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α-Ketoglutarate attenuates Wnt signaling and drives differentiation in colorectal cancer

Nature Cancer volume 1, pages 345–358 (2020)Cite this article

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Abstract

Genetic-driven deregulation of the Wnt pathway is crucial but not sufficient for colorectal cancer (CRC) tumorigenesis. Here, we show that environmental glutamine restriction further augments Wnt signaling in APC-mutant intestinal organoids to promote stemness, and leads to adenocarcinoma formation in vivo via decreasing intracellular α-ketoglutarate (αKG) levels. αKG supplementation is sufficient to rescue low-glutamine-induced stemness and Wnt hyperactivation. Mechanistically, we found that αKG promotes hypomethylation of DNA and histone H3K4me3, leading to an upregulation of differentiation-associated genes and downregulation of Wnt target genes, respectively. Using organoids derived from patients with CRC and several in vivo CRC tumor models, we show that αKG supplementation suppresses Wnt signaling and promotes cellular differentiation, thereby significantly restricting tumor growth and extending survival. Together, our results reveal how the metabolic microenvironment impacts Wnt signaling and identify αKG as a potent antineoplastic metabolite for potential differentiation therapy for patients with CRC.

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Fig. 1: Environmental glutamine restriction hyperactivates Wnt signaling and blocks cellular differentiation.
Fig. 2: Glutamine restriction promotes self-renewal and niche independence in ApcMin/+ organoids.
Fig. 3: αKG supplementation rescues low-glutamine-induced stemness and suppresses Wnt signaling.
Fig. 4: αKG supplementation leads to DNA hypomethylation of genes related to differentiation and Wnt inhibition.
Fig. 5: αKG supplementation drives terminal differentiation and suppresses the growth of patient-derived colon tumor organoids.
Fig. 6: αKG supplementation inhibits the growth of highly mutated CRC tumors in vivo.
Fig. 7: αKG supplementation is an effective therapeutic intervention in a mouse model of intestinal cancer.

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Data availability

DNA sequencing and RNA-Seq data that support the findings of this study have been deposited in the Gene Expression Omnibus under accession code GSE140270. SuperSeries GSE140270 is composed of the following SubSeries: GSE140263, GSE140264, GSE140265, GSE140266, GSE140267 and GSE140269. Metabolomics raw data are included in Supplementary Table 5. Source data for Figs. 1–3 and 5–7 and Extended Data Figs. 1–7 are provided with the paper. All other data supporting the findings of this study are available from the corresponding author upon reasonable request.

References

  1. Torre, L. A. et al. Global cancer statistics, 2012. CA Cancer J. Clin. 65, 87–108 (2015).

    PubMed  Google Scholar 

  2. Fearon, E. R. Molecular genetics of colorectal cancer. Annu. Rev. Pathol. 6, 479–507 (2011).

    CAS  PubMed  Google Scholar 

  3. Schepers, A. & Clevers, H. Wnt signaling, stem cells, and cancer of the gastrointestinal tract. Cold Spring Harb. Perspect. Biol. 4, a007989 (2012).

    PubMed  PubMed Central  Google Scholar 

  4. Drost, J. et al. Sequential cancer mutations in cultured human intestinal stem cells. Nature 521, 43–47 (2015).

    CAS  PubMed  Google Scholar 

  5. Kinzler, K. W. & Vogelstein, B. Lessons from hereditary colorectal cancer. Cell 87, 159–170 (1996).

    CAS  PubMed  Google Scholar 

  6. Fearon, E. R. & Vogelstein, B. A genetic model for colorectal tumorigenesis. Cell 61, 759–767 (1990).

    CAS  PubMed  Google Scholar 

  7. De Sousa e Melo, F. et al. A distinct role for Lgr5+ stem cells in primary and metastatic colon cancer. Nature 543, 676–680 (2017).

    CAS  PubMed  Google Scholar 

  8. Medema, J. P. Targeting the colorectal cancer stem cell. N. Engl. J. Med. 377, 888–890 (2017).

    PubMed  Google Scholar 

  9. Vermeulen, L. et al. Wnt activity defines colon cancer stem cells and is regulated by the microenvironment. Nat. Cell Biol. 12, 468–476 (2010).

