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Autophagy promotes growth of tumors with high mutational burden by inhibiting a T-cell immune response

Nature Cancer volume 1, pages 923–934 (2020)Cite this article

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A Publisher Correction to this article was published on 16 August 2021

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Abstract

Macroautophagy (hereafter autophagy) degrades and recycles intracellular components to sustain metabolism and survival during starvation. Host autophagy promotes tumor growth by providing essential tumor nutrients. Autophagy also regulates immune cell homeostasis and function and suppresses inflammation. Although host autophagy does not promote a T-cell antitumor immune response in tumors with low tumor mutational burden (TMB), whether this was the case in tumors with high TMB was not known. Here we show that autophagy, especially in the liver, promotes tumor immune tolerance by enabling regulatory T-cell function and limiting stimulator of interferon genes, T-cell response and interferon-γ, which enables growth of high-TMB tumors. We have designated this as hepatic autophagy immune tolerance. Autophagy thereby promotes tumor growth through both metabolic and immune mechanisms depending on mutational load and autophagy inhibition is an effective means to promote an antitumor T-cell response in high-TMB tumors.

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Fig. 1: Loss of host autophagy increases the level of circulating pro-inflammatory cytokines and promotes T-cell infiltration in high-TMB tumors.
Fig. 2: Host autophagy promotes high-TMB tumor growth through a T-cell-dependent mechanism.
Fig. 3: Loss of autophagy upregulates an antitumor immune response in a T-cell-dependent manner and increases Treg cells.
Fig. 4: Host autophagy promotes high-TMB tumor growth through suppression of Sting.
Fig. 5: Loss of autophagy increases immune cell fraction and IFN-γ pathway gene expression.
Fig. 6: Loss of autophagy decreases tumor growth in an IFN-γ- and MHC-I-dependent manner.
Fig. 7: Liver autophagy is necessary to maintain tumor growth in an IFN-γ-dependent manner.
Fig. 8: Model depicting hepatic autophagic immune tolerance.

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Data availability

10X scRNA-seq data have been deposited in the Gene Expression Omnibus under accession ID GSE154654. Whole-exome sequencing data generated in this study can be found in the Gene Expression Omnibus under accession ID GSE155556. All other data supporting the findings of this study are available from the corresponding author upon reasonable request. Source data are provided with this paper.

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Acknowledgements

This work was supported by National Institutes of Health grants: R01CA193970 (to E.W.), R01CA163591 (to E.W. and J.D.R.), R01CA193970 (to J.M.M.), R01CA211066 (to J.L.G), R01CA243547 (to E.W., S.G. and E.C.L.) and P30CA072720 (Rutgers Cancer Institute of New Jersey) and by the Krauss Foundation (to E.W. and E.C.L.). C.S.C. is supported in part by Stand Up to Cancer and National Science Foundation grant no. 1546101. L.P.P. and S.V.L. received support from a postdoctoral fellowship from the New Jersey Commission for Cancer Research (DHFS16PPC034 and DCHS19PPC009, respectively). Services, results and/or products in support of the research project were generated by funding from the Rutgers Cancer Institute of New Jersey Comprehensive Genomics and Immune Monitoring Shared Resources supported, in part by NCI-CCSG P30CA072720-5920 and by the Lewis-Sigler Institute for Integrative Genomics (Genomics Core Facility).

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  1. Praveen K. Bommareddy

    Present address: Replimune Inc., Woburn, MA, USA

Authors and Affiliations

  1. Rutgers Cancer Institute of New Jersey, New Brunswick, NJ, USA

    Laura Poillet-Perez, Daniel W. Sharp, Yang Yang, Saurabh V. Laddha, Maria Ibrahim, Praveen K. Bommareddy, Zhixian Sherrie Hu, Joshua Vieth, Joshua D. Rabinowitz, Jian Cao, Shridar Ganesan, Chang S. Chan, Janice M. Mehnert, Edmund C. Lattime & Eileen White

  2. Department of Cancer Biology, University of Cincinnati College of Medicine, Cincinnati, OH, USA

    Michael Haas & Jun-Lin Guan

  3. Department of Pathology, Yale University School of Medicine, New Haven, CT, USA

    Marcus W. Bosenberg

  4. Department of Chemistry and Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA

    Joshua D. Rabinowitz

  5. Department of Medicine, Robert Wood Johnson Medical School, Rutgers University, New Brunswick, NJ, USA

    Jian Cao, Shridar Ganesan, Chang S. Chan & Janice M. Mehnert

  6. Department of Surgery, Robert Wood Johnson Medical School, Rutgers University, New Brunswick, NJ, USA

    Edmund C. Lattime

  7. Department of Molecular Biology and Biochemistry, Rutgers University, Piscataway, NJ, USA

    Eileen White

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Contributions

L.P.P. performed the majority of the experimental work and wrote the manuscript. D.W.S. performed/assisted with the MB49 allografts and CD4/CD8 or CD25 depletion and NanoString analysis. Y.Y. developed the methods and provided the mice required for generating Atg5∆/∆ hosts. S.V.L. and C.S.C. analyzed the whole-exome sequencing data and scRNA-seq data. M.I. assisted with the in vivo experiments. P.K.B. assisted with tumor processing and analyzed the data for the NanoString. Z.S.H. assisted with animal husbandry. J.V. performed the flow cytometry, analyzed T-cell exhaustion markers and performed cell isolation and library preparation for single-cell sequencing. M.W.B. provided the YUMM1.1 melanoma cells. J.D.R and S.G provided advice throughout the project and on the manuscript. J.C. provided expertise on CRISPR Cas9. M.H and J.L.G provided the Fip200flox/flox mice. J.M.M. provided expertise in melanoma. E.W. and E.C.L. are the leading principal investigators who conceived the project, supervised research and edited the paper.

