科技科学

Membranolytic peptide programs immunogenic cell death for cancer therapy

Nature作者：Yueling Yuan2026年8月5日正文已收录本站

Data availability

RNA-seq and scRNA-seq data generated in this study have been deposited in the NCBI Sequence Read Archive under the BioProject accession numbers PRJNA1091224, PRJNA1413508 and PRJNA1417626. Publicly available resources used for analysis include GRCm38 mouse genome assembly (https://www.ncbi.nlm.nih.gov/datasets/genome/GCF_000001635.26/), MSigDB for Hallmark, GO and Reactome gene sets (https://www.gsea-msigdb.org/gsea/msigdb/mouse/genesets.jsp) and the DAVID web server for functional annotation (https://david.ncifcrf.gov). Source data are provided with this paper.

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Acknowledgements

We thank L. Tang (EPFL) for the discussion and X. Xia (Sun Yat-Sen University Cancer Center) for providing the MC38OVA cells. Illustrations were created using BioRender.

Funding

This work was supported by the National Natural Science Foundation of China, 32522050 (Y.B.), 52233015 (J. Cheng), 32371389 (Y.B.), U22A20156 (T.S.), 22422306 (S.X.); National Key R&D Program of China, 2022YFB3804600 (M.X.); the GJYC Program of Guangzhou City 2024D03J0001 (M.X.); and the Science and Technology Planning Project of Guangdong Province, 2023B1212060013 (Y.B.) and 2020B1212030004 (Y.B.).

Author information

Author notes

  1. These authors contributed equally: Yueling Yuan, Lifang Liang, Jie Li

Authors and Affiliations

  1. School of Biomedical Sciences and Engineering, South China University of Technology, Guangzhou, China

    Yueling Yuan, Lifang Liang, Jie Li, Chengrun Li, Jingxian Chen, Zining Wu, Rupei Du, Xiongwei Xiang, Zhouming Zhang, Yuhao Zhang, Kaiting Yang & Menghua Xiong

  2. Guangdong Provincial Key Laboratory of Malignant Tumour Epigenetics and Gene Regulation, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China

    Yueling Yuan, Fuxiang Wang, Chanjuan Su, Fan Lan, Jueqiong Xu, Huosheng Zhou, Long Zou, Songyin Huang & Yan Bao

  3. National Engineering Research Center for Tissue Restoration and Reconstruction, South China University of Technology, Guangzhou, China

    Yueling Yuan, Lifang Liang, Chengrun Li, Jingxian Chen, Zining Wu, Xiongwei Xiang, Zhouming Zhang, Yuhao Zhang, Kaiting Yang & Menghua Xiong

  4. Shenshan Medical Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Shanwei, China

    Yueling Yuan

  5. Jiangsu Province Key Laboratory of Anesthesiology and Brain Science, Xuzhou Medical University, Xuzhou, China

    Jie Li

  6. Nanhai Translational Innovation Center of Precision Immunology, Medical Research Center, Sun Yat-Sen Memorial Hospital, Foshan, China

    Fuxiang Wang, Chanjuan Su, Fan Lan, Huosheng Zhou, Long Zou & Yan Bao

  7. Medical Research Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China

    Kai Yan, Zhibin Zhao & Zhexiong Lian

  8. Key Laboratory of Biomedical Materials of the Ministry of Education, Key Laboratory of Biomedical Engineering of Guangdong Province, and Innovation Center for Tissue Restoration and Reconstruction, South China University of Technology, Guangzhou, China

    Rupei Du & Menghua Xiong

  9. School of Engineering, Westlake University, Hangzhou, China

    Yaofeng Zhou & Jianjun Cheng

  10. State Key Laboratory of Oncology in Southern China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, China

    Yajing Zhang & Penghui Zhou

  11. Key Laboratory of Organ Regeneration and Transplantation of Ministry of Education, The First Hospital, and Institute of Immunology, Jilin University, Changchun, China

