Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Age-associated mitochondrial DNA mutations cause metabolic remodeling that contributes to accelerated intestinal tumorigenesis

An Author Correction to this article was published on 30 November 2020

This article has been updated

Abstract

Oxidative phosphorylation (OXPHOS) defects caused by somatic mitochondrial DNA mutations increase with age in human colorectal epithelium and are prevalent in colorectal tumors, but whether they actively contribute to tumorigenesis remains unknown. Here we demonstrate that mitochondrial DNA mutations causing OXPHOS defects are enriched during the human adenoma/carcinoma sequence, suggesting that they may confer a metabolic advantage. To test this, we deleted the tumor suppressor Apc in OXPHOS-deficient intestinal stem cells in mice. The resulting tumors were larger than in control mice due to accelerated cell proliferation and reduced apoptosis. We show that both normal crypts and tumors undergo metabolic remodeling in response to OXPHOS deficiency by upregulating the de novo serine synthesis pathway. Moreover, normal human colonic crypts upregulate the serine synthesis pathway in response to OXPHOS deficiency before tumorigenesis. Our data show that age-associated OXPHOS deficiency causes metabolic remodeling that can functionally contribute to accelerated intestinal cancer development.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: OXPHOS subunit IHC and histochemical analysis of human colorectal adenomas and adenocarcinomas.
Fig. 2: Analysis of mtDNA mutations detected in 26 colorectal adenocarcinomas compared with normal aged crypts.
Fig. 3: PolgAmut/mut;Apcfl/fl mice have a reduced lifespan and enhanced tumor growth due to accelerated cell proliferation and reduced apoptosis compared with Apcfl/fl mice.
Fig. 4: Small intestinal adenomas from PolgAmut/mut;Apcfl/fl mice are deficient in mitochondrial complex I, but the majority retain expression of subunits of complexes III, IV and V.
Fig. 5: Mitochondrial OXPHOS dysfunction causes upregulation of de novo serine synthesis in both non-transformed crypts and adenomas from mice.
Fig. 6: Characterization of the immune microenvironment in the lamina propria of the small intestine of PolgAmut/mut and PolgA+/+ mice at 6 months of age, before tumor induction.
Fig. 7: Mitochondrial OXPHOS dysfunction causes upregulation of de novo serine synthesis in normal aging human colonic crypts.

Similar content being viewed by others

Data availability

RNA-Seq and DNA next-generation sequencing data have been deposited in the Sequence Read Archive under BioProject accession code PRJNA645504. 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.

Code availability

Code used to generate the mitochondrial OXPHOS Z scores and dot pots is freely available at http://mito.ncl.ac.uk/immuno/. The R programming code used in the linear regression mixed-effects modeling is available upon request.

Change history

  • 30 November 2020

    A Correction to this paper has been published: https://doi.org/10.1038/s43018-020-00156-7.

References

  1. Warburg, O. On the origin of cancer cells. Science 123, 309–314 (1956).

    CAS  PubMed  Google Scholar 

  2. Warburg, O. On respiratory impairment in cancer cells. Science 124, 269–270 (1956).

    CAS  PubMed  Google Scholar 

  3. Pedersen, P. L. Tumor mitochondria and the bioenergetics of cancer cells. Prog. Exp. Tumor Res. 22, 190–274 (1978).

    CAS  PubMed  Google Scholar 

  4. Marchetti, P. et al. Mitochondrial permeability transition is a central coordinating event of apoptosis. J. Exp. Med. 184, 1155–1160 (1996).

    CAS  PubMed  Google Scholar 

  5. Rosenzweig, A., Blenis, J. & Gomes, A. P. Beyond the Warburg effect: how do cancer cells regulate one-carbon metabolism? Front. Cell Dev. Biol. https://doi.org/10.3389/fcell.2018.00090 (2018).

  6. Diebold, L. & Chandel, N. S. Mitochondrial ROS regulation of proliferating cells. Free Radic. Biol. Med. 100, 86–93 (2016).

    CAS  PubMed  Google Scholar 

  7. Bender, A. et al. High levels of mitochondrial DNA deletions in substantia nigra neurons in aging and Parkinson disease. Nat. Genet. 38, 515–517 (2006).

    CAS  PubMed  Google Scholar 

  8. Fellous, T. G. et al. Locating the stem cell niche and tracing hepatocyte lineages in human liver. Hepatology 49, 1655–1663 (2009).

    CAS  PubMed  Google Scholar 

  9. Muller-Hocker, J. Cytochrome-c-oxidase deficient cardiomyocytes in the human heart—an age-related phenomenon. A histochemical ultracytochemical study. Am. J. Pathol. 134, 1167–1173 (1989).

    CAS  PubMed  PubMed Central  Google Scholar 

  10. Muller-Hocker, J. Cytochrome c oxidase deficient fibres in the limb muscle and diaphragm of man without muscular disease: an age-related alteration. J. Neurol. Sci. 100, 14–21 (1990).

    CAS  PubMed  Google Scholar 

  11. Greaves, L. C. et al. Defects in multiple complexes of the respiratory chain are present in ageing human colonic crypts. Exp. Gerontol. 45, 573–579 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  12. Greaves, L. C. et al. Clonal expansion of early to mid-life mitochondrial DNA point mutations drives mitochondrial dysfunction during human ageing. PLoS Genet. 10, e1004620 (2014).

