS was shown. c: Liposome containing PE or PS were incubated with mouse CD300ld-ECD-Fc. Supernatant (S) and pellet (P) fractions were separated by centrifugation and analyzed via western blot. d: SPR assay demonstrating that CD300ld-ECD-Fc binding to PS-containing liposomes is blocked by EDTA. e: Flow cytometry detection of Fc or CD300ld-ECD-Fc binding to mice thymocytes. Gate strategy (left) and quantification of binding signal (right) are shown (e, n = 3 independent samples per group). f: Flow cytometry detection of PS liposome-Cy5 binding to control (293T-Ctrl) or CD300ld-expressing (293T-CD300ld) cells (f, n = 3 independent samples per group). g: Flow cytometry detection of PS liposome-Cy5 binding to WT or KO neutrophils. h: RNA-seq analysis showing the expression (Log2 RPKM) of CD300ld and other PS binding proteins in neutrophils or PMN-MDSCs. Data are presented as mean ± s.e.m. Statistical analysis was performed using Student’s two-sided unpaired t-test (e, f). Data are representative of two (d) or three (c, e, f, g) independent experiments.

Source data

Extended Data Fig. 2 Identifying key amino acid residues involved in CD300ld binding to PS.

a: Schematic of the overall structure of mouse CD300ld structure, with amino acid sequence ranges for each domain indicated. b: Pull-down assay showing the interaction of PS liposomes with either full length of CD300ld-ECD (aa 19-177)-Fc or its IgV domain (aa 19-127)-Fc. Supernatant (S) and pellet (P) fractions were separated by centrifugation and analyzed via western blot. c, d: Flow cytometry detection of apoptotic thymocyte binding by various mouse CD300ld-ECD-Fc mutants. Representative flow cytometry histograms (c) and quantitative analysis (d) are shown (d, n = 3 independent samples per group). e, f: Structure stability assessment of mouse CD300ld-ECD WT and mutants (C62A, D116A) based on root mean square deviation (RMSD, e) and root mean square fluctuation (RMSF, f) from molecular dynamics simulations. Data are representative of three (b, c, d) independent experiments.

Source data

Extended Data Fig. 3 Binding with PS is required for CD300ld-mediated tumor progression.

a, b: B16-F10 tumor growth curves (a) and the percentage of indicated immune cell types (b) in CD300ldfl/flS100a8cre mice (a, b, n = 6 mice). c: In vitro proliferation curves of B16-F10 cells treated with the indicated concentrations of Annexin V protein (c, n = 3 independent samples per group). d: Tumor weight measurements and flow cytometric analysis of CD8+ T cells and PMN-MDSCs on day 15 after B16-F10 inoculation in WT or CD300ld KO mice treated with Hexa-His or Annexin V-His protein (d, WT + His, n = 7 mice; WT + Annexin V, n = 7 mice; KO + His, n = 7 mice; KO + Annexin V, n = 8 mice). e: Tumor growth curves of WT or CD300ld KO mice treated with Isotype or PS Ab starting from day 7 post B16-F10 tumor inoculation (e, n = 7 mice per group). f: Tumor weights in mice treated with Fc, CD300ld-ECD (WT), or its point mutants (C62A or D116A) at day 7 post tumor inoculation (f, Fc, n = 6 mice; ECD (WT), n = 6 mice; ECD (C62A), n = 5 mice; ECD (D116A), n = 5 mice). g: The percentage of indicated immune cell types in the B16-F10 tumors from mice treated with Fc, ECD (WT), ECD (C62A) or ECD (D116A) (g, Fc, n = 6 mice; ECD (WT), n = 5 mice; ECD (C62A), n = 5 mice; ECD (D116A), n = 6 mice). h: Sanger sequencing validation of CD300ld-C62A and CD300ld-D116A mutant mouse strains. Heterozygotes genotypes are shown. i: Flow cytometric quantification of CD300ld expression on peripheral blood neutrophils from CD300ld WT, KO, C62A and D116A mice (n = 6 mice per group). j: PS liposome-binding percentages of PMNs isolated from CD300ld WT, KO, C62A and D116A mice (j, n = 6 mice per group). k: Indicated immune cell percentage in the B16-F10 tumors of indicated mice at day-15 post tumor inoculation as determined by flow cytometry (k, WT n = 9 mice, KO n = 9 mice, C62A n = 8 mice, D116A n = 8 mice). l: Representative images of livers harvested from CD300ld WT, KO, C62A and D116A mice at day 31 following hydrodynamic injection of Akt/Ras (n = 6 mice per group). m: T cell suppression by splenic PMN-MDSCs isolated from CD300ld WT, KO, C62A and D116A B16-F10 tumor-bearing mice (n = 3 independent samples per group). Representative flow cytometry plots are shown. Data are presented as mean ± s.e.m. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001; NS, not significant. Statistical analysis was performed using ordinary one-way ANOVA (d, e, f, g, i, j, k) and Student’s two-sided unpaired t-test (a, b). Data are representative of two (a, b, c) or three (d, e, f, g, i, j, k, l, m) independent experiments.

