Abstract

Autophagy captures intracellular components and delivers them to lysosomes, where they are degraded and recycled to sustain metabolism and to enable survival during starvation1,2,3,4,5. Acute, whole-body deletion of the essential autophagy gene Atg7 in adult mice causes a systemic metabolic defect that manifests as starvation intolerance and gradual loss of white adipose tissue, liver glycogen and muscle mass1. Cancer cells also benefit from autophagy. Deletion of essential autophagy genes impairs the metabolism, proliferation, survival and malignancy of spontaneous tumours in models of autochthonous cancer6,7. Acute, systemic deletion of Atg7 or acute, systemic expression of a dominant-negative ATG4b in mice induces greater regression of KRAS-driven cancers than does tumour-specific autophagy deletion, which suggests that host autophagy promotes tumour growth1,8. Here we show that host-specific deletion of Atg7 impairs the growth of multiple allografted tumours, although not all tumour lines were sensitive to host autophagy status. Loss of autophagy in the host was associated with a reduction in circulating arginine, and the sensitive tumour cell lines were arginine auxotrophs owing to the lack of expression of the enzyme argininosuccinate synthase 1. Serum proteomic analysis identified the arginine-degrading enzyme arginase I (ARG1) in the circulation of Atg7-deficient hosts, and in vivo arginine metabolic tracing demonstrated that serum arginine was degraded to ornithine. ARG1 is predominantly expressed in the liver and can be released from hepatocytes into the circulation. Liver-specific deletion of Atg7 produced circulating ARG1, and reduced both serum arginine and tumour growth. Deletion of Atg5 in the host similarly regulated circulating arginine and suppressed tumorigenesis, which demonstrates that this phenotype is specific to autophagy function rather than to deletion of Atg7. Dietary supplementation of Atg7-deficient hosts with arginine partially restored levels of circulating arginine and tumour growth. Thus, defective autophagy in the host leads to the release of ARG1 from the liver and the degradation of circulating arginine, which is essential for tumour growth; this identifies a metabolic vulnerability of cancer.

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Data availability

All data are available from the authors upon reasonable request. Source Data for Figs. 1d, 2b, 3d are provided with the paper. The raw mass spectrometry data have been deposited in the MassIVE repository, entry MSV000082879.

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Change history

  • 06 December 2018

    In this Letter, ‘released’ should have been ‘regulated’ in the sentence starting: ‘Deletion of Atg5 in the host similarly regulated circulating arginine and suppressed tumorigenesis...’ This has been corrected online.

References

  1. 1.

    Karsli-Uzunbas, G. et al. Autophagy is required for glucose homeostasis and lung tumor maintenance. Cancer Discov. 4, 914–927 (2014).

  2. 2.

    Komatsu, M. et al. Impairment of starvation-induced and constitutive autophagy in Atg7-deficient mice. J. Cell Biol. 169, 425–434 (2005).

  3. 3.

    Kuma, A. et al. The role of autophagy during the early neonatal starvation period. Nature 432, 1032–1036 (2004).

  4. 4.

    Guo, J. Y. et al. Autophagy provides metabolic substrates to maintain energy charge and nucleotide pools in Ras-driven lung cancer cells. Genes Dev. 30, 1704–1717 (2016).

  5. 5.

    Kamada, Y., Sekito, T. & Ohsumi, Y. Autophagy in yeast: a TOR-mediated response to nutrient starvation. Curr. Top. Microbiol. Immunol. 279, 73–84 (2004).

  6. 6.

    Kimmelman, A. C. & White, E. Autophagy and tumor metabolism. Cell Metab. 25, 1037–1043 (2017).

  7. 7.

    Amaravadi, R., Kimmelman, A. C. & White, E. Recent insights into the function of autophagy in cancer. Genes Dev. 30, 1913–1930 (2016).

  8. 8.

    Yang, A. et al. Autophagy sustains pancreatic cancer growth through both cell-autonomous and nonautonomous mechanisms. Cancer Discov. 8, 276–287 (2018).

  9. 9.

    Wang, J. et al. UV-induced somatic mutations elicit a functional T cell response in the YUMMER1.7 mouse melanoma model. Pigment Cell Melanoma Res. 30, 428–435 (2017).

