Abstract

The extracellular matrix is a major component of the local environment—that is, the niche—that determines cell behaviour1. During metastatic growth, cancer cells shape the extracellular matrix of the metastatic niche by hydroxylating collagen to promote their own metastatic growth2,3. However, only particular nutrients might support the ability of cancer cells to hydroxylate collagen, because nutrients dictate which enzymatic reactions are active in cancer cells4,5. Here we show that breast cancer cells rely on the nutrient pyruvate to drive collagen-based remodelling of the extracellular matrix in the lung metastatic niche. Specifically, we discovered that pyruvate uptake induces the production of α-ketoglutarate. This metabolite in turn activates collagen hydroxylation by increasing the activity of the enzyme collagen prolyl-4-hydroxylase (P4HA). Inhibition of pyruvate metabolism was sufficient to impair collagen hydroxylation and consequently the growth of breast-cancer-derived lung metastases in different mouse models. In summary, we provide a mechanistic understanding of the link between collagen remodelling and the nutrient environment in the metastatic niche.

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Data availability

The authors declare that all data supporting the findings of this study are available within the paper, Extended Data Figs. 110, the Source Data (of Figs. 14 and Extended Data Figs. 17, 9, 10) or from the corresponding author upon reasonable request.

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Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

References

  1. 1.

    Bonnans, C., Chou, J. & Werb, Z. Remodelling the extracellular matrix in development and disease. Nat. Rev. Mol. Cell Biol. 15, 786–801 (2014).

  2. 2.

    Gilkes, D. M. et al. Collagen prolyl hydroxylases are essential for breast cancer metastasis. Cancer Res. 73, 3285–3296 (2013).

  3. 3.

    Xiong, G., Deng, L., Zhu, J., Rychahou, P. G. & Xu, R. Prolyl-4-hydroxylase α subunit 2 promotes breast cancer progression and metastasis by regulating collagen deposition. BMC Cancer 14, 1 (2014).

  4. 4.

    Elia, I. & Fendt, S.-M. In vivo cancer metabolism is defined by the nutrient microenvironment. Transl. Cancer Res. 5, S1284–S1287 (2016).

  5. 5.

    Elia, I., Doglioni, G. & Fendt, S.-M. Metabolic hallmarks of metastasis formation. Trends Cell Biol. 28, 673–684 (2018).

  6. 6.

    Christen, S. et al. Breast cancer-derived lung metastasis show increased pyruvate carboxylase-dependent anaplerosis. Cell Rep. 17, 837–848 (2016).

  7. 7.

    Shinde, A., Wilmanski, T., Chen, H., Teegarden, D. & Wendt, M. K. Pyruvate carboxylase supports the pulmonary tropism of metastatic breast cancer. Breast Cancer Res. 20, 76 (2018).

  8. 8.

    Faubert, B. et al. Lactate metabolism in human lung tumors. Cell 171, 358–371 (2017).

  9. 9.

    Buescher, J. M. et al. A roadmap for interpreting 13C metabolite labeling patterns from cells. Curr. Opin. Biotechnol. 34, 189–201 (2015).

  10. 10.

    Lorendeau, D., Christen, S., Rinaldi, G. & Fendt, S.-M. Metabolic control of signalling pathways and metabolic auto-regulation. Biol. Cell 107, 251–272 (2015).

  11. 11.

    Stegen, S. HIF-1α metabolically controls collagen synthesis and modification in chondrocytes. Nature 565, 511–515 (2019).

  12. 12.

    Gilkes, D. M., Semenza, G. L. & Wirtz, D. Hypoxia and the extracellular matrix: drivers of tumour metastasis. Nat. Rev. Cancer 14, 430–439 (2014).

  13. 13.

    Elia, I. et al. Proline metabolism supports metastasis formation and could be inhibited to selectively target metastasizing cancer cells. Nat. Commun. 8, 15267 (2017).

  14. 14.

    Kojima, Y. et al. Autocrine TGF-β and stromal cell-derived factor-1 (SDF-1) signaling drives the evolution of tumor-promoting mammary stromal myofibroblasts. Proc. Natl Acad. Sci. USA 107, 20009–20014 (2010).

