Abstract
Despite the success of PD-1 blockade in melanoma and other cancers, effective treatment strategies to overcome resistance to cancer immunotherapy are lacking1,2. Here we identify the innate immune kinase TANK-binding kinase 1 (TBK1)3 as a candidate immune-evasion gene in a pooled genetic screen4. Using a suite of genetic and pharmacological tools across multiple experimental model systems, we confirm a role for TBK1 as an immune-evasion gene. Targeting TBK1 enhances responses to PD-1 blockade by decreasing the cytotoxicity threshold to effector cytokines (TNF and IFNγ). TBK1 inhibition in combination with PD-1 blockade also demonstrated efficacy using patient-derived tumour models, with concordant findings in matched patient-derived organotypic tumour spheroids and matched patient-derived organoids. Tumour cells lacking TBK1 are primed to undergo RIPK- and caspase-dependent cell death in response to TNF and IFNγ in a JAK–STAT-dependent manner. Taken together, our results demonstrate that targeting TBK1 is an effective strategy to overcome resistance to cancer immunotherapy.
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Data availability
The datasets generated and analysed in this study are included in the Article and its Supplementary Information. In vivo scRNA-seq data have been deposited at the GEO under the accession codes GSE217160 (in vivo TBK1i study) and GSE217274 (in vivo TBK1 CRISPR–Cas9 study) and are available on request. Descriptions of the analyses are provided in the Methods and Reporting summary.
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Acknowledgements
This work was supported by NIH K08CA226391 (to R.W.J.), P01CA24023 (to S.I.P.), K99CA259511 (to K.P.), T32CA207021 (to J.H.C.), 5R01AR072304 (to D.E.F.), 5P01CA163222 (to D.E.F.), 5R01AR043369 (to D.E.F.) and 5R01CA222871 (to D.E.F.). Additional support was provided by the Melanoma Research Alliance Young Investigator Award (https://doi.org/10.48050/pc.gr.86371, to R.W.J.), a Karin Grunebaum Cancer Research Foundation Faculty Research Fellowship (to R.W.J.), Termeer Early Career Fellowship in Systems Pharmacology (to R.W.J.) and a gift from S. B. and J. W. Belkin. K.P. acknowledges support from the German Research Foundation (DFG), Stand Up to Cancer Peggy Prescott Early Career Scientist Award PA-6146, Stand Up to Cancer Phillip A. Sharp Award SU2C-AACR-PS-32; D.J. acknowledges the Susan Eid Tumor Heterogeneity Initiative; and D.E.F. acknowledges grant support from the Dr Miriam and Sheldon G. Adelson Medical Research Foundation. The funding bodies had no role in the design of the study, and the collection, analysis and interpretation of the data, or in writing the manuscript. We thank all members of the Manguso and Jenkins laboratories at MGH, HMS and the Broad Institute. Graphics in Figs. 2a and 5i were created using BioRender.
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Contributions
Conception and experimental design: Y.S., O.-y.R., S.A., C.E.M., P.T., K.B.Y., A.I.-V., R.T.M. and R.W.J. Methodology and data acquisition: Y.S., O.-y.R., S.A., E.A.K., C.H.W., A.J., C.E.M., E.J.R., A.F., X.M., J.G., P.T., A.M.C., M.Q.R., P.S., J.T., A.M., H.X., T.S., S.L., W.A.M., R.S.-B., J.K.E.S., X.Q., G.Z., M.Y.S., J.W.K., S.J.K., D.T.F., D.J., S.I.P., D.M.M., S.S., E.I., A.R.A., C.P.P., D.R.S. and G.M.B. Analysis and interpretation of data: Y.S., O.-y.R., S.A., C.E.M., P.T., T.G.R.D., S.K., P.P.D., J.T., A.M., A.M.S., K.Y., M.S.-F., T.L., J.W.K., K.A.S., A.G.-H., J.H.C., K.P., D.A.B., D.E.F., R.B.C., N.H., P.K.S., K.T.F., G.M.B., R.T.M. and R.W.J. Manuscript writing and revision: Y.S., O.-y.R., S.A., C.E.M., H.X., D.J., D.A.B., R.T.M. and R.W.J.