    Tianmeng Sun

  12. Department of Polymer Science and Engineering, University of Science and Technology of China, Hefei, China

    Shiyan Xiao

Authors

  1. Yueling Yuan
  2. Lifang Liang
  3. Jie Li
  4. Chengrun Li
  5. Fuxiang Wang
  6. Kai Yan
  7. Chanjuan Su
  8. Jingxian Chen
  9. Fan Lan
  10. Zining Wu
  11. Rupei Du
  12. Yaofeng Zhou
  13. Xiongwei Xiang
  14. Jueqiong Xu
  15. Huosheng Zhou
  16. Long Zou
  17. Zhouming Zhang
  18. Yuhao Zhang
  19. Songyin Huang
  20. Yajing Zhang
  21. Penghui Zhou
  22. Tianmeng Sun
  23. Kaiting Yang
  24. Zhibin Zhao
  25. Zhexiong Lian
  26. Shiyan Xiao
  27. Jianjun Cheng
  28. Yan Bao
  29. Menghua Xiong

Contributions

Y.Y. contributed to the overall coordination and organization of the project, and to the design, data analysis and manuscript writing for studies on the membranolytic and mLCD mode, transcriptomic analyses and part of the animal experiments. L.L. contributed to the design, data analysis and manuscript writing for studies of the immunological effects of MPs and most animal studies. J.L. contributed to the design, synthesis, structural characterization, data analysis and manuscript writing of the peptides. C.L., Z.W. and Yuhao Zhang assisted with polypeptide synthesis and characterization. F.W. performed western blot and RT–qPCR assays. K. Yan, L.Z., Z. Zhang, K. Yang and Z.L. assisted with scRNA-seq analysis. C.S. and H.Z. performed H&E and immunofluorescent staining and analysed the data. J. Chen assisted with confocal imaging and analysis. F.L. assisted with flow cytometry experiments. R.D. contributed to the generation of fluorescent-protein-expressing cell lines. Y. Zhou assisted with TEM experiments. X.X. assisted with the giant unilamellar vesicle study and cell cytotoxicity test. J.X. and S.H. constructed the CRISPR–Cas9 knockout cell lines. Yajing Zhang and P.Z. performed TCR-T studies. T.S. provided OT-I mice and technical support for the related experiments. Z. Zhao provided technical assistance on flow cytometry analyses. S.X. performed and analysed the simulation studies. J. Cheng contributed to the conception and design of the polypeptides and supervised the related experiments. Y.B. and M.X. contributed to the conception and design of the project, supervised all experiments and wrote the manuscript.

Corresponding authors

Correspondence to Shiyan Xiao, Jianjun Cheng, Yan Bao or Menghua Xiong.

Ethics declarations

Competing interests

Y.Y., J.L., Y.B. and M.X. have submitted a patent application (202111564284.3) related to this study. The other authors declare no competing interests.

Peer review

Peer review information

Nature thanks the anonymous reviewers for their contribution to the peer review of this work. Peer reviewer reports are available.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data figures and tables

Extended Data Fig. 1 aMPC16-CA50 activates multiple regulated mLCD pathways without contributing to its cytotoxic effects.

a–e, Activation of multiple regulated mLCD pathways in MC38 cells after aMPC16-CA50 (160 µg ml−1) treatment for varying durations. a, Immunoblotting of p-RIPK1, RIPK1, p-RIPK3, RIPK3, p-MLKL, or MLKL. The combined treatment of TNF, cycloheximide (CHX), and Z-VAD-FMK serves as the positive control. b, Immunoblotting of GSDME-N and GSDMD-N. TNF plus CHX and doxorubicin treatment serves as the positive control for GSDME-N and GSDMD-N induction, respectively. c,d, Lipid peroxidation evaluated by C11-BODIPY 581/591 staining. RSL3 treatment serves as positive control. c, Representative flow cytometry plots of C11-BODIPY 581/591 in MC38 cells. d, Relative lipid ROS is expressed as the ratio of oxidized to reduced C11-BODIPY MFI. e, Immunoblotting of cleaved PARP1 or caspase-3. Doxorubicin treatment serves as positive control. f–h, Viability of MC38 cells after treatment with aMPC16-CA50 (160 µg ml−1) for 24 h in the absence or presence of inhibitors. f, Necroptosis inhibitors: necrostatin-1 (Nec-1), GSK-872, GSK-840, necrosulfonamide (NSA), and GW806742. g, Pyroptosis inhibitors: VX-765, disulfiram (DSF), dimethyl fumarate (DMF), methylcobalamin (MeCbl), and Z-VAD-FMK. h, Ferroptosis inhibitors: N-acetyl-L-cysteine (NAC), deferoxamine (DFO), liproxstatin-1 (Lip-1), and ferrostatin-1 (Fer-1). i–k, Immunoblotting of MLKL (i), GSDME (j), and NINJ1 (k) in MC38 cells deficient for Mlkl (sgMlkl), Gsdme (sgGsdme), and Ninj1 (sgNinj1), respectively. NTC refers to the non-targeting control. l,m, Concentration-dependent cytotoxicity (l) and LDH release (m) induced by aMPC16-CA50 in MC38-sgNTC, MC38-sgMlkl, MC38-sgGsdme, and MC38-sgNinj1 cells after incubation at pH 6.8 for 24 h. n–p, Immunoblotting of HMGB1 in medium supernatants and cell lysate of MC38-sgMlkl (n), MC38-sgGsdme (o), and MC38-sgNinj1 (p) cells incubated with aMPC16-CA50 (160 µg ml−1) at pH 6.8 for varying durations. MC38-sgNTC cells were included as controls. In d,f–h,l,m, data are mean ± s.d., n = 3 biological replicates. Statistical significance was determined using one-way ANOVA with Dunnett’s multiple-comparison test (d). Uncropped immunoblot images are shown in Supplementary Fig. 1.