    CAS  PubMed  Google Scholar 

  10. Pate, K. T. et al. Wnt signaling directs a metabolic program of glycolysis and angiogenesis in colon cancer. EMBO J. 33, 1454–1473 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  11. Gao, P. et al. c-Myc suppression of miR-23a/b enhances mitochondrial glutaminase expression and glutamine metabolism. Nature 458, 762–765 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  12. Huang, F., Zhang, Q., Ma, H., Lv, Q. & Zhang, T. Expression of glutaminase is upregulated in colorectal cancer and of clinical significance. Int. J. Clin. Exp. Pathol. 7, 1093–1100 (2014).

    PubMed  PubMed Central  Google Scholar 

  13. Kim, M. H. & Kim, H. The roles of glutamine in the intestine and its implication in intestinal diseases. Int. J. Mol. Sci. 18, E1051 (2017).

    PubMed  Google Scholar 

  14. Le, A. et al. Glucose-independent glutamine metabolism via TCA cycling for proliferation and survival in B cells. Cell Metab. 15, 110–121 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  15. Carey, B. W., Finley, L. W., Cross, J. R., Allis, C. D. & Thompson, C. B. Intracellular α-ketoglutarate maintains the pluripotency of embryonic stem cells. Nature 518, 413–416 (2015).

    CAS  PubMed  Google Scholar 

  16. Pan, M. et al. Regional glutamine deficiency in tumours promotes dedifferentiation through inhibition of histone demethylation. Nat. Cell Biol. 18, 1090–1101 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  17. Tran, T. Q., Lowman, X. H. & Kong, M. Molecular pathways: metabolic control of histone methylation and gene expression in cancer. Clin. Cancer Res. 23, 4004–4009 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  18. Altman, B. J., Stine, Z. E. & Dang, C. V. From Krebs to clinic: glutamine metabolism to cancer therapy. Nat. Rev. Cancer 16, 619–634 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  19. Denkert, C. et al. Metabolite profiling of human colon carcinoma—deregulation of TCA cycle and amino acid turnover. Mol. Cancer 7, 72 (2008).

    PubMed  PubMed Central  Google Scholar 

  20. Schuijers, J. et al. Ascl2 acts as an R-Spondin/Wnt-responsive switch to control stemness in intestinal crypts. Cell Stem Cell 16, 158–170 (2015).

    CAS  PubMed  Google Scholar 

  21. Gregorieff, A. & Clevers, H. Wnt signaling in the intestinal epithelium: from endoderm to cancer. Genes Dev. 19, 877–890 (2005).

    CAS  PubMed  Google Scholar 

  22. Voronov, E. & Apte, R. N. IL-1 in colon inflammation, colon carcinogenesis and invasiveness of colon cancer. Cancer Microenviron. 8, 187–200 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  23. Sato, T. et al. Single Lgr5 stem cells build crypt–villus structures in vitro without a mesenchymal niche. Nature 459, 262–265 (2009).

    CAS  PubMed  Google Scholar 

  24. Tse, J. W. T., Jenkins, L. J., Chionh, F. & Mariadason, J. M. Aberrant DNA methylation in colorectal cancer: what should we target? Trends Cancer 3, 698–712 (2017).

    CAS  PubMed  Google Scholar 

  25. Kim, R., Sheaffer, K. L., Choi, I., Won, K. J. & Kaestner, K. H. Epigenetic regulation of intestinal stem cells by Tet1-mediated DNA hydroxymethylation. Genes Dev. 30, 2433–2442 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  26. Ashktorab, H. & Brim, H. DNA methylation and colorectal cancer. Curr. Colorectal Cancer Rep. 10, 425–430 (2014).

    PubMed  PubMed Central  Google Scholar 

  27. Morris, L. G. et al. Recurrent somatic mutation of FAT1 in multiple human cancers leads to aberrant Wnt activation. Nat. Genet. 45, 253–261 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  28. Baehs, S. et al. Dickkopf-4 is frequently down-regulated and inhibits growth of colorectal cancer cells. Cancer Lett. 276, 152–159 (2009).