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Extended Data Fig. 4 CD300ld-PS Interaction Fails to Induce Intracellular Signaling Axis.

a: RT-qPCR detect CD300ld (left) and S100A8 (right) mRNA expression in neutrophils isolated from mouse bone marrow and treated with B16-F10 tumor explant supernatant (TES), PC liposomes and PS liposomes (a, n = 3 independent samples per group). b: Western blot detection of phosphorylated STAT3 (p-STAT3) in neutrophils treated with TES, PC liposomes and PS liposomes. c-d: Suppression of CD8+ T cell proliferation by splenic PMN-MDSCs pre-treated with TES, PC liposomes and PS liposomes. Representative flow cytometry plots (c) and quantification (d) are shown (d, n = 3 independent samples per group). e: Flow cytometry analysis of CD300ld-ECD-Fc or Fc binding to cells from B16-F10 tumor single-cell suspensions (n = 6 independent samples per group). f: B16-F10 tumor cells were treated with CPT (30 µM) and apoptosis were detected by Flow. g: Engulfment of CellTrace Violet (CTV)-labeled apoptotic B16-F10 cells by WT and KO PMN-MDSCs, shown as representative dot plots (left) and quantification (right) (g, n = 4 independent samples per group). Data are presented as mean ± s.e.m. Statistical analysis was performed using ordinary one-way ANOVA. Data are representative of two (f) or three (a, b, c, d, e, g) independent experiments.

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Extended Data Fig. 5 PS-exposed tumor cells promote PMN-MDSC retention via CD300ld.

a: T7E1 digestion assay followed by agarose gel electrophoresis was used to validate CRISPR-mediated disruption of Tmem30a in B16-F10 cells. b: Flow cytometry analysis of surface PS levels in B16-F10-sg-Scramble (Ctrl) and B16-F10-sg-Tmem30a (Tmem30a-KO) cells. Representative dot plots (left) and quantification (right) are shown (n = 3 independent samples per group). c: In vitro proliferation curves of B16-F10 Ctrl and Tmem30a-KO cell (c, n = 3 independent samples per group). d: Tumor growth curves in CD300ld WT or KO mice inoculated with B16-F10 Ctrl or Tmem30a-KO cell (d, WT + Ctrl, n = 8 mice; WT + Tm KO, n = 7 mice; KO + Ctrl, n = 6 mice; KO + Tm KO, n = 6 mice). e: Flow cytometric analysis of CD8+ T cells (left) and PMN-MDSCs (right) in tumors derived from B16-F10 Ctrl or Tmem30a-KO cells at day 16 post tumor inoculation (e, WT + Ctrl, n = 8 mice; WT + Tm KO, n = 7 mice; KO + Ctrl, n = 6 mice; KO + Tm KO, n = 6 mice). f-g: WT mice inoculated with B16-F10 Ctrl or Tmem30a-KO cells were depleted of CD8+ T cells using anti-CD8 antibody. Tumor growth curve (f, n = 5 mice per group) and flow cytometric analysis of tumor-infiltrating PMN-MDSCs (g, n = 5 mice per group) are shown. h-i: Flow cytometric analysis and quantification of CD300ld (h) or CD14 (i) expression on PMN-MDSCs from B16-F10 ctrl and Tmem30a-KO tumor (h, i, n = 5 mice per group). j: T cell suppression activity of PMN-MDSCs isolated from B16-F10 Ctrl and Tmem30a-KO tumors, using a PMN-MDSCs: splenocyte ratio of 1:4 (j, n = 3 independent samples per group). Data are presented as mean ± s.e.m. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001; NS, not significant. Statistical analysis was performed using ordinary one-way ANOVA (d, e, j), and Student’s two-sided unpaired t-test (b, c, f, g, h, i). Data are representative of two (f, j) or three (a, b, c, d, e, h) independent experiments.