Extended Data Fig. 2 aMPC16-CA50 induces time-lagged lysosomal-to-plasma membrane rupture and enhances the immunogenicity across .

a–e, Time-lapse confocal imaging of Panc02Gal3-GFP, EO771Gal3-GFP, and A549Gal3-GFP cells incubated with aMPC16-CA50 (160 µg ml−1) and PI (red) at pH 6.8. a, Representative images. Yellow arrowheads indicate the same cell at different time points. Scale bar, 5 µm. b,c, Percentage of cells exhibiting Gal3-GFP puncta (b) and PI-positive staining (c). d, Appearance time of Gal3-GFP puncta in each cell. e, Time interval between Gal3-GFP puncta appearance and PI-positive staining in each cell. f–j, Analysis of CD8+ T cells activation. Peptides concentration, 160 µg ml−1. f, Experimental design. OT-I T cells were co-incubated with BMDCs pre-incubated with MPC16– or aMPC16-CA50–treated Panc02OVA (g,h) or EO771OVA (i,j) cells. Flow cytometry analysis of CD8+ T-cell proliferation (g,i) and expression of IFN-γ, granzyme B, and perforin in CD8+ T cells (h,j). k–m, Prophylactic vaccination efficacy of aMPC16-CA50–treated tumour cells. k, Experimental design. Mice were vaccinated subcutaneously with Panc02 or EO771 cells that had been pretreated with 160 µg ml−1 of either aMPC16-CA50 or MPC16 at pH 6.8 for 24 h. l,m, Tumour growth curves after challenge with viable, syngeneic tumour cells: Panc02 (l) and EO771 (m) cells, in the correspondingly vaccinated mice. In g–j, data are mean ± s.d., n = 3 biological replicates. In l,m, data are mean ± s.e.m., n = 5 mice. Statistical significance was determined using two-way ANOVA with Tukey’s multiple-comparison test (g–j,l,m). In a, representative images from at least two independent experiments. Diagrams in f,k were created using BioRender; Xiong, M. https://biorender.com/p8xag3c (f), https://biorender.com/ap2k7ea (k).

Source data

Extended Data Fig. 3 Potent LMR activity of aMPs is crucial for enhancing the immunogenicity of lytic tumour cells.