Corresponding author

Correspondence to Eileen White.

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Competing interests

E.W. is co-founder of Vescor Therapeutics and is a consultant for Novartis. S.G. has consulted for Roche, Merck, Novartis, Foundation Medicine and Foghorn Therapeutics. The other authors declare no competing interests.

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Extended data

Extended Data Fig. 1 Loss of host autophagy does not decrease the growth of low TMB tumors in a T cell-dependent manner.

a, CD3+, CD4+, CD8+ T cells (percentage) in high TMB tumors (MB49) grown on female Atg7+/+ and Atg7Δ/Δ (n = 5 mice each) hosts following αCD4/8, analyzed by flow cytometry. b, Representative IHC images and quantification of CD3+, CD4+ and CD8+ T cells in YUMM1.3 tumors from male Atg7+/+ and Atg7Δ/Δ hosts (n = 5 mice each). c, d, e, f, Comparison of YUMM1.3 tumor growth on male (c, d) Atg7+/+, Atg7+/+ + αCD4/8, Atg7Δ/Δ and Atg7Δ/Δ + αCD4/8 (n = 10 tumors each) and female (e, f) Atg7+/+(n = 6 tumors), Atg7+/+ + αCD4/8 (n = 12 tumors), Atg7Δ/Δ (n = 12 tumors) and Atg7Δ/Δ + αCD4/8 (n = 12 tumors). Tumor pictures (c, e), and tumor weight and ratio (antibody treated/control) (d, f) from the experimental endpoint. g, h, Comparison of MB49 tumor growth on female Atg7+/+(n = 14 tumors), Atg7+/+ + αCD4 (n = 12 tumors), Atg7+/+ + αCD8 (n = 12 tumors), Atg7+/+ + αCD4/8 (n = 8 tumors), Atg7Δ/Δ (n = 12 tumors), Atg7Δ/Δ + αCD4 (n = 14 tumors), Atg7Δ/Δ + αCD8 (n = 14 tumors) and Atg7Δ/Δ + αCD4/8 (n = 12 tumors). Tumor pictures (g), and tumor weight and ratio (antibody treated/control) (h) from the experimental endpoint. All data are mean +/- s.e.m. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.001 using two-sided Student’s t-test. Source data available for a, b, d, f, h.

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Extended Data Fig. 2 Loss of host autophagy through Atg5 deletion decreases tumor growth through a T cell-dependent mechanism.

a, Experimental design to induce conditional whole-body Atg5 deletion (Atg5Δ/Δ), and wild-type (Atg5+/+) controls without and with T cell depletion. Ubc-CreERT2/+;Atg5+/+ and Ubc-CreERT2/+;Atg5flox/flox mice were injected with TAM to delete Atg5 and were then injected subcutaneously with tumor cells and intraperitoneally with αCD4/8. Tumor growth was monitored over three weeks. b, c, d, e, Comparison of MB49 tumor growth on male (b, c) Atg5+/+(n = 8 tumors), Atg5+/+ + αCD4/8 (n = 6 tumors), Atg5Δ/Δ (n = 8 tumors) and Atg5Δ/Δ + αCD4/8 (n = 8 tumors) and female (d, e) Atg5+/+(n = 12 tumors), Atg5+/+ + αCD4/8 (n = 10 tumors), Atg5Δ/Δ (n = 12 tumors) and Atg5Δ/Δ + αCD4/8 (n = 10 tumors). Tumor pictures (b, d), and tumor weight and ratio (antibody treated/control) (c, e) from the experimental endpoint. f, Representative IHC images and quantification of CD3+, CD4+ and CD8+ T cells in MB49 tumors from male Atg5+/+ and Atg5Δ/Δ hosts (n = 5 mice each). g, h, Comparison of UV YUMM1.1-9 tumor growth on male (g) Atg7+/+ (n = 10 tumors) and Atg7Δ/Δ (n = 8 tumors) and female (h) Atg7+/+ (n = 16 tumors) and Atg7Δ/Δ (n = 12 tumors) hosts. Tumor pictures and tumor weight from the experimental endpoint. All data are mean +/- s.e.m. *P < 0.05, ***P < 0.001, ****P < 0.0001 using two-sided Student’s t-test. Source data available for c, e, f, g, h.