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Extended Data Fig. 6 CD300ld mediates PMN-MDSC engagement with PShigh CD8+ T cells.

a: Indicated T cell populations were isolated via FACS from B16-F10 tumors and Cell viability was detected by Flow cytometry (a, n = 3 independent samples per group). b: Percentage of PShigh CD8+ T cells in different organs from B16-F10 tumor-bearing mice, as determined by flow cytometry (b, n = 5 mice per group). c: PShigh and PSlow CD8+ T cells were isolated via FACS from B16-F10 tumors, and expression levels of indicated genes were detected by RT-qPCR (c, n = 3 independent samples per group). d: Cytotoxic activity of OT-1 CD8+ T cells sorted into PShigh and PSlow CD8+ T populations, measured as the percentage of lysed MC38 OVA-expressing tumor cells (d, n = 3 independent samples per group). e: Flow cytometry detection of CD107a positive CD8+ T cells from B16-F10 tumors (e, n = 6 mice per group). f: WT mice bearing B16-F10 tumors were treated with indicated antibodies post tumor inoculation. Tumor growth curves are shown (n = 5 mice). g: Splenocytes were incubated with CD300ld-ECD-Fc or Fc protein for 48 h, Proliferation of CD8+ T cells were assessed by flow cytometry. Representative histograms (left) and statistical analysis (right) are shown (g, n = 3 independent samples per group). h: Flow cytometric analysis of Biotin levels on 293t cells immobilized with or without SrtA protein. i: Flow cytometry analysis (left) and quantification (right) of the ratio of labeled bone marrow-derived DC (BMDC; Biotin+) after co-culture with SrtA+ CD8+ T cells, as determined by flow cytometry (i, n = 3 independent samples per group). j: Flow cytometry analysis and quantification of the ratio of labeled CD300ld WT, C62A, and D116A PMN-MDSCs (Biotin+) after incubation with control or SrtA+ CD8+ T cells (j, n = 4 mice per group). k: Flow cytometry analysis (left) and quantification (right) of the ratio of labeled WT PMN-MDSCs (Biotin+) after co-incubation with total or PShigh SrtA+ CD8+ T cells in the presence of CD300ld-ECD-Fc and Fc protein (k, n = 5 independent samples per group). l: Flow cytometry quantification of the ratio of labeled neutrophils (from tumor-free mice) or PMN-MDSCs (from tumor-bearing mice) after co-incubation with total or SrtA+ CD8+ T cells (l, n = 5 mice per group). Data are presented as mean ± s.e.m. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001; NS, not significant. Statistical analysis was performed using ordinary one-way ANOVA (d, f, g, i, j), Student’s two-sided unpaired t-test (k, l) and Student’s two-sided paired t-test (e). Data are representative of two (a, b, f) or three (c, e, g, h, i, j, k, l) independent experiments.

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Extended Data Fig. 7 PMN-MDSC impair PShigh CD8+ T cells through CD300ld.