a, Schematic illustration of aMPC12-CA50 and aMPC6-CA50. b, Time-dependent helicity recovery of aMPCn-CA50 (100 µg ml−1) upon incubation in buffers of different pH. c, Dye leakage from liposomes upon incubation with aMPCn-CA50 (160 µg ml−1) following preincubation under different pH conditions overnight. d, Concentration- and time-dependent cytotoxicity of aMPCn-CA50 against MC38 cells at pH 7.4 and 6.8 (n = 3 biological replicates). e, Confocal imaging of MC38LAMP1-mCherry cells incubated with aMPCn-CA50-FITC (160 µg ml−1) at pH 6.8 for 1 h. Scale bars, 2 µm. f–k, Time-lapse confocal imaging of MC38Gal3-GFP cells treated with aMPCn-CA50 (160 µg ml−1) and PI (red) at pH 6.8. f, Representative images. Yellow arrowheads indicate the same cell at different time points. Scale bar, 5 µm. g,h, Percentage of MC38Gal3-GFP cells exhibiting Gal3-GFP puncta (g) and PI-positive staining (h). i,j, Time for Gal3-GFP puncta appearance (i) and PI-positive staining (j). k, Time interval between Gal3-GFP puncta appearance and PI-positive staining in each cell. ND refers to not detectable. l,m, Analysis of CD8+ T cells activation. OT-I T cells were co-cultured with BMDCs that had been pre-incubated with MC38OVA cells treated with aMPCn-CA50 (160 µg ml−1) at pH 6.8 for 24 h. Flow cytometry analysis of CD8+ T-cell proliferation (l) and expression of IFN-γ, granzyme B, and perforin in CD8+ T cells (m). n, Confocal imaging of MC38LAMP1-mCherry&Gal3-GFP cells treated with GPN (320 µg ml−1) at pH 6.8 for 1 h. Scale bars, 5 and 1 µm for regular and magnified images, respectively. o, Concentration-dependent cytotoxic effects of GPN on MC38 cells upon incubation at pH 7.4 or 6.8 for 24 h. p,q, RNA-seq analysis of MC38 cells treated with GPN (320 µg ml−1) at pH 6.8 for 24 h versus untreated controls. p, Volcano scatter plots comparing gene expression levels. Upregulated (fold change >2, P < 0.05) and downregulated (fold change <0.5, P < 0.05) genes are depicted as red and blue dots, respectively. q, GSEA of transcriptional profiles using the hallmark gene set from MSigDB. NES: normalized enrichment scores. FDR: false-discovery rate. r–x, Combination of GPN and MPC16 effectively enhances the ability of MC38 cells to stimulate antigen presentation and T cell activation. r, Schematic illustration of sample preparation strategy. MC38OVA or MC38 cells were treated with (1) GPN, (2) the combination of GPN and MPC16, or (3) aMPC16-CA50 at varying concentrations for 24 h; MPC16 (160 µg ml−1) was applied for 1 h. BMDCs were co-incubated with pretreated MC38OVA or MC38 cells, and subsequent with OT-I T cells. Comparisons were made between the combination of MPC16 and GPN versus GPN treatment (s–u), and between the combination of MPC16 and GPN versus aMPC16-CA50 treatment (v–x). Flow cytometry analysis of H-2Kb–SIINFEKL expression on BMDCs (s,v), CD8+ T-cell proliferation (t,w), and expression of IFN-γ, granzyme B, and perforin in CD8+ T cells (u,x). In c,l,m,o,s–x, data are mean ± s.d., and n = 3 biological replicates. In e,f,n, representative images from at least two independent experiments. Statistical significance was determined using DESeq2 (two-sided Wald tests without adjustment) (p), permutation testing with FDR for GSEA (q), one-way ANOVA (l,m), and two-way ANOVA (s–x) with Tukey’s multiple-comparison test. Diagrams in r were created using BioRender; Xiong, M. https://biorender.com/p8xag3c.

Extended Data Fig. 4 Temporally controlled treatment with aMPC16-CA50 and MPC16 modulates the LMR-PMR interval and immunogenicity in lytic MC38 cells.

a, Experimental design. MC38Gal3-GFP or MC38OVA cells were sequentially treated with aMPC16-CA50 (80, 160, or 320 μg ml−1) and MPC16 (160 μg ml−1), while varying the time interval between their additions. b–f, Time-lapse confocal imaging of MC38Gal3-GFP cells. b–d, Representative images from two independent experiments. Scale bar, 5 µm. The concentrations of aMPC16-CA50 in b, c, and d were 80, 160 and 320 µg ml−1, respectively. e, Percentage of Gal3-GFP puncta-positive cells. f, Time interval between Gal3-GFP puncta appearance and PI-positive staining. g,h, Flow cytometry analysis of CD8+ T-cell proliferation (g) and expression of IFN-γ, granzyme B, and perforin in CD8+ T cells (h), following the stimulation schedule depicted in a. i,j, Correlation between CD8+ T-cell proliferation and the time interval between Gal3-GFP puncta appearance and PI-positive staining across treatments. Statistical significance was determined using two-sided Pearson correlation test. In g–i, data are mean ± s.d., and n = 3 biological replicates. Diagrams in a were created using BioRender; Xiong, M. https://biorender.com/p8xag3c.