  10. 10.

    Strohecker, A. M. et al. Autophagy sustains mitochondrial glutamine metabolism and growth of Braf V600E-driven lung tumors. Cancer Discov. 3, 1272–1285 (2013).

  11. 11.

    Guo, J. Y. et al. Autophagy suppresses progression of K-ras-induced lung tumors to oncocytomas and maintains lipid homeostasis. Genes Dev. 27, 1447–1461 (2013).

  12. 12.

    Chantranupong, L. et al. The CASTOR proteins are arginine sensors for the mTORC1 Pathway. Cell 165, 153–164 (2016).

  13. 13.

    Morris, S. M. Jr. Arginine metabolism: boundaries of our knowledge. J. Nutr. 137, 1602S–1609S (2007).

  14. 14.

    Delage, B. et al. Arginine deprivation and argininosuccinate synthetase expression in the treatment of cancer. Int. J. Cancer 126, 2762–2772 (2010).

  15. 15.

    Dillon, B. J. et al. Incidence and distribution of argininosuccinate synthetase deficiency in human cancers: a method for identifying cancers sensitive to arginine deprivation. Cancer 100, 826–833 (2004).

  16. 16.

    Patil, M. D., Bhaumik, J., Babykutty, S., Banerjee, U. C. & Fukumura, D. Arginine dependence of tumor cells: targeting a chink in cancer’s armor. Oncogene 35, 4957–4972 (2016).

  17. 17.

    Rabinovich, S. et al. Diversion of aspartate in ASS1-deficient tumours fosters de novo pyrimidine synthesis. Nature 527, 379–383 (2015).

  18. 18.

    Nagamani, S. C. & Erez, A. A metabolic link between the urea cycle and cancer cell proliferation. Mol. Cell. Oncol. 3, e1127314 (2016).

  19. 19.

    Feun, L. G. et al. Negative argininosuccinate synthetase expression in melanoma tumours may predict clinical benefit from arginine-depleting therapy with pegylated arginine deiminase. Br. J. Cancer 106, 1481–1485 (2012).

  20. 20.

    Lam, T. L. et al. Recombinant human arginase inhibits the in vitro and in vivo proliferation of human melanoma by inducing cell cycle arrest and apoptosis. Pigment Cell Melanoma Res. 24, 366–376 (2011).

  21. 21.

    Hui, S. et al. Glucose feeds the TCA cycle via circulating lactate. Nature 551, 115–118 (2017).

  22. 22.

    Morris, S. M. Jr. Arginases and arginine deficiency syndromes. Curr. Opin. Clin. Nutr. Metab. Care 15, 64–70 (2012).

  23. 23.

    Takamura, A. et al. Autophagy-deficient mice develop multiple liver tumors. Genes Dev. 25, 795–800 (2011).

  24. 24.

    Komatsu, M. et al. Homeostatic levels of p62 control cytoplasmic inclusion body formation in autophagy-deficient mice. Cell 131, 1149–1163 (2007).

  25. 25.

    Sousa, C. M. et al. Pancreatic stellate cells support tumour metabolism through autophagic alanine secretion. Nature 536, 479–483 (2016).

  26. 26.

    Katheder, N. S. et al. Microenvironmental autophagy promotes tumour growth. Nature 541, 417–420 (2017).

  27. 27.

    Kremer, J. C. et al. Arginine deprivation inhibits the Warburg effect and upregulates glutamine anaplerosis and serine biosynthesis in ASS1-deficient cancers. Cell Reports 18, 991–1004 (2017).

  28. 28.

    Yau, T. et al. A phase 1 dose-escalating study of pegylated recombinant human arginase 1 (Peg-rhArg1) in patients with advanced hepatocellular carcinoma. Invest. New Drugs 31, 99–107 (2013).

  29. 29.

    Shen, W. et al. A novel and promising therapeutic approach for NSCLC: recombinant human arginase alone or combined with autophagy inhibitor. Cell Death Dis. 8, e2720 (2017).

  30. 30.