  15. 15.

    van Gorsel, M., Elia, I. & Fendt, S.-M. 13C tracer analysis and metabolomics in 3D cultured cancer cells. Methods Mol. Biol. 1862, 53–66 (2019).

  16. 16.

    Mandegar, M. A. et al. CRISPR interference efficiently induces specific and reversible gene silencing in human iPSCs. Cell Stem Cell 18, 541–553 (2016).

  17. 17.

    Gilbert, L. A. et al. Genome-scale CRISPR-mediated control of gene repression and activation. Cell 159, 647–661 (2014).

  18. 18.

    Lorendeau, D. et al. Dual loss of succinate dehydrogenase (SDH) and complex I activity is necessary to recapitulate the metabolic phenotype of SDH mutant tumors. Metab. Eng. 43, 187–197 (2017).

  19. 19.

    Creemers, L. B., Jansen, D. C., van Veen-Reurings, A., van den Bos, T. & Everts, V. Microassay for the assessment of low levels of hydroxyproline. Biotechniques 22, 656–658 (1997).

  20. 20.

    Sunic, D., Belford, D. A., McNeil, J. D. & Wiebkin, O. W. Insulin-like growth factor binding proteins (IGF-BPs) in bovine articular and ovine growth-plate chondrocyte cultures: their regulation by IGFs and modulation of proteoglycan synthesis. Biochim. Biophys. Acta 1245, 43–48 (1995).

  21. 21.

    Broekaert, D. & Fendt, S.-M. Measuring in vivo tissue metabolism using 13C glucose infusions in mice. Methods Mol. Biol. 1862, 67–82 (2019).

  22. 22.

    Oskarsson, T. Extracellular matrix components in breast cancer progression and metastasis. Breast 22 (Suppl. 2), S66–S72 (2013).

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Acknowledgements

We thank P. Carmeliet for providing P5CS shRNA constructs, L. Van Den Bosch and A. Orimo for providing (myo)fibroblasts, J. Norman, B. Hemmeryckx, F. Stanchi, L. Allen and G. Bergers for their advice, D. Anastasiou for providing reagents, D. Nittner (VIB histology core) for performing immunohistochemistry staining, R. Anderson for providing EMT6.5 cells. S.S. and M.R. are supported by FWO postdoctoral fellowships. M.v.G. and G.D. are supported by Kom op tegen Kanker fellowships. S.-M.F. acknowledges funding from the European Research Council under ERC Consolidator Grant Agreement number 771486 MetaRegulation, FWO Odysseus II, FWO Research Grants and Projects, and KU Leuven Methusalem Co-Funding.

Reviewer information

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

Author information

Author notes

  1. These authors contributed equally: Matteo Rossi, Steve Stegen, Dorien Broekaert, Ginevra Doglioni, Marit van Gorsel

Affiliations

  1. Laboratory of Cellular Metabolism and Metabolic Regulation, VIB-KU Leuven Center for Cancer Biology, VIB, Leuven, Belgium

    • Ilaria Elia
    • , Matteo Rossi
    • , Dorien Broekaert
    • , Ginevra Doglioni
    • , Marit van Gorsel
    • , Carmen Escalona-Noguero
    •  & Sarah-Maria Fendt
  2. Laboratory of Cellular Metabolism and Metabolic Regulation, Department of Oncology, KU Leuven and Leuven Cancer Institute (LKI), Leuven, Belgium

    • Ilaria Elia
    • , Matteo Rossi
    • , Dorien Broekaert
    • , Ginevra Doglioni
    • , Marit van Gorsel
    • , Carmen Escalona-Noguero
    •  & Sarah-Maria Fendt
  3. Laboratory of Clinical and Experimental Endocrinology, Department of Chronic Diseases, Metabolism and Ageing, KU Leuven, Leuven, Belgium

    • Steve Stegen
    • , Sophie Torrekens
    •  & Geert Carmeliet
  4. Stem Cell Institute, KU Leuven, Leuven, Belgium

    • Ruben Boon
    •  & Catherine Verfaillie
  5. Translational Cell and Tissue Research, KU Leuven, Leuven, Belgium