    CAS  PubMed  Google Scholar 

  29. TeSlaa, T. et al. α-Ketoglutarate accelerates the initial differentiation of primed human pluripotent stem cells. Cell Metab. 24, 485–493 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  30. Salz, T. et al. hSETD1A regulates Wnt target genes and controls tumor growth of colorectal cancer cells. Cancer Res. 74, 775–786 (2014).

    CAS  PubMed  Google Scholar 

  31. Sierra, J., Yoshida, T., Joazeiro, C. A. & Jones, K. A. The APC tumor suppressor counteracts β-catenin activation and H3K4 methylation at Wnt target genes. Genes Dev. 20, 586–600 (2006).

    CAS  PubMed  PubMed Central  Google Scholar 

  32. Ring, A., Kim, Y. M. & Kahn, M. Wnt/catenin signaling in adult stem cell physiology and disease. Stem Cell Rev. 10, 512–525 (2014).

    CAS  PubMed Central  Google Scholar 

  33. Degos, L. & Wang, Z. Y. All trans retinoic acid in acute promyelocytic leukemia. Oncogene 20, 7140–7145 (2001).

    CAS  PubMed  Google Scholar 

  34. Vlachogiannis, G. et al. Patient-derived organoids model treatment response of metastatic gastrointestinal cancers. Science 359, 920–926 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  35. Dow, L. E. et al. Apc restoration promotes cellular differentiation and reestablishes crypt homeostasis in colorectal cancer. Cell 161, 1539–1552 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  36. De Rosa, M. et al. Genetics, diagnosis and management of colorectal cancer (Review). Oncol. Rep. 34, 1087–1096 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  37. Moser, A. R. et al. ApcMin: a mouse model for intestinal and mammary tumorigenesis. Eur. J. Cancer 31A, 1061–1064 (1995).

    CAS  PubMed  Google Scholar 

  38. Kamphorst, J. J. et al. Human pancreatic cancer tumors are nutrient poor and tumor cells actively scavenge extracellular protein. Cancer Res. 75, 544–553 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  39. Roberts, E. et al. Amino acids in epidermal carcinogenesis in mice. Cancer Res. 9, 350–353 (1949).

    CAS  PubMed  Google Scholar 

  40. Miyo, M. et al. Metabolic adaptation to nutritional stress in human colorectal cancer. Sci. Rep. 6, 38415 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  41. Reid, M. A. et al. The B55α subunit of PP2A drives a p53-dependent metabolic adaptation to glutamine deprivation. Mol. Cell 50, 200–211 (2013).

    CAS  PubMed  Google Scholar 

  42. Tran, T. Q. et al. Tumor-associated mutant p53 promotes cancer cell survival upon glutamine deprivation through p21 induction. Oncogene 36, 1991–2001 (2017).

    CAS  PubMed  Google Scholar 

  43. Yang, Y. et al. MiR-135 suppresses glycolysis and promotes pancreatic cancer cell adaptation to metabolic stress by targeting phosphofructokinase-1. Nat. Commun. 10, 809 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  44. Lowman, X. H. et al. p53 promotes cancer cell adaptation to glutamine deprivation by upregulating Slc7a3 to increase arginine uptake. Cell Rep. 26, 3051–3060.e4 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  45. Carnero, A. & Lleonart, M. The hypoxic microenvironment: a determinant of cancer stem cell evolution. BioEssays 38, S65–S74 (2016).

    PubMed  Google Scholar 

  46. Sullivan, R., Pare, G. C., Frederiksen, L. J., Semenza, G. L. & Graham, C. H. Hypoxia-induced resistance to anticancer drugs is associated with decreased senescence and requires hypoxia-inducible factor-1 activity. Mol. Cancer Ther. 7, 1961–1973 (2008).

    CAS  PubMed  Google Scholar 

  47. Raa, A. et al. Hyperoxia retards growth and induces apoptosis and loss of glands and blood vessels in DMBA-induced rat mammary tumors. BMC Cancer 7, 23 (2007).

