IFN-γ-dependent NK cell activation is essential to metastasis suppression by engineered Salmonella

Metastasis accounts for 90% of cancer-related deaths and, currently, there are no effective clinical therapies to block the metastatic cascade. A need to develop novel therapies specifically targeting fundamental metastasis processes remains urgent. Here, we demonstrate that Salmonella YB1, an engineered oxygen-sensitive strain, potently inhibits metastasis of a broad range of cancers. This process requires both IFN-γ and NK cells, as the absence of IFN-γ greatly reduces, whilst depletion of NK cells in vivo completely abolishes, the anti-metastatic ability of Salmonella. Mechanistically, we find that IFN-γ is mainly produced by NK cells during early Salmonella infection, and in turn, IFN-γ promotes the accumulation, activation, and cytotoxicity of NK cells, which kill the metastatic cancer cells thus achieving an anti-metastatic effect. Our findings highlight the significance of a self-regulatory feedback loop of NK cells in inhibiting metastasis, pointing a possible approach to develop anti-metastatic therapies by harnessing the power of NK cells.

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Jiandong Huang
Feb 22, 2021 Luciferase live imaging: Images were taken with the PE IVIS Spectrum in vivo imaging system; Mass cytometry: The samples were acquired on a CyTOF2 (Fluidigm) at an event rate of <500 events/second. Flow Cytometry: BD LSR Fortessa Analyzer, ACEA Novocyte Flow Cytometer were used for the flow cytometric data acquisition.
Luciferase live imaging: Data was analyzed with Living image 4.0 software; Mass cytometry: After the acquisition, the data were normalized using bead-based normalization in the CyTOF software (Version 6.7.1014, Fluidigm). Mass cytometry data were normalized to EQ 4-element bead signal (Lot P15K0802, Passport EQ 4_P13H2302) in 100s interval windows using the normalization function in the CyTOF software (Version 6.7.1014, Fluidigm). Mass tag barcodes were also resolved with a doublet filtering scheme using Debarcoder in the CyTOF software (Version 6.7.1014, Fluidigm). Live immune cells were manually gated in FlowJo by event length, live/dead discrimination, and the desired expression of CD45. Data were then exported for downstream analysis and transformed with a coefficient of 5 with method cytofAsinh. For most downstream analyses, the individual sample data were subsampled to 5000 events (or all events were sampled if total cell number was less than 5,000).All samples had at least 2000 events. t-Distributed Stochastic Neighbor Embedding (t-SNE) dimension reduction and PhenoGraph clustering analyses were performed using the tool cytofkit run in R. No data were excluded.
All attempts at replication were successful. All data in the paper was successfully replicated in at least two independent experiments performed under identical conditions. Cell cultures were regularly checked for mycoplasma. Key results were confirmed in different models. For example, the anti-metastasis effect of YB1 was confirmed in mutiple syngeneic tumor models. The effect of IFN-" was validated by in vivo antibody-dependent depletion and IFN-" knockout mice.
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nature research | reporting summary
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Primarily isolated mouse immune cells and YAC-1 cancer cell line were applied to flow analysis in this study. For cell surface markers detection, immune cells were stained with antibodies for 30 min on ice and washed twice with 1% BSA/PBS before flow cytometric analysis. For intracellular staining, immune cells were induced ex vivo with PMA/ionomycin (or YAC-1 cancer cell) supplemented with brefeldin A for 5 h. After culture, cell mixtures were collected and stained for cell surface markers. Following fixation and permeabilization of cells (BD, catalog no. 554714), cells were stained with intracellular staining antibodies on ice for 30 min and washed twice before flow cytometric analysis.
The stop gating setting for most flow cytometry analysis: the number of singlets should be more than 20000 events; The stop gating setting for flow cytometry-based killing assay: YAC-1 target cells are more than 4000 events (only 10000 cells were seeded into each well); The abundance of relevant cell populations were labeled with percentage in raw PDF data and quantified in main figures.

October 2018
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