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Killing tumor-associated bacteria with a liposomal antibiotic generates neoantigens that induce anti-tumor immune responses

Nature Biotechnology (2023)Cite this article

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Abstract

Increasing evidence implicates the tumor microbiota as a factor that can influence cancer progression. In patients with colorectal cancer (CRC), we found that pre-resection antibiotics targeting anaerobic bacteria substantially improved disease-free survival by 25.5%. For mouse studies, we designed an antibiotic silver-tinidazole complex encapsulated in liposomes (LipoAgTNZ) to eliminate tumor-associated bacteria in the primary tumor and liver metastases without causing gut microbiome dysbiosis. Mouse CRC models colonized by tumor-promoting bacteria (Fusobacterium nucleatum spp.) or probiotics (Escherichia coli Nissle spp.) responded to LipoAgTNZ therapy, which enabled more than 70% long-term survival in two F. nucleatum-infected CRC models. The antibiotic treatment generated microbial neoantigens that elicited anti-tumor CD8+ T cells. Heterologous and homologous bacterial epitopes contributed to the immunogenicity, priming T cells to recognize both infected and uninfected tumors. Our strategy targets tumor-associated bacteria to elicit anti-tumoral immunity, paving the way for microbiome–immunotherapy interventions.

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Fig. 1: The class of antibiotics targeting anaerobic bacteria have protective effect on patients with CRC.
Fig. 2: F. nucleatum invaded CT26FL3(Luc/RFP) tumor cells in response to hypoxia.
Fig. 3: Characterization of the pH-sensitive antibiotic liposomes.
Fig. 4: Removing F. nucleatum in the tumor by liposomal antibiotics AgTNZ eradicated CRC.
Fig. 5: T cells from survivors suppressed the growth of both infected and uninfected tumors.
Fig. 6: The killing of tumor-associated bacteria promoted immune recognition of bacterial neoepitopes.

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Data availability

The 16S rRNA data are available through the National Center for Biotechnology Information (NCBI) Sequence Read Archive (accession numbers SRR23197060–SRR23197067, BioProject PRJNA926798). The whole-exome sequencing data are available through the Sequence Read Archive (BioProject PRJNA926643). The genome of Fusobacterium nucleatum subsp. nucleatum ATCC 25586 (GCA_000007325.1) is available on KEGG (https://www.genome.jp/kegg-bin/show_organism?org=fnu). Mus musculus genome (GRCm39 reference annotation release 109) is available at the NCBI (https://www.ncbi.nlm.nih.gov/genome/annotation_euk/Mus_musculus/109/). Fusobacterium nucleatum reference proteome (UP000002521_190304) is available at the European Bioinformatics Institute (https://www.ebi.ac.uk/reference_proteomes/). All other data supporting the findings of this study are available from the corresponding authors upon reasonable request. Source data are provided with this paper.

Code availability

The distance map for FISH images analysis is available on Zenodo (https://doi.org/10.5281/zenodo.8200515)78.

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Acknowledgements

K.-H.L. passed away before the submission of the manuscript. The paper is dedicated in memory of him. We thank the University of North Carolina’s Department of Chemistry Mass Spectrometry Core Laboratory, especially E. D. Weatherspoon, for assistance with mass spectrometry analysis. We thank the University of North Carolina’s Department of Microscopy Services Laboratory, especially V. J. Madden, for assistance with TEM imaging. We thank the University of North Carolina’s Animal Histopathology and Laboratory Medicine Core, especially L. Wang, for assistance with histology and toxicity analysis. We thank the University of North Carolina’s Cryo-EM Core, especially J. Peck, for assistance with cryo-EM imaging. We thank the University of North Carolina’s Nanomedicines Characterization Core Facility, especially M. Sokolsky, for assistance with ICP‒MS analysis. We thank the University of North Carolina’s Microbiome Core Facility for 16S rRNA gene sequencing, the Cancer Center Support Grant (P30 CA016086) and the Center for Gastrointestinal Biology and Disease (P30 DK34987). Figures 2a, 3a, 4a, 4o and 5d and Supplementary Figs. 4a, 6b, 10h and 12a were created with BioRender. The work was supported by NIH grant CA198999 (to L.H. and A.A.), the Fred Eshelman Distinguished Professorship (to L.H.), the Institut National du Cancer (InCa), the Nuovo-Soldati Foundation, Swim Across America and, in part, through NIH/NCI Cancer Center Support Grant P30 CA008748 (to B.R., M.B.F. and O.A.). M.B.F. is funded by NIH T32‐CA009512 and an ASCO Young Investigator Award.

Author information

Authors and Affiliations

  1. Division of Pharmacoengineering and Molecular Pharmaceutics, Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC, USA

    Menglin Wang, Kunyu Qiu, Yu Zhang, Ava Vargason, Yun Liu, Jianfeng Guo, Xuefei Zhou, Juliane Nguyen, Aaron C. Anselmo & Leaf Huang

  2. Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA

    Benoit Rousseau, Oliver Artz & Michael B. Foote

  3. Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC, USA

    Guannan Huang, Janelle C. Arthur & Jenny P.-Y. Ting

  4. Department of Genetics, University of North Carolina, Chapel Hill, NC, USA

    Guannan Huang & Jenny P.-Y. Ting

  5. Department of Microbiology and Immunology, University of North Carolina, Chapel Hill, NC, USA

    Guannan Huang, Janelle C. Arthur & Jenny P.-Y. Ting

  6. Department of Bioinformatics and Computational Biology, University of North Carolina, Chapel Hill, NC, USA

    Hang Su

  7. Health Data and Assessment Department, Data Science and Assessment Division, French National Cancer Institute, Boulogne-Billancourt, France