    PubMed  PubMed Central  Google Scholar 

  48. Stuhr, L. E. et al. Hyperoxia retards growth and induces apoptosis, changes in vascular density and gene expression in transplanted gliomas in nude rats. J. Neurooncol. 85, 191–202 (2007).

    CAS  PubMed  Google Scholar 

  49. Stępień, K., Ostrowski, R. P. & Matyja, E. Hyperbaric oxygen as an adjunctive therapy in treatment of malignancies, including brain tumours. Med. Oncol. 33, 101 (2016).

    PubMed  PubMed Central  Google Scholar 

  50. Miyoshi, Y. et al. Somatic mutations of the APC gene in colorectal tumors: mutation cluster region in the APC gene. Hum. Mol. Genet. 1, 229–233 (1992).

    CAS  PubMed  Google Scholar 

  51. Voloshanenko, O. et al. Wnt secretion is required to maintain high levels of Wnt activity in colon cancer cells. Nat. Commun. 4, 2610 (2013).

    PubMed  Google Scholar 

  52. Schneikert, J., Grohmann, A. & Behrens, J. Truncated APC regulates the transcriptional activity of β-catenin in a cell cycle dependent manner. Hum. Mol. Genet. 16, 199–209 (2007).

    CAS  PubMed  Google Scholar 

  53. Pai, R. et al. Prostaglandin E2 transactivates EGF receptor: a novel mechanism for promoting colon cancer growth and gastrointestinal hypertrophy. Nat. Med. 8, 289–293 (2002).

    CAS  PubMed  Google Scholar 

  54. Janssen, K. P. et al. APC and oncogenic KRAS are synergistic in enhancing Wnt signaling in intestinal tumor formation and progression. Gastroenterology 131, 1096–1109 (2006).

    CAS  PubMed  Google Scholar 

  55. Jemal, A. et al. Global cancer statistics. CA Cancer J. Clin. 61, 69–90 (2011).

    PubMed  Google Scholar 

  56. Seshagiri, S. et al. Recurrent R-Spondin fusions in colon cancer. Nature 488, 660–664 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  57. The Cancer Genome Atlas Network. Comprehensive molecular characterization of human colon and rectal cancer. Nature 487, 330–337 (2012).

    Google Scholar 

  58. Krishnamurthy, N. & Kurzrock, R. Targeting the Wnt/beta-catenin pathway in cancer: update on effectors and inhibitors. Cancer Treat. Rev. 62, 50–60 (2018).

    CAS  PubMed  Google Scholar 

  59. Jimeno, A. et al. A first-in-human phase I study of the anticancer stem cell agent ipafricept (OMP-54F28), a decoy receptor for Wnt ligands, in patients with advanced solid tumors. Clin. Cancer Res. 23, 7490–7497 (2017).

    CAS  PubMed  Google Scholar 

  60. O’Rourke, K. P., Ackerman, S., Dow, L. E. & Lowe, S. W. Isolation, culture, and maintenance of mouse intestinal stem cells. Bio Protoc. 6, e1733 (2016).

    PubMed  Google Scholar 

  61. Van de Wetering, M. et al. Prospective derivation of a living organoid biobank of colorectal cancer patients. Cell 161, 933–945 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  62. Tran, T. Q. et al. Glutamine deficiency induces DNA alkylation damage and sensitizes cancer cells to alkylating agents through inhibition of ALKBH enzymes. PLoS Biol. 15, e2002810 (2017).

    PubMed  PubMed Central  Google Scholar 

  63. Liu, X., Ser, Z. & Locasale, J. W. Development and quantitative evaluation of a high-resolution metabolomics technology. Anal. Chem. 86, 2175–2184 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  64. Tong, K. et al. Degree of tissue differentiation dictates susceptibility to BRAF-driven colorectal cancer. Cell Rep. 21, 3833–3845 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

We thank members of the Kong laboratory and the Waterman laboratory, as well as E. J. Stanbridge, for helpful comments on the manuscript. We thank D. T. Florina for assistance with the animal experiments, and the L. Dow Laboratory (Weill Cornell) for the AKP organoids. This research was supported by funds from the NIH (R01CA183989 and R01GM132142 to M.K.; R01CA17765 to M.L.W. and R.A.E.; and U54CA217378 to M.L.W.) and American Cancer Society (grant number RSG-16-085-01-TBE to M.K.). E.A.H. is supported by the American Cancer Society (PFDDC-132846). A.N.H. is supported by NSF grant DGE‐1321846 and NIH grant T32CA009054. Research reported here includes work carried out in Core Facilities at the University of California Irvine, supported by the NIH under grant number P30CA062203.