    Koprivnikar, J., McCloskey, J. & Faderl, S. Safety, efficacy, and clinical utility of asparaginase in the treatment of adult patients with acute lymphoblastic leukemia. Onco Targets Ther. 10, 1413–1422 (2017).

  31. 31.

    Ruzankina, Y. et al. Deletion of the developmentally essential gene ATR in adult mice leads to age-related phenotypes and stem cell loss. Cell Stem Cell 1, 113–126 (2007).

  32. 32.

    Hara, T. et al. Suppression of basal autophagy in neural cells causes neurodegenerative disease in mice. Nature 441, 885–889 (2006).

  33. 33.

    Meeth, K., Wang, J. X., Micevic, G., Damsky, W. & Bosenberg, M. W. The YUMM lines: a series of congenic mouse melanoma cell lines with defined genetic alterations. Pigment Cell Melanoma Res. 29, 590–597 (2016).

  34. 34.

    Summerhayes, I. C. & Franks, L. M. Effects of donor age on neoplastic transformation of adult mouse bladder epithelium in vitro. J. Natl. Cancer Inst. 62, 1017–1023 (1979).

  35. 35.

    Lu, W. et al. Metabolomic analysis via reversed-phase ion-pairing liquid chromatography coupled to a stand alone orbitrap mass spectrometer. Anal. Chem. 82, 3212–3221 (2010).

  36. 36.

    Papazyan, R. et al. Physiological suppression of lipotoxic liver damage by complementary actions of HDAC3 and SCAP/SREBP. Cell Metab. 24, 863–874 (2016).

  37. 37.

    Melamud, E., Vastag, L. & Rabinowitz, J. D. Metabolomic analysis and visualization engine for LC–MS data. Anal. Chem. 82, 9818–9826 (2010).

  38. 38.

    Zhan, L. et al. Dysregulation of bile acid homeostasis in parenteral nutrition mouse model. Am. J. Physiol. Gastrointest. Liver Physiol. 310, G93–G102 (2016).

  39. 39.

    Su, X., Lu, W. & Rabinowitz, J. D. Metabolite spectral accuracy on orbitraps. Anal. Chem. 89, 5940–5948 (2017).

  40. 40.

    Sailer, M. et al. Increased plasma citrulline in mice marks diet-induced obesity and may predict the development of the metabolic syndrome. PLoS ONE 8, e63950 (2013).

  41. 41.

    Sleat, D. E. et al. Mass spectrometry-based protein profiling to determine the cause of lysosomal storage diseases of unknown etiology. Mol. Cell. Proteomics 8, 1708–1718 (2009).

  42. 42.

    Beavis, R. C. Using the global proteome machine for protein identification. Methods Mol. Biol. 328, 217–228 (2006).

  43. 43.

    Lund, S. P., Nettleton, D., McCarthy, D. J. & Smyth, G. K. Detecting differential expression in RNA-sequence data using quasi-likelihood with shrunken dispersion estimates. Stat. Appl. Genet. Mol. Biol. 11, 1544-6115 (2012).

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Acknowledgements

This work was supported by National Institutes of Health grants: R01CA130893, R01CA188096 (to E.W.), R01CA163591 (to E.W. and J.D.R.), K22CA190521 (to J.Y.G.), R50CA211437 (to W.L.), R01CA193970 and the V Foundation for Cancer Research (to J.M.M.). L.P.-P. received support from a postdoctoral fellowship from the New Jersey Commission for Cancer Research (DHFS16PPC034). We thank the Rutgers-New Brunswick/Robert Wood Johnson Medical School Biological Mass Spectrometry Facility (S10OD016400) for mass spectrometry analysis, and the Biospecimen Repository and Histopathology Service, Metabolomics Service, Flow Cytometry and Biometrics Shared Resources (D. Moore performed the statistical analysis of the proteomics data) of Rutgers Cancer Institute of New Jersey (P30CA072720).

Reviewer information

Nature thanks R. DeBerardinis and the other anonymous reviewer(s) for their contribution to the peer review of this work.