a: Flow cytometric quantification of PShigh CD8+ T cells in MC38 tumors from WT or KO mice at day 18 post tumor inoculation (a, n = 5 mice per group). b: Percentage of activated or exhausted CD8+ T cells in PShigh and PSlow CD8+ T cell populations in MC38 tumors from WT or KO mice at day 18 post tumor inoculation, as determined by flow cytometry (b, Gzmb+ n = 8 mice, IFN-γ+ n = 8 mice, PD-1+ Tim3+ n = 5 mice). c: Gene expression profiles of lineage-defining markers from single-cell RNA-seq, used to annotate major cell clusters. d: Merged UMAP embedding and density plots showing the distribution of PShigh and PSlow CD8+ T cells from WT and KO tumors. e: Pathway enrichment analysis of effector CD8+ T cells from WT and KO tumors. f: T cells are colored by pseudotime, with color intensity increasing from naive (dark) to terminally differentiated (bright) cells. g: UMAP plots showing the clustering of myeloid-lymphocyte doublets detected in the scRNA-seq dataset. h: Dot plot showing the expression of myeloid- or lymphocyte-specific genes across the indicated clusters. i: Box plots displaying the number of genes expressed per cell in doublet populations compared to their singlet counterparts (i, lymphocyte n = 27071, myeloid-lymphocyte n = 763, myeloid n = 2343). j: Frequency of myeloid-lymphocyte doublets among total CD8+ cell plus myeloid-lymphocytes in each experimental group. k: Flow cytometry dot plots (left) and quantification (right) showing PS expression levels in CD8+ T cells after 48-h co-culture with WT or KO PMN-MDSCs (k, n = 3 independent samples per group). l: Flow cytometric analysis (left) and quantification (right) of CD300ld expression levels on PMN-MDSCs immobilized with Fc or CD300ld-ECD protein (l, n = 3 independent samples per group). m: Flow cytometric analysis (left) and quantification (right) of SA+ labeling of Fc or CD300ld-ECD-immobilizatd PMN-MDSCs (SA+) following co-incubation with SrtA+ CD8+ T cell (m, n = 3 independent samples per group). The scRNA-seq dataset was generated by pooling cells from five mice per group into one sequencing sample per group (c, d, e, f, g, h, i, j). Data are presented as mean ± s.e.m (k, l, m). For i, the central line represents the mean and the upper and lower edges of the box correspond to the first and third quartiles, respectively; the whiskers extend to the minimum and maximum values. Statistical analysis was performed using ordinary one-way ANOVA (b, i, k, m), and Student’s two-sided unpaired t-test (a, l). For e, the GO enrichment is reported as GeneRatio with BH-adjusted P value, based on one-sided hypergeometric over-representation analysis Data are representative of three (a, b, k, l, m) independent experiments.

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Extended Data Fig. 8 CD300ld blockade antibody abrogates tumor progression.

a: Antibody-mouse CD300ld-ECD binding modes simulated by Alphafold3. Mouse CD300ld shown in purple and antibodies are shown in green as cartoon structure. b: Dot plot shows the total binding energy and PS-binding-pocket energy of screened antibodies. c: Flow cytometry analysis of binding signals from isotype control antibody (Ctrl Ab) or CD300ld-targeting antibody (L14 Ab) in peripheral blood neutrophils from WT and CD300ld KO mice. Representative histograms (left) and quantification (right) are shown (c, n = 3 mice per group). d: Flow cytometry staining of PE-labeled anti-CD300ld antibody (TX69) on WT or KO neutrophils pre-treated with Ctrl Ab or L14 Ab. Histograms (left) and quantification (right) are shown (d, n = 3 mice per group). e: Flow cytometry detection of PS liposome-Cy5 binding to CD300ld WT or KO neutrophils with indicated concentration of antibodies (e, n = 3 mice per group). f: Proportion of labeled PMN-MDSCs (SA+) in spleens (left) and tumors (right) following adoptive transfer of TPL+ CD8+ T cells with Ctrl Ab or L14 Ab treatment (f, n = 4 mice per group). g: Representative photographs (Bar = 1 cm) of the tumors from indicated B16-F10 tumor at day 15 post tumor inoculation. h: Flow cytometric quantification of immune cell subpopulations in B16-F10 tumors from indicated groups (g, h, WT Ctrl Ab n = 9 mice, WT L14 Ab n = 9 mice, LDKO Ctrl Ab n = 7 mice, LDKO L14 Ab n = 7 mice). i: Percentage of PShigh CD8+ T cells in B16-F10 tumors from WT mice treated with Ctrl Ab or L14 Ab at day 15 post tumor inoculation, as determined by flow cytometry (i, n = 6 mice per group). j: Tumor growth curve of B16-F10-bearing WT mice treated with Ctrl Ab or L14 Ab beginning on day 10 post-inoculation (j, Ctrl n = 6 mice, L14 Ab n = 7 mice). k-l: Tumor growth curve (k, n = 6 mice per group) and flow cytometric analysis of PMN-MDSCs recruitment (l, n = 6 mice per group) in B16-F10-bearing mice treated with Ctrl Ab or L14 Ab, followed by CD8+ T cell depletion. Data are presented as mean ± s.e.m. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001; NS, not significant. Statistical analysis was performed using ordinary one-way ANOVA (c, d, e, f, h, k, l), and Student’s two-sided unpaired t-test (i, j). Data are representative of two (j, k, l) or three (c, d, e, f, h, i) independent experiments.