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Competing interests
R.W.J. is a member of the advisory board for and has a financial interest in Xsphera Biosciences, a company focused on using ex vivo profiling technology to deliver functional, precision immune-oncology solutions for patients, providers and drug development companies. A.M. is a consultant for Third Rock Ventures, Asher Biotherapeutics and Abata Therapeutics; and holds equity in Asher Biotherapeutics and Abata Therapeutics. S.I.P. has received consultancy payments from Abbvie, Astrazeneca/MedImmune, Cue Biopharma, Fusion Pharmaceuticals, MSD/Merck, Newlink Genetics, Oncolys Biopharma, Replimmune, Scopus Biopharma and Sensei Biopharma; she has received grants/research support from Abbvie, Astrazeneca/MedImmune, Cue Biopharma, Merck and Tesaro. S.J.K. has served a consultant/advisory role for Eli Lilly, Merck, BMS, Astellas, Daiichi-Sankyo, Pieris and Natera; and owns stock in Turning Point Therapeutics. D.J. received consulting fees from Novartis, Genentech, Syros, Eisai, Vibliome, Mapkure and Relay Therapeutics; conducted contracted research with Novartis, Genentech, Syros, Pfizer, Eisai, Takeda, Pfizer, Ribon Therapeutics, Infinity, InventisBio and Arvinas; and has ownership interest in Relay Therapeutics and PIC Therapeutics. D.M.M. has received honoraria for participating on advisory boards for Checkpoint Therapeutics, EMD Serono, Castle Biosciences, Pfizer, Merck, Regeneron and Sanofi Genzyme; and owns stock in Checkpoint Therapeutics. D.E.F. has a financial interest in Soltego, a company developing salt-inducible kinase inhibitors for topical skin-darkening treatments that might be used for a broad set of human applications. R.T.M. consults for Bristol Myers Squibb. M.S.-F. receives research funding from Bristol-Meyers Squib.
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Extended data figures and tables
Extended Data Fig. 1 Supporting evidence that loss of TBK1 sensitizes tumours to cancer immunotherapy.
a, Relative depletion/enrichment of Ikbke sgRNAs from a pool of sgRNAs targeting 2,368 genes expressed by Cas9-expressing B16 melanoma cells (n = 4 independent guides targeting each gene; false discovery rate (FDR) was calculated using the STARS algorithm v1.3, as previously described6,7). b, TBK1 and β-actin protein levels in control and Tbk1-null B16 cells. Results are representative of three independent experiments. c, Proliferation of Tbk1-null and control B16 tumour cells following at 1-4 days of in vitro culture (n = 9 per condition from three independent experiments). d, Tumour volume of control (grey), Tbk1-null (light red) B16 tumours in NSG mice (n = 5 mice per group). Mean tumour volumes (solid circles) are shown +/− s.e.m. (shaded region). 2-way ANOVA with Sidak’s multiple comparisons test. e, Spider plots for tumour volume analysis for control sgRNA-1 (black), sgRNA-2 (grey), Tbk1 sgRNA-1 (pink), and Tbk1 sgRNA-2 (red) B16 tumours in anti-PD-1-treated wild-type C57BL/6 mice (see Fig. 1c). f-g, Spider plots for tumour volume analysis (f) and survival (g) for control (black), anti-PD-1 (grey), TBK1i (pink), and anti-PD-1+TBK1i (red) B16 tumours in C57BL/6 mice (see Fig. 1d). For survival analysis (g), pairwise testing was performed using the log-rank (Mantel-Cox) test for survival (g); n = 10 mice per treatment group, ***P < 0.001; ns, not significant, compared to control group. h, body weight of mice bearing B16-ova tumours on Day 14 of indicated treatment. Means (bars) and individual values (open circles) are shown (n = 10 mice per group, 1-way ANOVA with Tukey’s multiple comparisons test; ns, not significant). i, Viability assessment of CT26 MDOTS with indicated treatments. Means (bars) and individual values (open circles) are shown (n = 3, biological replicates, one-way ANOVA with Tukey’s multiple comparisons test; *P < 0.05; **P < 0.01; ***P < 0.001; **** P < 0.0001). j–k, Tumour volume analyses of mice bearing MC38 (j) and MB49 (k) tumours treated with TBK1i, anti-PD-L1, or combination compared to control (IgG + vehicle); n = 10 mice per treatment group. Mean tumour volumes (solid circles) are shown +/− s.e.m. (shaded region). 2-way ANOVA with Tukey’s multiple comparisons test ***P < 0.001; compared to control group.