Extended Data Fig. 5 Cytotoxicity of MPC16 is inhibited in a dose-dependent manner upon its interaction with anionic phospholipids.

a, ITC-determined integrated heat release and equilibrium dissociation constant (Kd) of the interaction between MPC16 and anionic phospholipids (PS and PdI). ΔH, enthalpy change. b, Size change of lipid vehicles when titrated with MPC16. Images of the mixture of MPC16 and phospholipid are shown. c,d, Concentration- and time-dependent cytotoxicity of MPC16 against MC38 cells in the absence or presence of PS (c) or PdI (d) at varying concentrations. e, Concentration- and time-dependent cytotoxicity of MPC16 against MC38 cells in the absence or presence of PS or PdI (160 μg ml−1). In c–e, data are mean ± s.d., and n = 3 biological replicates.

Extended Data Fig. 6 pH dependent cytotoxic effects of aMPC16-DA50 and aMPC16-TA50.

a, Concentration- and time-dependent cytotoxicity of aMPC16-DA50 and aMPC16-TA50 against MC38 cells at pH 7.4 or 6.8. n = 3 biological replicates. b–d, Time-dependent release of cellular contents of MC38 cells incubated with aMPC16-DA50 or aMPC16-TA50 (160 µg ml−1) at pH 6.8 for varying durations. Levels of LDH (b), HMGB1 (c), and total proteins (d) in the supernatant were tested. e, Concentration- and temperature-dependent cytotoxicity of aMPC16-DA50 and aMPC16-TA50 against MC38 cells at pH 6.8 after 2 and 5 h incubation, respectively. f, Cytotoxicity of aMPC16-DA50 and aMPC16-TA50 (160 µg ml−1) against MC38 cells at pH 6.8 without or with the presence of endocytosis inhibitors after 2 and 5 h incubation, respectively. g, Confocal imaging of MC38 cells incubated with aMPC16-DA50-FITC or aMPC16-TA50-FITC (160 µg ml−1, in green) at pH 6.8 for 10 min and 1 h, respectively. Scale bars, 2 µm. h, Time-lapse confocal imaging of MC38GFP/mCherry cells incubated with aMPC16-DA50 (160 µg ml−1) at pH 6.8. Scale bars, 2 µm. i, Flow cytometry analysis of relative MFI of LysoTracker Green in the aMPC16-TA50–treated MC38 cells compared to untreated cells. j, Time-lapse confocal imaging of MC38Gal3-GFP cells upon incubation with aMPC16-TA50-Cy5 (160 µg ml−1, in red) at pH 6.8. After incubating MC38Gal3-GFP cells with aMPC16-TA50-Cy5 for 2 h, free aMPC16-TA50-Cy5 in the medium was washed out prior to time-lapse monitoring. k, Effect of LEIs on the viability of MC38 cells after treatment with aMPC16-TA50 (160 µg ml−1). The LEIs included CA-074-Me (1 µM), E-64d (80 µM), and pepstatin (80 µM). In b,e,f,i,k, data are mean ± s.d., and n = 3 biological replicates. In c,d,g,h,j, representative images from at least two independent experiments. Uncropped immunoblot and gel images are shown in Supplementary Fig. 1. Diagram in j was created using BioRender, Xiong, M. https://biorender.com/p8xag3c.

Extended Data Fig. 7 pH-responsive kinetics of aMPs are crucial in modulating the process of membrane rupture and enhancing the immunogenicity of lytic tumour cells.

a, Schematic illustration of aMPC16-CA30, aMPC16-CA70, and aMPC16-AA50, exhibiting varying pH-responsive kinetics. b, Time-dependent restoration of α-helical conformation of aMPC16-Ax (100 µg ml−1) following incubation in buffers of different pH. c, Dye leakage from liposomes upon incubation with aMPC16-Ax (160 µg ml−1) following preincubation under different pH conditions overnight. d, Concentration- and time-dependent cytotoxicity of aMPC16-Ax against MC38 cells at pH 7.4 and 6.8 (n = 3 biological replicates). e, Confocal imaging of MC38LAMP1-mCherry cells incubated with aMPC16-Ax-FITC (160 µg ml−1, in green) at pH 6.8. Cells were treated with aMPC16-CA30-FITC for 10 min, with aMPC16-CA70-FITC for 1 h, or aMPC16-AA50-FITC for 1 h. Scale bars, 2 µm. f–j, Time-lapse confocal imaging of MC38Gal3-GFP cells treated with aMPC16-Ax (160 µg ml−1) and PI (red) at pH 6.8. f, Representative images. Yellow arrowheads indicate the same cell at different time points. Scale bar, 5 µm. g,h, Percentage of MC38Gal3-GFP cells exhibiting Gal3-GFP puncta (g) and PI-positive staining (h). i, Time for Gal3-GFP puncta appearance. j, Time interval between Gal3-GFP puncta appearance and PI-positive staining in each cell. k,l, Analysis of CD8+ T cells activation. OT-I T cells were co-cultured with BMDCs that had been pre-incubated with MC38OVA cells treated with aMPC16-Ax (160 µg ml−1) at pH 6.8 for 24 h. Flow cytometry analysis of CD8+ T-cell proliferation (k) and expression of IFN-γ, granzyme B, and perforin in CD8+ T cells (l). In c,k,l, data are mean ± s.d., and n = 3 biological replicates. Statistical significance was determined using one-way ANOVA with Tukey’s multiple-comparison test (k,l). Representative images from at least two independent experiments are shown in e,f.