    Christine Le Bihan-Benjamin & Ines Khati

  8. Natural Products Research Laboratories, Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC, USA

    Yung-Yi Cheng & Kuo-Hsiung Lee

  9. Chinese Medicine Research and Development Center, China Medical University and Hospital, Taichung, Taiwan

    Kuo-Hsiung Lee

  10. Curriculum in Oral and Craniofacial Biomedicine, Division of Oral and Craniofacial Health Sciences, Adams School of Dentistry, University of North Carolina, Chapel Hill, NC, USA

    Michael Z. Miao

  11. Thurston Arthritis Research Center, Division of Rheumatology, Allergy, and Immunology, University of North Carolina, Chapel Hill, NC, USA

    Michael Z. Miao

  12. Department of Radiology and Biomedical Research Imaging Center, University of North Carolina, Chapel Hill, NC, USA

    Yue Sun

  13. Health Survey, Data Science and Assessment Division, French National Cancer Institute, Boulogne Billancourt, France

    Philippe-Jean Bousquet

  14. GERCOR Group, Paris, France

    Marc Hilmi

  15. Medical Oncology Department, Curie Institute, Saint Cloud, France

    Marc Hilmi

  16. Residual Tumor & Response to Treatment Laboratory, RT2Lab, Translational Research Department, INSERM, U932 Immunity and Cancer, Paris, France

    Elise Dumas, Anne-Sophie Hamy & Fabien Reyal

  17. INSERM, U900, Paris, France

    Elise Dumas

  18. MINES ParisTech, PSL Research University, CBIO-Centre for Computational Biology, Paris, France

    Elise Dumas

  19. Department of Medical Oncology, Centre René Hughenin, Saint Cloud, France

    Anne-Sophie Hamy

  20. Department of Surgery, Institut Jean Godinot, Reims, France

    Fabien Reyal

  21. Department of Surgical Oncology, Institut Curie, University of Paris, Paris, France

    Fabien Reyal

  22. BMTCT Program, Division of Hematology, Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC, USA

    Lin Lin & Paul M. Armistead

  23. Department of Internal Medicine, University of North Carolina, Chapel Hill, NC, USA

    Paul M. Armistead

  24. Key Laboratory of Polymer Ecomaterials, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun, China

    Wantong Song

  25. Jilin Biomedical Polymers Engineering Laboratory, Changchun, China

    Wantong Song

  26. Center for Gastrointestinal Biology and Disease, University of North Carolina, Chapel Hill, NC, USA

    Janelle C. Arthur

  27. Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA

    Yongqun He

  28. Unit for Laboratory Animal Medicine, University of Michigan Medical School, Ann Arbor, MI, USA

    Yongqun He

  29. Department of Microbiology and Immunology, University of Michigan Medical School, Ann Arbor, MI, USA

    Yongqun He

  30. Division of Craniofacial and Surgical Care, School of Dentistry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

    Jenny P.-Y. Ting

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  1. Menglin Wang
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Contributions

L.H., A.A. and M.W. conceived and designed the research. L.H., M.W., K.Q., A.V., A.A., W.S., J.G., J.A., J.N. and J.P.-Y.T. designed the experiments and analyzed the data. B.R., C.L.B.-B., I.K., P.-J.B., M.H., M.F., E.D., A.H. and F.R. generated the database and did methodology, statistical analyses, models and figures for clinical data. O.A. analyzed the whole-genome sequencing data. K.Q. established the culture and plating system for F. nucleatum and modeled the growth curve versus turbidity. G.H. did sample preparation and data analysis for 16S rRNA sequencing. H.S. aligned epitopes from bacteria proteome. Y.H. ran the topology analysis for bacteria genome. Y.-Y.C., K.-H.L. and M.W profiled the pharmacokinetics of the drugs. Y.Z., Y.L. and M.W. sampled the tissues and serum for pharmacokinetic and toxicity assays. M.M. did deconvolution and reconstruction of the images. Y.S. coded for the FISH quantification. J.G., X.Z., Y.Z. and M.W. performed the surgery and in vivo mouse experiments. X.Z. and M.W. did flow cytometry analysis. L.L., P.A. and M.W. purified and analyzed T cell epitopes. M.W. and Y.Z. prepared the frozen sections and immunofluorescence, FISH staining and qPCR assays. M.W., B.R. and L.H. wrote the manuscript.

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Correspondence to Leaf Huang.

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Competing interests

L. Huang: Consultant with PDS Biotechnology and Stemirna Therapeutics. B. Rousseau: Advisory/Consultancy, Speaker Bureau/Expert testimony: Bayer; Advisory/Consultancy, Speaker Bureau/Expert testimony: Roche; Travel/Accommodation/Expenses: Servier; Travel/Accommodation/Expenses: Astellas; Speaker Bureau/Expert testimony: Gilead.

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Supplementary information

Supplementary Information

Supplementary Methods, Supplementary Figs. 1–16 and Supplementary Tables 1–3

Reporting Summary

Supplementary Video

Reconstruction of image of F. nucleatum-infected CT26FL3(Luc/RFP) cells

Supplementary Data

Source Data Supplementary Figs. 4 and 6–14

Source data

Source Data Fig. 1

Statistical Source Data

Source Data Fig. 5

Unprocessed western blots

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Wang, M., Rousseau, B., Qiu, K. et al. Killing tumor-associated bacteria with a liposomal antibiotic generates neoantigens that induce anti-tumor immune responses. Nat Biotechnol (2023). https://doi.org/10.1038/s41587-023-01957-8

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