Extended Data Fig. 2 Supporting data that TBK1 inhibition enhances sensitivity to PD-1 blockade using PDOTS.
a, Tumour type, tissue source (location), clinical response data, PDOTS response data, and associated tumour mutation profile for specimens used for PDOTS profiling (samples ordered by ex vivo PDOTS response to combined anti-PD-1+TBK1i). PDOTS response parameters defined as follows: responder (reduction >30% compared to control), partial responder (<30% reduction and <20% growth compared to control), and non-responder (>20% growth compared to control). Red border around grey rectangle indicates presence of alteration in indicated gene. b, effect of IgG4 control monoclonal Ab on viability of PDOTS from a patient with melanoma. Means (bars) and individual values (open circles) are shown (n = 3, biological replicates, 2-sided unpaired t-test).
Extended Data Fig. 3 Effect of TBK1 inhibition on the tumour immune microenvironment.
a–b, tSNE plot of 11 clusters of CD45+ cells (a) from patients with metastatic melanoma responsive (R) or non-responsive (NR) to immune checkpoint blockade (ref. Sade-Feldman et al. 2018), and t-SNE plots of RNA-sequenced single cells with colouring of CD3E (T cells), CD14 (myeloid cells), and CD19 (B cells) TBK1 and IKBKE expression (b). c–d, broad cluster proportions (c) and percent cells per cluster across indicated treatment groups (d). e–f, UMAP (c) and density (d) plots of reclustered lymphoid (T/NK) cells. g, cluster proportions of lymphoid (T/NK) cells. Means (bars) and individual values (circles) are shown +/− s.e.m (error bars). Multiple unpaired t-test, *P < 0.05; **P < 0.01; ***P < 0.001; **** P < 0.0001; ns, not significant. h, percentage of activated (CD69+CD25+) mouse CD8+ splenocytes pre-treated with TBK1i (1 μM) or DMSO (0.1%) with/without restimulation; n = 3 biologically independent samples, 2-way ANOVA, Sidak’s multiple comparisons test; *P < 0.05; ***P < 0.001. i–k, intracellular cytokine staining for TNF (i), IL-2 (j), and IFNγ (k) of mouse CD3+CD8+ splenocytes pre-treated with TBK1i (1 μM) or DMSO (0.1%) with/without restimulation with data shown as % CD69+CD25+ cells and MFI); n = 3 biologically independent samples, 2-way ANOVA, Sidak’s multiple comparisons test; **P < 0.01; **** P < 0.0001; ns, not significant.
Extended Data Fig. 4 Effect of Tbk1 deletion on the tumour immune microenvironment.
a, Flow cytometry of immune populations from control and Tbk1-null B16 tumours treated with anti-PD-1 (n = 4 per group). Means (bars) and individual values (open circles) are shown (n = 4 biologically independent samples, 2-sided unpaired t-test). b-c, UMAP (b) and density (c) plots of 31,810 RNA-sequenced single cells from control and Tbk1-null B16 tumours following anti-PD-1 treatment (DC, dendritic cells; Tregs, regulatory T cells; MDSC, myeloid-derived suppressor cell; NK, natural killer cells; M1, M1 macrophages; M2, M2 macrophages). d, percent of cells in each lineage-defined cluster. Means (bars) and individual values (open circles) are shown (n = 4 biologically independent samples, 2-way ANOVA, Sidak’s multiple comparisons test; P values shown for M1 macrophages and CD8 T cells that did not reach statistical significance). e, UMAP plot of RNA-sequenced single cells with colouring of Tbk1 and Ikbke expression with cell types referenced (b). f, bubble plot indicating Tbk1 and Ikbke expression across UMAP-defined cell clusters.
Extended Data Fig. 5 TNF and IFNγ expression in B16 melanoma tumours.
a, UMAP plot of RNA-sequenced single cells with colouring of Ifng and Tnf expression with cell types referenced (right). b, log-fold change of Ifng (light red) and Tnf (light blue) expression across lineage-defined cell clusters (Tbk1-null/control).