Author information

Affiliations

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

    • Laura Poillet-Perez
    • , Xiaoqi Xie
    • , Le Zhan
    • , Yang Yang
    • , Daniel W. Sharp
    • , Zhixian Sherrie Hu
    • , Xiaoyang Su
    • , Anurag Maganti
    • , Cherry Jiang
    • , Janice M. Mehnert
    • , Jessie Yanxiang Guo
    • , Edmund Lattime
    • , Joshua D. Rabinowitz
    •  & Eileen White
  2. Department of Medicine, Robert Wood Johnson Medical School, Rutgers University, New Brunswick, NJ, USA

    • Xiaoyang Su
    •  & Jessie Yanxiang Guo
  3. Department of Chemistry and Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA

    • Wenyun Lu
    •  & Joshua D. Rabinowitz
  4. Biological Mass Spectrometry Facility, Rutgers University, Robert Wood Johnson Medical School, Rutgers University, Piscataway, NJ, USA

    • Haiyan Zheng
  5. Department of Pathology, Yale University School of Medicine, New Haven, CT, USA

    • Marcus W. Bosenberg
  6. Department of Medicine, Division of Medical Oncology, Developmental Therapeutics Unit, Robert Wood Johnson Medical School, Rutgers University, New Brunswick, NJ, USA

    • Janice M. Mehnert
  7. Department of Chemical Biology, Rutgers Ernest Mario School of Pharmacy, Piscataway, NJ, USA

    • Jessie Yanxiang Guo
  8. Department of Surgery, Robert Wood Johnson Medical School, Rutgers University, New Brunswick, NJ, USA

    • Edmund Lattime
  9. 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. L.Z. performed surgery and infusion with labelled arginine. Y.Y. developed the methods and provided the mice required for generating Atg5Δ/Δ and hosts with liver-specific deletion of Atg5. A.M. and C.J. assisted with in vitro experiments. X.X. and J.Y.G. performed some of the tumour growth experiments. J.M.M. provided melanoma expertise. D.W.S. and E.L. assisted with CD4 and CD8 depletion. Z.S.H. assisted with mouse husbandry. H.Z. performed proteomics processing and analysis. X.S., W.L. and J.D.R. performed metabolomics processing and analysis. M.W.B. provided YUMM 1.1, 1.3, 1.7 and 1.9 melanoma cells. E.W. is the leading principal investigator who conceived the project, supervised research and edited the paper.

Competing interests

E.W. is co-founder of Vescor Therapeutics. The other authors declare no competing interests.

Corresponding author

Correspondence to Eileen White.

Extended data figures and tables

  1. Extended Data Fig. 1 Host autophagy promotes growth of different tumour cell types.

    a, c, e, Comparison of tumour weight between Atg7+/+ (n = 5) and Atg7Δ/Δ (a, n = 4; c, n = 5; e, n = 4) hosts after injection of 1.3 (a), MB49 (c) or 71.8 (e) cells. Data are mean ± s.e.m. *P < 0.05, **P < 0.01. b, d, f, Immunohistochemistry quantification of Ki-67+ and active caspase-3+ cells in tumours from Atg7+/+ and Atg7Δ/Δ hosts. Data are mean ± s.e.m. *P < 0.05, ***P < 0.001, ****P < 0.0001. Source data

  2. Extended Data Fig. 2 Immune response is not involved in decreased tumour growth observed in Atg7Δ/Δ hosts.

    ac, Comparison of tumour weight between Atg7+/+ (n = 5) and Atg7Δ/Δ (a, n = 5; c, n = 6) hosts after injection of 1.7 (a) or 1.9 (c) cells. Data are mean ± s.e.m. b, d, Immunohistochemistry quantification of Ki-67+ and active caspase-3+ in 1.7 (b) and 1.9 (d) tumours from Atg7+/+ and Atg7Δ/Δ hosts. Data are mean ± s.e.m. e, Representative immunohistochemistry images and quantification of CD3+, CD4+ and CD8+ cells in tumours from Atg7+/+ and Atg7Δ/Δ hosts. Data are mean ± s.e.m. f, Comparison of tumour volume and weight between Atg7+/+ (n = 10), Atg7+/+ + CD4 and CD8 antibody depletion (n = 15), Atg7Δ/Δ (n = 7) and Atg7Δ/Δ + CD4 and CD8 antibody depletion (n = 8) hosts. Data are mean ± s.e.m. *P < 0.05, ****P < 0.0001. g, Fold change in immune components between Atg7+/+ and Atg7Δ/Δ, with or without antibody depletion (n = 5 each). Treg, T regulatory cells; DC, dendritic cells; MDSC, myeloid-derived suppressor cells. Data are mean ± s.e.m. ***P < 0.001, ****P < 0.0001, by two-way ANOVA test. Source data