    • Erik Verbeken

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Contributions

I.E. performed most experiments and analysed all data. Key in vitro experiments were reproduced by M.v.G., M.R. and C.E.-N. M.R. helped with microscopy analysis, fibroblast and western blot analysis. D.B. and G.D. helped with western blot analysis and/or in vivo experiments. M.v.G. performed the imaging of the tissue sections and helped with in vitro sample collection. S.S. and S.T. performed hydroxyproline measurements and collagen synthesis measurements. R.B. and C.V. helped with CRISPR and overexpression construct designs. C.E.-N. performed the experiment with the HCC70 cell line. E.V. helped with the interpretation of in vivo ECM remodelling data. G.C. provided advice on ECM remodelling. I.E. and S.-M.F. designed the study and wrote the manuscript. S.-M.F. conceived and supervised the study and obtained funding.

Competing interests

S.-M.F. has received research funding from Bayer AG and Merck. The other authors declare no competing interests.

Corresponding author

Correspondence to Sarah-Maria Fendt.

Extended data figures and tables

  1. Extended Data Fig. 1 Pyruvate is required for three-dimensional but not two-dimensional growth of breast cancer cells.

    a, b, Growth curves (two-dimensional, left) and representative pictures (three-dimensional, right) of human MCF10A H-RASV12 and mouse 4T1 cells cultured in medium with or without pyruvate, glucose or glutamine. c, Representative pictures of MCF10A H-RASV12 and MCF10A spheroids in the presence or absence of pyruvate or 0.5% supplemented ECM (Matrigel). Analysis was performed at day 5. The number of biological replicates for each experiment was n = 3. Data are mean ± s.d. of biological independent samples. Scale bars, 150 μm. d, Cellular pyruvate, α-ketoglutarate and hydroxyproline metabolism. Enzymes are depicted in bold and italics. ALT2, mitochondrial alanine aminotransferase; GDH, glutamate dehydrogenase; MCT2, monocarboxylate transporter 2; MPC, mitochondrial pyruvate carrier; P4HA, collagen prolyl-4-hydroxylase; OH-proline, hydroxyproline. Only selected reactions are depicted. Source data

  2. Extended Data Fig. 2 Pyruvate depletion does not affect collagen synthesis.

    a, Total collagen and protein synthesis (left) as well as protein synthesis (right) in human and mouse breast cancer spheroids with and without pyruvate. CPM, counts per min. Total collagen and protein synthesis was assessed by incorporation of radioactive proline into collagen and protein, whereas protein synthesis was assessed by fluorescently labelled methionine incorporation into protein. The latter is more specific for protein synthesis since methionine is only to a minor extent incorporated into collagen. Changes that occur in both parameters indicate alterations in protein synthesis, whereas changes that occur only in total collagen and protein synthesis indicate alterations in collagen synthesis. Our data indicate that collagen synthesis was not altered by pyruvate depletion, because either total collagen and protein synthesis were not altered or both parameters were altered to a similar extent in the tested cell lines. n = 3. b, Relative abundance of collagen I and III and representative three-dimensional reconstruction in human MCF10A H-RASV12 and mouse 4T1 breast cancer spheroids with and without pyruvate measured by immunofluorescence. n = 5. Collagen I and III are major collagen species in breast cancer22. Blue, DAPI-stained nuclei; red, collagen I; green, collagen III. The total fluorescence intensity was measured in each microscopy field and normalized over the cell number, scored as the number of DAPI-stained nuclei. Five microscopy fields were averaged for each sample. Relative fluorescence intensities per cell are depicted, normalized to the control condition. The solid line indicates the median, the box extends to the 25th and 75th percentiles, the whiskers span the smallest and the largest values. Data are mean ± s.d. of biological independent samples unless otherwise noted. Two-tailed unpaired Student’s t-test. Source data