Extended Data Fig. 6 Supporting data that loss/inhibition of TBK1 sensitizes tumour cells to TNF/IFNγ.
a, volcano plot depicting relative sgRNAs gene depletion/enrichment. Top 5 depleted sgRNAs indicated. b, scatter plot of gene essentiality from in vitro CRISPR screen (control and Tbk1-null B16 cells). c, TBK1 expression and cell viability (control vs. TNF/IFNγ;) for single cell clones derived from polyclonal control and Tbk1-null B16 cells. Western blot is representative of three independent experiments. Means (bars) and individual values (open circles) are shown (n = 6 across two independent experiments, 2-way ANOVA, Sidak’s multiple comparisons test; **** P < 0.0001; ns, not significant). d, TBK1 indel spectrum from control sgRNA and Tbk1 sgRNA B16 single cell clones. e, Viability assessment (Cell Titer Glo) of B16-ova cells in standard 2D culture after 24 h treatment with TNF (160 ng ml−1) + IFNγ (40 ng ml−1) compared to unstimulated cells (n = 6, 2 independent experiments, 1-way ANOVA, Holm-Sidak’s multiple comparisons test). f, Viability assessment (Hoechst/propidium iodide) of B16 tumour spheroids (lacking immune cells) in 3D microfluidic culture after 96 h treatment with TNF (10 ng ml−1) + IFNγ (10 ng ml−1) compared to unstimulated cells (n = 6, 2 independent experiments, 1-way ANOVA, Holm-Sidak’s multiple comparisons test). g, Cell viability assessment of B16 cells after 24 h treatment with TNF (200 ng ml−1) + IFNγ (40 ng ml−1) compared to unstimulated cells treated with increasing concentrations of MRT67307 (n = 9, 3 independent experiments 2-way ANOVA, Sidak’s multiple comparisons test). h, Cell viability assessment of B16 cells in standard 2D culture after 24 h treatment with TNF (200 ng ml−1) + IFNγ (40 ng ml−1) compared to unstimulated cells treated with increasing concentrations of GSK8612 (n = 3, 1 independent experiment, 2-way ANOVA, Sidak’s multiple comparisons test). i, Cell viability assessment of B16 cells in standard 2D culture after 24 h treatment with TNF (200 ng ml−1) + IFNγ (40 ng ml−1) with increasing concentrations of TBK1 PROTAC 3i (n = 6, 2 independent experiments 2-way ANOVA, Sidak’s multiple comparisons test). **** P < 0.0001; ns, not significant.
Extended Data Fig. 7 Supporting data that TBK1 inhibition lowers the cytotoxicity threshold to TNF/IFNγ.
a, GR values for 9-point inhibitor titration of TBK1i in parental, control sgRNA (polyclonal and monoclonal), and Tbk1 sgRNA (polyclonal and monoclonal) B16 cells (2 independent experiments; representative data from single experiment with 6 technical replicates per condition). Means (solid circles) are shown +/− s.e.m (error bars). b–c, evaluation of TBK1i potency (b; half-maximal effect, GEC50) and overall efficacy (c; area over the GR curve, GRAOC) d–e, Heatmap of GR values for parental (d) and BRAF/MEK inhibitor resistant (e) A375 human melanoma cells treated with increasing concentrations of TNF and IFNγ for 24, 24, and 72 h with 0, 0.25, and 1.0 μM TBK1i (n = 3).
Extended Data Fig. 8 Supporting data that Tbk1-null cells undergo RIPK- and caspase-dependent cell death.