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Extended Data Fig. 3 Loss of autophagy reduces Tregs and increases immune cell fraction.

a, Overall NanoString gene expression analysis (750 genes) from tumors on female Atg7+/+ and Atg7Δ/Δ hosts with or without αCD4/8 (n = 2 tumors each). Red: high, blue: low expression level. b, Representative IHC images and quantification of FOXP3+ cells in MB49 tumors from female Atg7+/+ and Atg7Δ/Δ hosts (n = 5 tumors each). c, FOXP3+ Treg cells, CD4+ and CD8+ T cells (percentage) in high TMB tumors (MB49) grown on female (n = 3 tumors) Atg7+/+ and Atg7Δ/Δ hosts following αCD25, analyzed by flow cytometry. d, Representative IHC images and quantification of FOXP3+ cells in MB49 tumors from female Atg7+/+ and Atg7Δ/Δ hosts following αCD25 (n = 3 tumors each). e, Survival analysis of Atg7+/+ (n = 19 mice), Atg7Δ/Δ (n = 19 mice), Stinggt/gt;Atg7+/+ (n = 15 mice) and Stinggt/gt;Atg7Δ/Δ (n = 13 mice) mice. f, scRNA-seq UMAP projection of cell cluster from tumors from female Atg7+/+ and Atg7Δ/Δ hosts (n = 3 tumors each). All data are mean +/- s.e.m. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001 using two-sided Student’s t-test. Source data available for b, c, d.

Source data

Extended Data Fig. 4 Loss of autophagy increases high TMB tumor growth in an IFNγ-dependent manner.

a, Survival analysis of Atg7+/+ (n = 16 mice), Atg7Δ/Δ (n = 14 mice), IFNγ-/-;Atg7+/+ (n = 6 mice) and IFNγ-/-;Atg7Δ/Δ (n = 5 mice) hosts. b, Representative H&E tissue staining from IFNγ-/-;Atg7+/+ and IFNγ-/-;Atg7Δ/Δ hosts. Images are representative of two independent experiments. c, d, e, f. Comparison of UV YUMM1.1-9 tumor growth on male (c, d) Atg7+/+ (n = 18 tumors), IFNγ-/-;Atg7+/+ (n = 18 tumors), Atg7Δ/Δ (n = 10 tumors), IFNγ-/-;Atg7Δ/Δ (n = 18 tumors) and female (e, f) Atg7+/+ (n = 16 tumors), IFNγ-/-;Atg7+/+ (n = 18 tumors), Atg7Δ/Δ (n = 16 tumors), IFNγ-/-;Atg7Δ/Δ (n = 18 tumors) hosts. Tumor pictures (c, e), and tumor weight and ratio (antibody treated/control) (d, f) from the experimental endpoint. g, Cropped Western blotting showing expression of B2m in MB49 shC and shB2m tumors from Atg7+/+ and Atg7Δ/Δ hosts (n = 3 tumors each) from one experiment. Actin was used a loading control. All data are mean +/- s.e.m. **P < 0.01, ***P < 0.001 using two-sided Student’s t-test. Source data available for d, f.

Source data

Extended Data Fig. 5 Loss of autophagy, not LC3-associated phagocytosis (LAP), decreases tumor growth through a T cell-dependent mechanism.

a, Serum and b, liver cytokine and chemokine profiling of female and male hosts bearing MB49 tumors with or without liver-specific deletion of Atg7 (n = 6 mice each), showing those with significant differences among 26. c, Experimental design to induce liver-specific Fip200 deletion (liver Fip200Δ/Δ) and wild-type controls (liver Fip200+/+). Fip200flox/flox or C57BL/6J mice were injected with AAV-TBG-iCre and MB49 cells were then injected subcutaneously and tumor growth was monitored over three weeks. d, Cropped Western blotting showing expression of Fip200 in livers, kidneys and brains (n = 3 each) from one experiment. e, Comparison of MB49 tumor growth on male liver Fip200+/+(n = 8 tumors) and liver Fip200Δ/Δ (n = 6 tumors) hosts. f, Experimental design to induce conditional Fip200 deletion (Fip200Δ/Δ) and wild-type (Fip200+/+) controls. C57BL/6J mice were injected with lentiCRISPR scramble or Fip200 to delete Fip200 and were then injected subcutaneously with tumor cells. Tumor growth was monitored over three weeks. g, Representative surveyor assay for Fip200 gRNA screening using liver gDNA from Fip200+/+ and Fip200Δ/Δ hosts (n = 10 mice each) from one experiment. h, Representative IHC images of FIP200+ and p62+ cells in liver from Fip200+/+ and Fip200Δ/Δ hosts (n = 10 mice each). i, j, Comparison of MB49 tumor growth on female Fip200+/+ and Fip200Δ/Δ hosts with or without CD4/8 depletion (n = 10 tumors each). Tumor pictures (i), and tumor weight and ratio (antibody treated/control) (j) from the experimental endpoint. Data are mean +/- s.e.m. *P < 0.05, **P < 0.01, ***P<0.001, ****P < 0.0001 using two-sided Student’s t-test. Source data available for a, b, e, j.

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Poillet-Perez, L., Sharp, D.W., Yang, Y. et al. Autophagy promotes growth of tumors with high mutational burden by inhibiting a T-cell immune response. Nat Cancer 1, 923–934 (2020). https://doi.org/10.1038/s43018-020-00110-7

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