  3. Extended Data Fig. 3 Tumour cells are arginine auxotrophs.

    a, YUMM 1.3, 71.8, MB49 and YUMM 1.7, 1.9 proliferation in vitro, in medium containing different percentages of arginine. Cell density was measured every 2 h using the IncuCyte. Data are representative of three independent experiments performed in duplicate. b, Western blotting showing expression of ASS1, ASL and OTC in kidneys and livers from Atg7+/+ and Atg7Δ/Δ hosts. *P < 0.05 compared to Atg7+/+ hosts. Data are representative of three independent experiments. Actin was used as a loading (kidney ASL and liver OTC) and processing (kidney ASS1, liver ASS1 and ASL) control. c, Western blotting showing expression of ASS1, ASL and OTC in YUMM 1.7 tumours from Atg7+/+ and Atg7Δ/Δ hosts. Data are representative of two independent experiments. Actin was used as a loading (OTC) and processing (ASS1 and ASL) control. d, Analysis of levels of nitric oxide in serum in Atg7+/+ (n = 11) and Atg7Δ/Δ (n = 9) hosts. Data are mean ± s.e.m. Source data

  4. Extended Data Fig. 4 Atg7 deletion increases serum arginine degradation but does not modify arginine metabolism in kidney and liver.

    a, Serum 13C6-arginine and 13C5-ornithine in Atg7+/+ and Atg7Δ/Δ hosts (n = 3 each) over time. Data are mean ± s.e.m. b, Concentration (in μΜ) of arginine, citrulline and ornithine in serum from Atg7+/+ (n = 3) and Atg7Δ/Δ hosts (n = 4), after infusion with 13C615N4-arginine. c, d, Concentration (in nmol g−1) of arginine, citrulline and ornithine in kidneys (c) and livers (d) from Atg7+/+ and Atg7Δ/Δ hosts (n = 2 each) after infusion with 13C615N4-arginine. Data are mean. **P < 0.01 by two-way ANOVA test. Source data

  5. Extended Data Fig. 5 Liver-specific deletion of Atg7 leads to liver-cell enlargement without affecting other tissues.

    ac, Western blotting showing expression of Atg7 in livers (n = 11 each) (a), brains (n = 9 and 11, respectively) (b) and kidneys (n = 10 each) (c) from Atg7+/+ hosts and hosts with liver-specific deletion of Atg7. *P < 0.05 compared to Atg7+/+ hosts. Data are representative of two independent experiments. Actin was used as a loading control. d, Representative haematoxylin and eosin tissue staining from Atg7+/+ hosts and hosts with liver-specific deletion of Atg7. Images are representative of two independent experiments. e, Analysis of levels of nitric oxide in serum, in Atg7+/+ hosts (n = 13) and hosts with liver-specific deletion of Atg7 (n = 15). Data are mean ± s.e.m. f, Comparison of serum metabolites that are significantly regulated in Atg7Δ/Δ hosts and hosts with liver-specific deletion of Atg7 (n = 17 each, P < 0.05). Source data