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Extended Data Fig. 9 CD300ld blockade antibody potentiates ICB immunotherapies for tumor clearance and durable protection.

a-c: WT HCC mice were treated with Ctrl Ab or L14 Ab as shown in the schematic diagram and analyzed at day 30 post Akt/Ras hydrodynamic injection. Representative liver images (a, scale bar = 1 cm, n = 10 mice per group), liver-to-body weight ratios (b, n = 10 mice per group), and flow cytometric analysis of immune subpopulations in tumors (c, n = 8 mice per group) are shown. d-e: TC-1 tumor-bearing mice were treated with Ctrl Ab or L14 Ab from day 7 post-inoculation. Tumor growth curves (d) and immune cell profiling by flow cytometry (d, e, n = 7 mice per group) at day 15 are shown. f-h: Renca tumor-bearing mice were treated with Ctrl Ab or L14 Ab from day 7 post-inoculation. Tumor growth (f), weight (g) and immune subpopulation analysis (f, g, h, n = 8 mice per group) were determined at day 17. i: WT mice were treated with anti-PD1 antibody and/or L14 Ab at the indicated time post B16-F10 inoculation. Tumor growth was then measured (i, Isotype n = 15 mice, Anti PD-1 n = 12 mice, L14 Ab n = 14 mice, Combine n = 18 mice). j: Percentage of CD8+ T cells in B16-F10 tumors under the indicated treatment (j, n = 7 mice per group). k-m: WT mice were inoculated with MC38 cells and received the combination treatment of anti-PD1 antibody and/or L14 Ab at the indicated time post tumor inoculation. Cured mice receiving the combination treatment were rechallenged with MC38 cells on day 60. Shown are experimental timeline (k), average tumor growth curves (l) and tumor growth in individual mice (m). (l, m, Isotype n = 10 mice, Anti PD-1 n = 10 mice, L14 Ab n = 10 mice, Combine n = 15 mice). Data are presented as mean ± s.e.m. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001; NS, not significant. Statistical analysis was performed using ordinary one-way ANOVA (i, j, l), and Student’s two-sided unpaired t-test (b, c, d, e, f, g, h). Data are representative of two (d, e) or three (a, b, c, f, g, h, i, j, l) independent experiments.

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Extended Data Fig. 10 Therapeutic targeting of human CD300LD confers anti-tumor benefits in preclinical models.

a-b: HuCD300LD (HuLD) mice bearing B16-F10 tumors were treated with Isotype or PS Ab starting on day 7 post tumor inoculation. Tumor growth curves (a) and percentages of PMN-MDSCs in tumors (b) are shown (a, b, n = 7 mice). c-d: HuLD mice were inoculated with B16-F10 Ctrl or Tmem30a-KO cells. Tumor growth curves (c) and percentages of PMN-MDSCs in tumors (d) are shown (c, d, n = 7 mice). e: Sanger sequencing validation of HuLD-D115A mutant mice. Heterozygous genotypes are shown. f: Flow cytometric quantification of immune cell subpopulations in B16-F10 tumors from indicated groups (f, n = 7 mice). g-h: Suppressive activity of splenic PMN-MDSCs tumor-bearing mice of indicated genotypes (CD300ld WT, KO, huLD and D115A). Representative flow cytometry plots (g) and quantitative analysis (h) are shown (h, n = 3 independent samples per group). i: Proportion of SA+-labeled PMN-MDSCs from indicated genotypes after co-culture with SrtA+ CD8+ T cells (i, n = 3 independent samples per group). j: Microscale thermophoresis (MST) dose-response curve showing the binding affinity between human CD300LD-ECD-Fc and L14-1 Ab. k: Flow cytometric quantification of immune cell subpopulations in B16-F10 tumors from indicated groups (k, n = 6 mice). l: Kaplan-Meier analysis showing SKCM (skin cutaneous melanoma) patients stratified by expression of PShigh CD8+ T cells signature (n = 459 patients). m: Schematic summary of the CD300LD-PS axis mediating neutrophil-driven suppression of CD8+ T cells and its role in anti-tumor immunity. Data are presented as mean ± s.e.m. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001; NS, not significant. Statistical analysis was performed using ordinary one-way ANOVA (f, h, i), Student’s two-sided unpaired t-test (a, b, c, d, k), and log-rank test (l). Data are representative of two (i, j, k) or three (a, b, c, d, f, h) independent experiments.

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Wang, C., Zheng, P., Wang, A. et al. CD300ld on pathologically activated neutrophils promotes tumor immune suppression by binding phosphatidylserine on CD8+ T cells. Nat Cancer (2026). https://doi.org/10.1038/s43018-026-01169-4

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