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Author notes

  1. These authors contributed equally: Eric A. Hanse, Amber N. Habowski.

Authors and Affiliations

  1. Department of Molecular Biology and Biochemistry, University of California, Irvine, Irvine, CA, USA

    Thai Q. Tran, Eric A. Hanse, Mari B. Ishak Gabra, Ying Yang, Xazmin H. Lowman, Amelia M. Ooi & Mei Kong

  2. Department of Microbiology and Molecular Genetics, University of California, Irvine, Irvine, CA, USA

    Amber N. Habowski & Marian L. Waterman

  3. Division of Informatics, Department of Computational and Quantitative Medicine, Center of Informatics, Beckman Research Institute of City of Hope Cancer Center, Duarte, CA, USA

    Haiqing Li

  4. Department of Pathology and Laboratory Medicine, University of California, Irvine, Irvine, CA, USA

    Shu Y. Liao & Robert A. Edwards

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Contributions

T.Q.T. conceived of the project, designed and performed the majority of the experiments and wrote the manuscript. M.K. conceived of the project, supervised the study, designed the experiments and wrote the manuscript. E.A.H. performed the ChIP experiments, metabolite measurements and animal studies and contributed to manuscript preparation. A.N.H. provided materials, performed the PDO culture experiments and contributed to manuscript preparation. H.L. performed the bioinformatic analyses. M.B.I.G. and Y.Y. assisted with the animal studies. X.H.L. and A.M.O. assisted with qPCR and sample preparation. S.Y.L. provided clinical samples for the PDOs. R.A.E. assisted with the pathological analysis. M.L.W. provided conceptual advice on the experimental design and assisted with manuscript preparation.

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Correspondence to Mei Kong.

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Extended data

Extended Data Fig. 1 The effect of glutamine starvation on ApcMin/+ and wildtype organoids.

a, Relative glutamine uptake in ApcMin/+ organoids and wildtype organoids (n=3 biologically independent samples) and relative glutamine uptake in AKP organoids upon doxycycline addition (n=4 biologically independent samples). b, Percentage of cystic organoid in ApcMin/+ organoids upon glutamine deprivation (0.2 mM and 0.4 mM) overtime (n=7 biologically independent cultures). c, Percentage of cystic organoids and organoid number of ApcMin/+ organoids treated with CB-839 for 1 week (n=3 biologically independent cultures). d, Percentage of wildtype organoids with cystic morphology after 4 passages in low glutamine conditon (n=6 biologically independent cultures). e, qPCR analysis of Axin2 in wildtype organoids cultured in control or low glutamine medium for 1 week. Data from n=3 independent experiments with a line marking the mean value. (f,g) Control and glutamine-starved wildtype organoids were dissociated into single cells, and equal number of organoid-derived cells were cultured in organoid medium with 3 mM or 0.3 mM glutamine (low gln). Secondary organoid formation and percentage of cystic organoids are shown (n=9 biologically independent cultures). Data in a-e,g represent means ± SD, p values were determined by two-tailed unpaired Student’s t-test. Scale bars, 1000 μm (c,d,f). Source data are provided for a-e,g.