Extended Data Fig. 8 Kinetically programmed aMPs potentiate anti-PD-L1 therapy in the MC38 bilateral.

a, Experimental schedule for tumour inoculation and treatments of mice. Mice bearing bilateral MC38 tumours received i.t. injections of aMPs (125 µg per tumour for each injection) into the right flank tumours and the i.v. administration of anti-PD-L1 (0.75 mg kg−1). b–d, Antitumour efficacy of combined treatment of aMPC16-CAx and anti-PD-L1 (x includes 30, 50, and 70). e–g, Antitumour efficacy of combined treatment of aMPC16-A50 and anti-PD-L1 (A includes CA and AA). h–j, Antitumour efficacy of combined treatment of aMPCn-CA50 and anti-PD-L1 (Cn includes C6, C12, and C16). Chemical structures of aMPs (b,e,h) and tumour growth curves of the injected (c,f,i) and distal (d,g,j) tumours are shown. CR, complete response. In c,d,f,g,i,j, data are mean ± s.e.m., n = 6 mice, and statistical significance was determined using two-way ANOVA followed by Tukey’s multiple-comparison test, comparing aMPC16-CA50 with the indicated groups. Diagram in a was created using BioRender; Xiong, M. https://biorender.com/ap2k7ea.

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Extended Data Fig. 9 Cellular uptake and cytotoxicity of aMPC16-CA50 in MC38 .

a,b, Cellular uptake in various viable cell populations in MC38GFP tumours at 12 and 24 h following i.t. administration of aMPC16-CA50-Cy5 or MPC16-Cy5 (125 μg per mouse). MC38GFP cells express MyrPalm-GFP on the cell membranes. c–g, Cytotoxicity analysis of aMPC16-CA50 and MPC16 in MC38 tumours. c, Experimental design. Following three i.t. administrations of aMPC16-CA50 or MPC16 (125 μg per mouse for each injection), MC38GFP or MC38 tumours were subjected to flow cytometry and histological analyses, respectively. d, Flow cytometry analysis of viable cell numbers across various cell types. e–g, H&E staining and immunofluorescent (IF) staining for CD31 and CD3 on consecutive tumour sections. e, Representative images. Scale bars, 400 and 50 µm for regular and magnified images, respectively. f,g, Quantification of CD31+ endothelial cells (f) and CD3+ T cells (g) in necrotic and non-necrotic area. h–j, Alternating administration of aMPC16-CA50 and MPC16 did not compromise the antitumour efficacy of aMPC16-CA50. h, Experimental schedule for tumour inoculation and treatments. Mice bearing bilateral MC38 tumours received i.t. injections into the right flank tumours of aMPC16-CA50, MPC16, or an alternating combination of both (125 µg per tumour for each injection). anti-PD-L1 was i.v. administrated at a dose of 0.75 mg kg−1. i,j, Tumour growth curves of the injected (i) and distal (j) tumours. CR, complete response. In b,d,f,g,i,j, data are mean ± s.e.m.. n = 3 mice (b), 5 mice (d), 9 mice (f,g), 4 mice (i,j). Statistical significance was determined using two-tailed Mann-Whitney U test (f,g), one-way ANOVA (d) and two-way ANOVA (i,j) with Tukey’s multiple-comparison test. In e, representative images from 9 mice are shown. Diagrams in a,c,h were created using BioRender; Xiong, M. https://biorender.com/ap2k7ea.

