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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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.
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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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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 Methods, Supplementary Figs. 1–16 and Supplementary Tables 1–3
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Reconstruction of image of F. nucleatum-infected CT26FL3(Luc/RFP) cells
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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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DOI: https://doi.org/10.1038/s41587-023-01957-8
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