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Extended Data Fig. 2 Genetic alterations do not contribute to low-glutamine induced stemness.

a, Identified genetic alterations in glutamine-starved ApcMin/+ organoids compared to paired control organoids as determined by exome sequencing. b, Brightfield images of control and glutamine-starved ApcMin/+organoids after 12 passages. Results are representative of three biologically independent cultures. c, Immunoblotting for full length and truncated Apc protein in control and glutamine starved ApcMin/+ organoids after 8 passages. Results are representative of three independent experiments. d, Representative images and percentage of cells with full-length Apc protein based on immunofluorescent staining with C-terminus Apc antibody in wildtype organoids, tumour organoids derived from adenomas derived in ApcMin/+ mice, and ApcMin/+organoids from healthy tissues in control medium and upon glutamine deprivation (n=4 biologically independent cultures), data represent means ± SD. (e,f) Representative images and percentage of shApc /KrasG12D/p53fl/fl (AKP) organoid with crypts cultured in control or low glutamine medium for 10 days (n=5 biologically independent cultures). g, qPCR analysis of Krt20 and Lgr5 in a similar experiment described in e after 3 days of glutamine deprivation. Data from n=2 independent experiments with a line marking the mean value. h, Hierarchical clustering of significant differentiated gene expression of ApcMin/+ organoids cultured in control or low-glutamine medium (n=3 biologically independent samples). i, qPCR analysis of the indicated genes in SW620 colon cancer cells (n=3 technical replicates and data represent means) cultured in medium with the indicated glutamine concentration for 3 days. A single experiment is shown that is representative of two independent experiments with similar results. Scale bars, 200 µm (b), 400 μm (d,e). Unprocessed blot images for c and source data for d,f,g,i are provided.

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Extended Data Fig. 3 The role of aKG in low-glutamine induced stemness.

a, Schematic diagram of glutamine metabolism. b, Relative metabolite levels as measured by LC-MS in ApcMin/+ organoids cultured in control and low glutamine medium (n=4 biologically independent samples). c, Relative aKG levels in intestinal tumours from ApcMin/+ mice and normal intestinal tissues of wildtype mice (n=5 mice per group). Data in b,c represent means ± SD, and p values were determined by two-tailed unpaired Student’s t-test. (d,e) Relative intracellular aKG and succinate levels in ApcMin/+ organoids upon DM-aKG (n=5 biologically independent samples) or DM-succinate supplementation (n=6 biologically independent samples). f, Immunofluorescent staining for ROS in ApcMin/+ organoids under low glutamine or low glutamine medium supplemented with NAC. Results are representative from three biologically independent samples. g, Control organoids, glutamine-starved organoids treated with or without 3.5 mM DM-aKG were dissociated into single cells. An equal number of organoid-derived cells were cultured, and secondary organoid formation (n=6 biologically independent cultures) and cell proliferation (n=3 biologically independent cultures) were measured after 1 week and are shown. p values were determined by two-tailed unpaired Student’s t-test. h, Immunoblotting for Lgr5 and (i) qPCR analysis for Axin2 expression in ApcMin/+ organoid cultured in control and low glutamine medium with or without DM-aKG (n= 2 independent experiments with a line marking the mean value). Box plots in d,e,g show the maximum, third quartile, median, first quartile and minimum values, and the p values were determined by two-tailed unpaired Student’s t-test. Scale bar, 400 μm f, 1000 μm g. Unprocessed blot images for h and source data for b-e and g,i are provided.

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Extended Data Fig. 4 The effect of aKG and glutamine supplementation on intestinal differentiation.

a, Representative brightfield images and immunofluorescent staining of the differentiation marker Krt20 in ApcMin/+ organoids treated with 3 mM DM-aKG for 3 days. Results are representative of three independent experiments. b, Representative images and relative organoid number of control ApcMin/+ organoid or glutamine-starved ApcMin/+ organoids upon 2 mM DM-aKG treatment or 6mM glutamine addition for 1 week (n=3 biologically independent cultures). Data represent means ± SD, and the p values were determined by two-tailed unpaired Student’s t-test. c, Overlapping gene expression profile of ApcMin/+ organoids cultured in low glutamine medium or treated with aKG reveals opposing regulation on Wnt target genes and intestinal differentiation related genes. Scale bars, 1000 μm (Brightfield), 200 μm (Immunofluorescence). Source data are provided for b.