  3. Extended Data Fig. 3 Pyruvate drives collagen hydroxylation.

    a, Pyruvate, lactate and glucose uptake/secretion in human MCF10A H-RASV12 breast cancer spheroids treated with MCT2 inhibitor (α-cyano-hydroxycinnamic acid; 1.5 mM). These data show that the used inhibitor impairs pyruvate uptake, but not lactate secretion or glucose uptake. b, c, Hydroxylated collagen was assessed by measuring hydroxyproline in human (MCF10A H-RASV12, MCF7 and HCC70) and mouse (4T1) breast cancer spheroids treated with a MCT2 inhibitor (α-cyano-hydroxycinnamic acid; 1.5 mM), or treated with the MPC inhibitor UK5099 (50 μM) in the presence of pyruvate. The number of biological replicates for each experiment was n = 3. Data are mean ± s.d. of biological independent samples. Two-tailed unpaired Student’s t-test. Source data

  4. Extended Data Fig. 4 Pyruvate drives collagen hydroxylation via α-ketoglutarate.

    a, Heat map representing metabolite changes in MCF10A H-RASV12 spheroids in the presence or absence of pyruvate measured by mass spectrometry. Blue, significantly reduced metabolites upon pyruvate depletion. n = 3. b, Intracellular abundance of pyruvate, α-ketoglutarate (α-KG), citrate and malate in human MCF10A H-RASV12 breast cancer spheroids with and without pyruvate. n = 3. c, Hydroxylated collagen was assessed by measuring hydroxyproline in MCF10A H-RASV12 spheroids in the presence or absence of pyruvate upon addition of lactate (2 mM), alanine (2 mM), glutamate (2 mM) or cell-permeable α-ketoglutarate (1.5 mM). n = 3. d, Intracellular abundance of α-ketoglutarate, citrate and malate in human MCF10A H-RASV12 breast cancer spheroids upon supplementation of cell-permeable α-ketoglutarate (1.5 mM), citrate (5 mM) or malate (5 mM). n = 3. e, Relative change in hydroxylated collagen was assessed by measuring hydroxyproline in human (MCF10A, MCF7 and HCC70) and mouse (4T1 and EMT6.5) breast cancer spheroids in the absence of pyruvate with or without cell-permeable α-ketoglutarate (1.5 mM). Data are normalized to controls. Dashed line indicates the level of hydroxylated collagen in control conditions with pyruvate. n = 3 for MCF10A and EMT6.5; n = 6 for MCF7 and HCC70; n = 9 for MCF10A H-RASV12 and 4T1. f, Relative change in hydroxylated collagen was assessed by measuring hydroxyproline in MCF10A H-RASV12 spheroids treated with the MCT2 inhibitor α-cyano-4-hydroxycinnamic acid (1.5 mM) upon addition of cell-permeable α-ketoglutarate (1.5 mM) in the presence of pyruvate. Data are normalized to control. Dashed line indicates the level of hydroxylated collagen in the control condition. n = 3. Data are mean ± s.d. of biological independent samples. Two-tailed unpaired Student’s t-test. Source data

  5. Extended Data Fig. 5 Pyruvate to alanine conversion drives α-ketoglutarate production.

    a, Carbon contribution of 13C5-glutamine, 13C6-glucose and 13C3-pyruvate to alanine and α-ketoglutarate assessed by 13C tracer analysis. n = 3. b, Alanine uptake/secretion in MCF10A H-RASV12 spheroids with and without pyruvate was measured by mass spectrometry analysis of the medium. n = 3. cf, Intracellular abundance of α-ketoglutarate and hydroxylated collagen in human and mouse breast cancer spheroids upon treatment with the transaminase inhibitor aminooxyacetate (AOA) (0.8 mM), the glutamate dehydrogenase (GDH) inhibitor epigallocatechin gallate (EGCG) (50 μM), transduced with a lentiviral vector with shRNA against either mitochondrial ALT2 or Alt2 (KD), GDH (KD) or scrambled control sequence in the presence of pyruvate. n = 3 for EGCG and AOA treatment (c, d); n = 9 for control shRNA, n = 6 for GDH shRNA 1 and 2 and n = 3 for ALT2 shRNA1 and 2 (MCF10A H-RASV12; e, f); n = 3 for control shRNA and Alt2 shRNA 1 and 2 (4T1; e, f). If ALT activity majorly contributs to α-ketoglutarate generation, EGCG (which inhibits the pyruvate-independent conversion of glutamate to α-ketoglutarate via GDH), should have a minor effect on α-ketoglutarate abundance and hydroxylated collagen. Indeed, we found that this was the case. Data are mean ± s.d. of biological independent samples. Two-tailed unpaired Student’s t-test. Source data