  6. Extended Data Fig. 6 Atg5 deletion increased serum ARG1, decreased serum arginine and tumour growth.

    a, Experimental design to induce host mice with conditional whole-body deletion of Atg5 (Atg5Δ/Δ) and wild-type controls (Atg5+/+) with which to assess tumour growth. Ubc-creERT2/+;Atg5+/+ and Ubc-creERT2/+;Atg5flox/flox mice were injected with TAM at 8 to 10 weeks of age to delete Atg5 and create Atg5+/+ and Atg5Δ/Δ hosts. Mice were then injected subcutaneously with tumour cells and tumour growth was monitored over three weeks. b, Comparison of tumour weight between Atg5+/+ (n = 4) and Atg5Δ/Δ (n = 3) hosts. Data are mean ± s.e.m. **P < 0.01. c, Immunohistochemistry quantification of Ki-67+ and active caspase-3+ cells in tumours from Atg5+/+ and Atg5Δ/Δ hosts. Data are mean ± s.e.m. ****P < 0.0001. d, Western blotting showing expression of ARG1 in serum from Atg5+/+ (n = 3), Atg5Δ/Δ (n = 4) and Atg7Δ/Δ (n = 3) hosts. *P < 0.05 compared to Atg5+/+ hosts. Transferrin was used as a loading control. e, Levels of arginine, ornithine and citrulline in serum in Atg5+/+ (n = 4) and Atg5Δ/Δ (n = 3) hosts, obtained by LC–MS. Data are mean ± s.e.m. *P < 0.05, **P < 0.01. Source data

  7. Extended Data Fig. 7 Liver-specific Atg5-deleted hosts present liver-cell enlargement, increased serum ARG1 and decreased serum arginine.

    a, Experimental design to induce liver-specific deletion of Atg5. Atg5flox/flox mice were injected in the tail vein with AAV–TBG–GFP or AAV–TBG–iCre at 8 to 10 weeks of age to delete Atg5 in the liver and create Atg5+/+ hosts and hosts with liver-specific deletion of Atg5, respectively. b, Western blotting showing expression of Atg5 in the livers, brains and kidneys of Atg5+/+ hosts and hosts with liver-specific deletion of Atg5 (n = 6 each). *P < 0.05 compared to Atg5+/+ hosts. Actin was used as a loading control c, Haematoxylin and eosin tissue staining from Atg5+/+ hosts and hosts with liver-specific deletion of Atg5 (n = 6 each). d, Western blotting showing expression of ARG1 in serum from Atg5+/+ hosts and hosts with liver-specific deletion of Atg5 (n = 6 each). *P < 0.05 compared to Atg5+/+ hosts. Transferrin was used as a loading control. e, Levels of arginine, ornithine and citrulline in serum in Atg5+/+ hosts and hosts with liver-specific deletion of Atg5 (n = 6 each), obtained by LC–MS. Data are mean ± s.e.m. ***P < 0.001, ****P < 0.0001. Source data

  8. Extended Data Fig. 8 Dietary arginine supplementation rescues YUMM 1.3 tumour growth in Atg7Δ/Δ hosts.

    a, Serum arginine, ornithine and citrulline in Atg7+/+ (n = 5), Atg7+/+ + 1% arginine (n = 5), Atg7Δ/Δ (n = 6) and Atg7Δ/Δ + 1% arginine (n = 6) hosts, obtained by LC–MS. Data are mean ± s.e.m. *P < 0.05, **P < 0.01. b, Comparison of YUMM 1.3 tumour weight between Atg7+/+ and Atg7Δ/Δ (n = 5 each) hosts, with or without arginine supplementation. Data are mean ± s.e.m. **P < 0.01, ****P < 0.0001. c, Immunohistochemistry quantification of Ki-67+ and active caspase-3+ cells in tumours from Atg7+/+ and Atg7Δ/Δ hosts, with or without arginine supplementation. Data are mean ± s.e.m. **P < 0.01, ****P < 0.0001. Source data

Supplementary information

  1. Supplementary Figures

    This file contains Supplementary Figure 1: Source data gels western blotting

  2. Reporting Summary

  3. Supplementary Table

    This file contains Supplementary Tables 1-5. Supplementary table 1: Metabolites with significant changes in Atg7/ vs Atg7+/+ hosts. Supplementary table 2: Unchanged metabolites in Atg7/ vs Atg7+/+ hosts. Supplementary table 3: Proteins with significant changes in Atg7/ vs Atg7+/+ host. Supplementary table 4: Metabolites with significant changes in liver specific Atg7 deleted host vs Atg7 WT host. Supplementary table 5: Unchanged metabolites in liver specific Atg7 deleted host vs Atg7 WT host

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https://doi.org/10.1038/s41586-018-0697-7

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