Source data

Extended Data Fig. 5 aKG promotes hypomethylation of histone and DNA in CRC cells.

a, qPCR analysis of Axin2 in control and glutamine-starved organoids treated with 1 μM decitabine for 3 days. Data from n=2 independent experiments with a line marking the mean value. (b,c) Dot blot analysis of 5meC levels in ApcMin/+ organoids in control and low glutamine medium and SW620 cells in control, low glutamine medium or low glutamine medium supplemented with 8mM DM-aKG. Results are representative from two independent experiments. d, Heatmap of the differential methylated regions (different methylated ratio >±20%) in SW620 cells upon 8 mM DM-aKG treatment for 3 days. Beta value of the methylation ratio are shown (n=2 biologically independent samples). e, qPCR analysis of Dkk4 in ApcMin/+ organoids treated with 3.5 mM DM-aKG or 1 μM decitabine (n=3 technical replicates). A repeat experiment showed similar results. f, Dot blot analysis of 5meC levels in SW620 cells treated with DM-aKG (left), MeDIP experiment with 5meC antibody for DKK4 promoter in SW620 cells upon 8 mM DM-aKG treatment (right). Data show means ± SD of n=4 technical replicates. Results are representative of two independent experiments. g, qPCR analysis of TET1 expression in SW620 cells transfected with control siRNA or TET1 siRNA (data show means of n=3 technical replicates). h, qPCR analysis of DKK4 and LGR5 expression in control SW620 cells or TET1 siRNA knockdown cells following DM-aKG treatment. Data from n=2 independent experiments with a line marking the mean value. i, Representative immunoblot of histone methylation in SW620 cells treated with DM-aKG from two independent experiments. j, ChIP analysis of H3K4 levels on promoter regions of AXIN2 and MYC in SW620 cells in response to 8mM DM-aKG treatment for 3 days (n=4 technical replicates). k, Representative immunoblot of H3K4me3 in SW620 cells in control, low-glutamine medium or low glutamine medium supplemented with 8 mM DM-aKG from two independent experiments. l, ChIP analysis of H3K4me3 levels on promoter regions of AXIN2 and MYC in SW620 cells in response to glutamine starvation after 1 week (n=4 technical replicates). Results in j and l represent means ± SD and are representative of two independent experiments. Unprocessed blot images are provided for b,c,f, i and k. Source data are provided for a,e-h,j, and l.

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Extended Data Fig. 6 DM-aKG treatment inhibits initiation and growth of PDOs.

a, Clinical information on PDOs used in the study. b, Immunoblot probed for Apc protein in different PDOs. c, Relative organoid size (n=50 organoids) and d, representative images of four biologically independent cultures of T23 PDO treated with 6 mM DM-aKG for 7 days, followed by metabolite wash-out and subsequent culture for 7 days. Data in c represent means ± SD. Scale bar, 400 μm (d). Unprocessed blot images for b and source data for c is provided.

Source data

Extended Data Fig. 7 The effect of DM-aKG treatment in mice.

a, Body weight and histological analysis of wildtype mice treated with 400 mg/kg DM-aKG via IP injection for more than 2 months (n=4 mice per group). b, Representative IHC staining for Cyclin D1 in intestinal tissues collected from ApcMin/+ mice treated with DM-aKG from three mice per group. c, Gene expression analysis from RNA sequencing performed on the intestinal tissues of wildtype mice (n=7 mice), ApcMin/+ mice (n=7 mice), and ApcMin/+ mice treated with DM-aKG (n=6 mice). d, Body weight changes and images of liver and spleen from ApcMin/+ mice treated with DM-aKG (n=5 mice per group). e, Liver and kidney function of wildtype mice treated with 15 mg/ml DM-aKG supplemented in drinking water for more than 4 months (n=5 mice per group). Data shown in a,d,e are means ± SD. The p values in e were determined by two-tailed unpaired Student’s t-test. Source data are provided for a,d,e.

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Supplementary information

Reporting Summary

Supplementary Tables

Supplementary Tables 1–5.

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Tran, T.Q., Hanse, E.A., Habowski, A.N. et al. α-Ketoglutarate attenuates Wnt signaling and drives differentiation in colorectal cancer. Nat Cancer 1, 345–358 (2020). https://doi.org/10.1038/s43018-020-0035-5

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