  6. Extended Data Fig. 6 α-Ketoglutarate metabolically regulates P4HA activity in cancer cells.

    a, Schematic representation of the metabolic regulation and carbon donor mechanisms by which α-ketoglutarate can regulate collagen hydroxylation. Solid lines indicate metabolite conversion; dashed lines indicate metabolic regulation. Enzymes are depicted in bold and italics. P4HA, collagen prolyl-4-hydroxlase; P5CS, pyrroline-5-carboxylate synthase. b, c, Relative change in intracellular abundance of proline and hydroxylated collagen in MCF10A H-RASV12 spheroids transduced with a lentiviral vector with shRNA against either P5CS (KD) or a scrambled control sequence with or without cell-permeable α-ketoglutarate (1.5 mM) in the presence or absence of pyruvate normalized to the control condition. If the carbon donor mechanism occurs, it is expected that the abundance of proline decreases in P5CS knockdown spheroids and that they no longer respond to rescue by α-ketoglutarate upon pyruvate depletion. However, we observed that proline abundance did not significantly change in P5CS knockdown spheroids. Moreover, α-ketoglutarate addition still significantly increased hydroxylated collagen to a similar extent as pyruvate. n = 3 replicates (b); n = 6 control shRNA; n = 3 P5CS shRNA 1 and 2 (c). d, Hydroxylated collagen was assessed by measuring hydroxyproline in human (myo)fibroblasts in the presence or absence of pyruvate with or without cell-permeable α-ketoglutarate (1.5 mM) and/or cell-permeable succinate (1.5 mM). n = 3 human primary skin-derived fibroblasts; n = 4 human immortalized mammary and cancer associated myofibroblasts. e, Hydroxylated collagen was assessed by measuring hydroxyproline in human (myo)fibroblasts treated with the MCT2 inhibitor α-cyano-4-hydroxycinnamic acid (1.5 mM), the MPC inhibitor UK5099 (50 μM) or the transaminase inhibitor AOA (0.8 mM) in the presence of pyruvate. n = 3. f, Intracellular abundance of α-ketoglutarate in the presence or absence of pyruvate in human fibroblasts. n = 3. Data are mean ± s.d. of biological independent samples. Two-tailed unpaired Student’s t-test. Source data

  7. Extended Data Fig. 7 Metabolic regulation of P4HA activity is independent of its known transcriptional regulation.

    a, Absolute levels of P4HA1, P4HA2 and P4HA3 in human MCF10A H-RASV12 breast cancer spheroids in the presence of pyruvate. b, Relative change in P4HA1 gene expression upon pyruvate depletion as well as P4HA1 overexpression (OE) in normoxia, P4HA1 expression in hypoxia (1% oxygen), upon 12 ng ml−1 TGFβ addition and 50 μM IOX2 treatment normalized to the control condition with pyruvate. c, Relative P4HA1 or P4ha1 gene expression in human (MCF7 and HCC70) and mouse (4T1) breast cancer spheroids in the presence (normoxia) or absence (hypoxia (1% oxygen); IOX2 (50 μM); TGFβ (12 ng ml−1)) of pyruvate normalized to the normoxia condition with pyruvate. d, Hydroxylated collagen was assessed by measuring hydroxyproline in human (MCF10A H-RASV12, MCF7 and HCC70) and mouse (4T1) breast cancer spheroids treated with TGFβ (12 ng ml−1) or IOX2 (50 μM) with or without pyruvate or upon addition of cell-permeable α-ketoglutarate (1.5 mM). The number of biological replicates for each experiment was n = 3. Data are mean ± s.d. of biological independent samples. Two-tailed unpaired Student’s t-test. Source data

  8. Extended Data Fig. 8 Functional collagen deposition decreases in the lung metastatic niche upon pyruvate metabolism inhibition.