a–b, Cell viability assessment (Cell Titer Glo) in control and Tbk1-null B16 cells pre-treated with RIPK1 inhibitor (Nec-1s, 10 μM) and the pan-caspase inhibitor Q-VD-OPh (10 μM) +/− TNF/IFNγ (n=3, 1 independent experiment: 2-way ANOVA, Dunnett’s multiple comparisons test). b, cell viability assessment (Cell Titer Glo) in control and Tbk1-null B16 cells pre-treated with RIPK1 inhibitor (Nec-1s, 10 μM) and the pan-caspase inhibitor z-VAD-fmk (20 μM) +/− TNF/IFNγ (n = 3-6, 1-2 independent experiments: 2-way ANOVA, Dunnett’s multiple comparisons test). c, cell viability assessment in Tbk1-null B16 cells pre-treated with RIPK1 inhibitor (Nec-1s, 10 μM) and the caspase 8 inhibitor z-IETD-fmk (2.5 μM) +/− TNF/IFNγ (n = 6, 2 independent experiments; 2-way ANOVA, Dunnett’s multiple comparisons test). d, cell viability assessment in Tbk1-null B16 cells pre-treated with RIPK3 inhibitor (HS-1371, 2 μM) and the pan-caspase inhibitor Q-VD-OPh (20 μM) +/− TNF/IFNγ (n = 6, 2 independent experiments: 2-way ANOVA, Dunnett’s multiple comparisons test). e, cell viability assessment in Tbk1-null B16 cells pre-treated with MLKL inhibitor (GW806742X, 5 μM) and the pan-caspase inhibitor Q-VD-OPh (20 μM) +/− TNF/IFNγ (n = 6, 2 independent experiments: 2-way ANOVA, Dunnett’s multiple comparisons test). f-h, Clonogenic assay of B16 cells treated with TNF (10 ng ml−1), IFNγ (10 ng ml−1), or TNF + IFNγ with control (0.1% DMSO), Q-VD-OPh (20 μM) with/without the RIPK1 inhibitor Nec-1s (10 μM, f), RIPK3 inhibitor HS-1371 (2 μM, g), and MLKL inhibitor GW806742X (2 μM, h) (representative images shown; n = 3). i, normalized expression of selected genes in B16 cells treated with TNF (10 ng ml−1), IFNγ (100 ng ml−1), or both, compared to control cells (source data for bulk RNA-seq – Manguso et al. 2017). j, normalized expression of Mlkl and Ripk3 in control and Tbk1-null B16 cells with/without TNF/IFNγ treatment (18 h) determined by qRT-PCR (n = 3; 2-way ANOVA, Sidak’s multiple comparison test). *P < 0.05; **P < 0.01; ***P < 0.001; **** P < 0.0001; ns, not significant. k, Western blot of indicated proteins in Tbk1-null B16 cell lysates following 2-hour pre-treatment with vehicle control (0.1%DMSO), Q-VD-OPh (20 μM), Nec-1s (10 μM), or Q-VD-OPh plus Nec-1s, or Q-VD-OPh plus birinapant (1 μM) followed by 10 h treatment with TNF (160 ng ml−1) and IFNγ (40 ng ml−1) or unstimulated (PBS) control. Data are representative of three independent experiments.
Extended Data Fig. 9 Supporting data regarding TNF/IFNγ-induced cell death signalling in control and Tbk1-null cells.
a, heatmap of % cytochrome C (cyt C) release for in vitro BH3 profiling of unstimulated control (sg1 and sg2) and Tbk1-null (sg1 and sg2) B16 cells. Mean values shown; n=3 biologically independent samples; 2-way ANOVA, Dunnett’s multiple comparisons test. b, heatmap of % cytochrome C (cyt C) release for in vitro BH3 profiling of control sgRNA and Tbk1 sgRNA B16 cells. Mean values shown; n = 3 biologically independent samples; 2-way ANOVA, Tukey’s multiple comparisons test. No statistically significant differences observed between control sgRNA and Tbk1 sgRNA B16 cells at any time point. c, Viability assessment (Cell Titer Glo) of B16 cells in standard 2D culture after 24 h treatment with indicated concentrations of staurosporine (STS) in control and Tbk1-null B16 cells. Means (bars) and individual values (open circles) are shown (n = 6, 2 independent experiments, 2-way ANOVA, Sidak’s multiple comparisons test). d, Viability assessment (Hoechst/propidium iodide) of B16 tumour spheroids (lacking immune cells) in 3D microfluidic culture after 48 h treatment indicated concentrations of staurosporine (STS) compared to unstimulated cells Means (bars) and individual values (open circles) are shown (n = 6, 2 independent experiments, 1-way ANOVA, Holm-Sidak’s multiple comparisons test). e, Western blot