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Extended Data Fig. 10 aMPC16-CA50 is systemically administrable to potentiate anti-PD-L1 .

a, MTD of intravenously administered aMPC16-CA50 and MPC16 in ICR mice. n = 6 mice. b, H&E staining of liver sections from ICR mice 24 h after aMPC16-CA50 administration. Scale bars, 50 µm (left) and 20 µm (right). Representative images from three mice are shown. c–k, Antitumour efficacy and T cell activation induced by combination therapy in MC38 tumour models. n = 6 mice. c, The schedule for treatments and sample collection for flow cytometry analysis. Tumour-bearing mice were i.v. administered with aMPC16-CA50 (15 mg kg−1) and anti-PD-L1 (0.75 mg kg−1). d, Growth curves of subcutaneous MC38 tumours. e–i, Flow cytometry analysis of T cells in the tumour (e,f), draining lymph node (g), spleen (h), and blood (i) of subcutaneous MC38 tumour-bearing mice. e,g–i, Percentages of IFN-γ-, granzyme B-, and perforin-positive cells among the CD8+ T cells and IFN-γ-positive cells among the CD4+ T cells. f, Representative plots showing IFN-γ and perforin expression in CD8+ T cells from tumour tissues. j,k, Kaplan–Meier survival curves (j) and bioluminescence imaging (k) of mice bearing peritoneal metastases of luciferase-expressing MC38 tumours. l,m, Growth curves of orthotopic EMT6 breast tumours (l, n = 7 mice) and subcutaneous Panc02 tumours (m, n = 5 mice). Tumour-bearing mice were i.v. administered with aMPC16-CA50 (15 mg kg−1) and anti-PD-L1 (0.75 mg kg−1 in l and 1 mg kg−1 in m). In d,e,g–i,m, data are mean ± s.e.m.. Statistical significance was determined using two-way ANOVA with Tukey’s multiple-comparison test (d,m), one-way ANOVA with Tukey’s multiple-comparison test (e,g–i), and log-rank test (j). Diagrams in c,l,m were created using BioRender; Xiong, M. https://biorender.com/ap2k7ea.

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Extended Data Fig. 11 scRNA-seq transcriptional profiling of CD45+ cells from MC38 tumours.

a, The schedule for tumour inoculation, treatments, and sample collection for scRNA-seq analysis. Mice bearing subcutaneous MC38 tumours were i.v. administered with aMPC16-CA50 (15 mg kg−1) and anti-PD-L1 (0.75 mg kg−1). n = 3 mice. b, Uniform manifold approximation and projection (UMAP) map of CD45+ cells. cDC, conventional DC; mDC, migratory DC; pDC, plasmacytoid DC. c, Bubble plots showing marker differentially expressed genes (DEGs) for major immune cell lineages. DEGs were identified using a two-sided Wilcoxon rank-sum test. d, Heatmaps of scaled GSVA scores for immune signatures. e, Violin plots of signature scores for Interferon-Stimulated Genes50 (Supplementary Table 3). f, Heatmaps showing scaled expression of IFN-I–response and cytokines–associated genes. g, Violin plots showing signature scores for Antigen Processing-Cross Presentation in APCs. h, Heatmaps showing scaled expression of antigen-processing and presentation genes in APCs. i, Violin plots showing signature scores for T cell-Mediated Cytotoxicity in CD8+ T cells. j, Heatmaps showing scaled expression of effector/cytotoxicity genes in CD8+ T cells. In e,g,i, box plots indicate median (middle line), interquartile range (box), and 1.5×IQR (whiskers); cell numbers (n, left to right): CD8+ T cell, 980/1888/2425/3706; CD4+ T cell, 305/548/425/685; NK cell, 208/637/668/1344; cDC, 478/334/403/729; mDC, 263/319/434/456; pDC, 66/59/71/83; macrophage, 8408/6602/5538/9485; monocyte, 720/749/934/2328; B cell, 218/165/183/118. Statistical significance was determined using Kruskal-Wallis H test with Dunn’s post hoc test (e,g,i). Diagram in a was created using BioRender; Xiong, M. https://biorender.com/ap2k7ea.

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Yuan, Y., Liang, L., Li, J. et al. Membranolytic peptide programs immunogenic cell death for cancer therapy. Nature (2026). https://doi.org/10.1038/s41586-026-10899-5

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