    Representative pictures of functional collagen of lung metastases tissue based on picro-Sirius red staining and polarized light microscopy. Red predominantly indicates tick collagen I fibres and green predominately indicates thin collagen III fibres. a, 4T1 model (m.f.) upon pharmacological inhibition of MCT2 (α-cyano-4-hydroxycinnamic acid; 60 mg per kg, i.p.). b, 4T1 (m.f.) and EMT6.5 (i.v.) models upon genetic inhibition of Mct2. c, 4T1 model (m.f.) upon pharmacological inhibition of MCT2 (α-cyano-4-hydroxycinnamic acid; 60 mg per kg, i.p.) with or without treatment with cell-permeable α-ketoglutarate (50 mg per kg, i.p.). d, 4T1 model (i.v.) upon genetic inhibition of Alt2. Scale bars, 50 μm.

  9. Extended Data Fig. 9 Metastatic burden decreases independently of primary tumour volume upon pyruvate metabolism inhibition.

    a, Primary tumour volume over time and final tumour weight upon pharmacological inhibition of MCT2 (α-cyano-4-hydroxycinnamic acid, 60 mg per kg, i.p.) with or without treatment with cell-permeable α-ketoglutarate (50 mg per kg, i.p.) in the 4T1 model (m.f.). n = 23 (vehicle, 3 cohorts), n = 24 (MCT2 inhibitor, 2 cohorts), n = 10 (MCT2 inhibitor and α-ketoglutarate). b, Primary tumour volume over time and final tumour weight upon genetic inhibition of MCT2 in the 4T1 model (m.f.). n = 11 (4T1 control), n = 7 (4T1 Mct2 gRNA). c, Representative pictures of tissue from lung metastases upon genetic inhibition of Mct2 in the 4T1 model (m.f.) based on haematoxylin and eosin staining. d, Representative pictures of tissue from lung metastases upon genetic inhibition of Mct2 in the EMT6.5 model (i.v.) based on haematoxylin and eosin staining. e, Representative pictures of tissue from lung metastases upon genetic inhibition of Alt2 in the 4T1 model (i.v.) based on haematoxylin and eosin staining. f, Representative pictures of tissue from lung metastases upon pharmacological inhibition of MCT2 (α-cyano-4-hydroxycinnamic acid; 60 mg per kg, i.p.) with or without treatment with cell-permeable α-ketoglutarate (50 mg per kg, i.p.) in the 4T1 model (m.f.) based on haematoxylin and eosin staining. The much milder effect of MCT2 inhibition compared to the previously described P4HA inhibition2 on primary tumour growth could be explained by our previous observation that pyruvate is less available to primary breast cancers than to lung metastases6. Arrow heads indicate metastasis tissue. Data are mean ± s.e.m. from different mice. Two-tailed unpaired Student’s t-test. Scale bars, 0.5 cm. Source data

  10. Extended Data Fig. 10 Protein and RNA expression of genetically modified breast cancer cells.

    a, Western blot analysis of MCT2 in human (MCF10A H-RASV12 and MCF7) and mouse (4T1 and EMT6.5) breast cancer cells infected with either a control gRNA or two different MCT2 or Mct2 gRNAs normalized to the control condition. Human positive/negative control: H460/MDA-MB-468; mouse positive/negative control: testis/lung. b, Western blot analysis and relative gene expression of GDH in human MCF10A H-RASV12 breast cancer cells infected with either a control shRNA or two different GDH shRNA normalized to the control condition. c, Western blot analysis and relative gene expression of ALT2 in human (MCF10A H-RASV12) and mouse (4T1) breast cancer cells infected with either a control shRNA or two different ALT2 or Alt2 shRNAs normalized to the control condition. d, Western blot analysis and relative gene expression of P5CS in human MCF10A H-RASV12 breast cancer cells infected with either a control shRNA or two different P5CS shRNAs. e, Western blot analysis of P4HA in human MCF10A H-RASV12 breast cancer cells infected with either a control or an P4HA-overexpression vector. f, g, Time-resolved contribution of 13C6-glucose, 13C5-glutamine and 13C3-pyruvate to α-ketoglutarate and alanine in human MCF10A H-RASV12 breast cancer spheroids. The number of biological replicates for each experiment was n = 3. Data are mean ± s.d. of biological independent samples. Two-tailed unpaired Student’s t-test. For gel source data, see Supplementary Fig. 1. Source data

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    This file contains the uncropped blots shown in Extended Data Figure 10.

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