for STING, IRF3, TBK1, and β-actin in B16 cells with single CRISPR cell lines with single-guide RNAs targeting Tmem173, Irf3, and Tbk1 compared to control sgRNA. Data are representative of three independent experiments. f, Western blot for STING, IRF3, TBK1, and β-actin in double CRISPR B16 cells with indicated sgRNA pairs. Data are representative of three independent experiments. g, Viability assessment (Cell Titer Glo) of indicated sgRNA B16 cells after 48 h treatment with TNF (160 ng ml−1) + IFNγ (40 ng ml−1) compared to unstimulated cells. Means (bars) and individual values (open circles) are shown (n = 4 biological replicates, 2-way ANOVA, Sidak’s multiple comparisons test, **P < 0.01; **** P < 0.0001; ns, not significant). h, PDOTS viability assessment from patients (n = 2) with cutaneous melanoma with indicated treatments. Means (bars) and individual values (open circles) are shown (n = 6 biological replicates, 2 independent specimens; one-way ANOVA with Dunn’s multiple comparisons test, **P < 0.01; **** P < 0.0001; ns, not significant). i, heatmap of secreted cytokine profiles (L2FC) of conditioned media from PDOTS in response to indicated treatments (n = 2). Mean values shown. **P < 0.01; **** P < 0.0001; ns, not significant.
Extended Data Fig. 10 Supporting data that IFNγ sensing is essential for effector cytokine-induced death in TBK1-null cells.
a, Frequency histograms of enrichment (z-score) for all sgRNAs per target in a Tbk1-null B16 cells +/− in vitro stimulation with TNF (10 ng ml−1) and IFNγ (10 ng ml−1). b, scatter plot depicting relative depletion of sgRNAs targeting 19,674 genes in a Cas9+ B16 control and Tbk1 sgRNA cell line +/− in vitro stimulation with TNF (10 ng ml−1) and IFNγ (10 ng ml−1). c, Western blot of control sgRNA and Tbk1-null B16 cells treated with TNF (160 ng ml−1) and IFNγ (40 ng ml−1) for the indicates times. Data are representative of three independent experiments. d, cell viability assessment in parental B16 cells pre-treated with TBK1i (1 μM) +/− JAK 1/2 inhibitor (ruxolitinib, 0.5 μM) +/− TNF/IFNγ for 48 h compared to unstimulated controls. Means (bars) and individual values (open circles) are shown (n=3, 1 independent experiment; 2-way ANOVA, Dunnett’s multiple comparisons test; *P < 0.05; ***P < 0.001; **** P < 0.0001; ns, not significant). e, Western blot of indicated proteins in Tbk1-null B16 cell lysates following 2-hour pre-treatment with vehicle control (0.1%DMSO), ruxolitinib (1 μM), Q-VD-OPh (20 μM), Nec-1s (10 μM), or Q-VD-OPh plus Nec-1s followed by 10-hour treatment with TNF (160 ng ml−1) and IFNγ (40 ng ml−1) or unstimulated (PBS) control. Data are representative of three independent experiments. f, GR values for 9-point inhibitor titration of ruxolitinib (JAK1/2i) in parental, control sgRNA (monoclonal), and Tbk1 sgRNA (monoclonal) B16 cells (2 independent experiments; representative data from single experiment with 6 technical replicates per condition). Means (solid circles) are shown +/− s.e.m (error bars).
Supplementary information
Supplementary Information
Supplementary Figs. 1–13. Gene expression matrices for scRNA-seq, gating strategy for flow cytometry and uncropped images for western blot analyses.
Supplementary Table 1
PDOTS clinicopathological data.
Supplementary Table 2
sgRNA depletion and enrichment data for in vitro CRISPR screens in B16 cells.
Supplementary Table 3
Supporting data for the main figures.
Supplementary Table 4
Supporting data for the extended data figures.
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Sun, Y., Revach, Oy., Anderson, S. et al. Targeting TBK1 to overcome resistance to cancer immunotherapy. Nature 615, 158–167 (2023). https://doi.org/10.1038/s41586-023-05704-6
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DOI: https://doi.org/10.1038/s41586-023-05704-6
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