    PubMed  PubMed Central  Google Scholar 

  13. Taylor, R. W. et al. Mitochondrial DNA mutations in human colonic crypt stem cells. J. Clin. Invest. 112, 1351–1360 (2003).

    CAS  PubMed  PubMed Central  Google Scholar 

  14. Lightowlers, R. N., Chinnery, P. F., Turnbull, D. M. & Howell, N. Mammalian mitochondrial genetics: heredity, heteroplasmy and disease. Trends Genet. 13, 450–455 (1997).

    CAS  PubMed  Google Scholar 

  15. Bao, X. R. et al. Mitochondrial dysfunction remodels one-carbon metabolism in human cells. eLife 5, e10575 (2016).

    PubMed  PubMed Central  Google Scholar 

  16. Yuan, Y. et al. Comprehensive molecular characterization of mitochondrial genomes in human cancers. Nat. Genet. 52, 342–352 (2020).

    CAS  PubMed  PubMed Central  Google Scholar 

  17. He, Y. et al. Heteroplasmic mitochondrial DNA mutations in normal and tumour cells. Nature 464, 610–614 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  18. Larman, T. C. et al. Spectrum of somatic mitochondrial mutations in five cancers. Proc. Natl Acad. Sci. USA 109, 14087–14091 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  19. Polyak, K. et al. Somatic mutations of the mitochondrial genome in human colorectal tumours. Nat. Genet. 20, 291–293 (1998).

    CAS  PubMed  Google Scholar 

  20. Bowel Cancer Statistics (CRUK); http://www.cancerresearchuk.org/health-professional/cancer-statistics/statistics-by-cancer-type/bowel-cancer (accessed March 2020).

  21. Greaves, L. C. et al. Comparison of mitochondrial mutation spectra in ageing human colonic epithelium and disease: absence of evidence for purifying selection in somatic mitochondrial DNA point mutations. PLoS Genet. 8, e1003082 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  22. Ericson, N. G. et al. Decreased mitochondrial DNA mutagenesis in human colorectal cancer. PLoS Genet. 8, e1002689 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  23. Greaves, L. C. et al. Mitochondrial DNA mutations are established in human colonic stem cells, and mutated clones expand by crypt fission. Proc. Natl Acad. Sci. USA 103, 714–719 (2006).

    CAS  PubMed  PubMed Central  Google Scholar 

  24. Barker, N. et al. Crypt stem cells as the cells-of-origin of intestinal cancer. Nature 457, 608–611 (2009).

    CAS  PubMed  Google Scholar 

  25. Kujoth, G. C. et al. Mitochondrial DNA mutations, oxidative stress, and apoptosis in mammalian aging. Science 309, 481–484 (2005).

    CAS  PubMed  Google Scholar 

  26. Trifunovic, A. et al. Premature ageing in mice expressing defective mitochondrial DNA polymerase. Nature 429, 417–423 (2004).

    CAS  PubMed  Google Scholar 

  27. Baines, H. L. et al. Similar patterns of clonally expanded somatic mtDNA mutations in the colon of heterozygous mtDNA mutator mice and ageing humans. Mech. Ageing Dev. 139, 22–30 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  28. Stamp, C. et al. Predominant asymmetrical stem cell fate outcome limits the rate of niche succession in human colonic crypts. EBioMedicine 31, 166–173 (2018).

    PubMed  PubMed Central  Google Scholar 

  29. Rocha, M. C. et al. A novel immunofluorescent assay to investigate oxidative phosphorylation deficiency in mitochondrial myopathy: understanding mechanisms and improving diagnosis. Sci. Rep. 5, 15037 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  30. 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 

  31. Fox, R. G., Magness, S., Jujoth, G. C., Prolla, T. A. & Maeda, N. Mitochondrial DNA polymerase editing mutation, PolgD257A, disturbs stem-progenitor cell cycling in the small intestine and restricts excess fat absorption. Am. J. Physiol. Gastrointest. Liver Physiol. 302, G914–G924 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  32. El-Mir, M. Y. et al. Dimethylbiguanide inhibits cell respiration via an indirect effect targeted on the respiratory chain complex I. J. Biol. Chem. 275, 223–228 (2000).

    CAS  PubMed  Google Scholar 

  33. Owen, M. R., Doran, E. & Halestrap, A. P. Evidence that metformin exerts its anti-diabetic effects through inhibition of complex 1 of the mitochondrial respiratory chain. Biochem. J. 348, 607–614 (2000).

    CAS  PubMed  PubMed Central  Google Scholar 

  34. Maddocks, O. D. K. et al. Modulating the therapeutic response of tumours to dietary serine and glycine starvation. Nature 544, 372–376 (2017).

    CAS  PubMed  Google Scholar 

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

    CAS  PubMed  Google Scholar 

  36. Winawer, S. J. et al. Colorectal cancer screening: clinical guidelines and rationale. Gastroenterology 112, 594–642 (1997).

    CAS  PubMed  Google Scholar 

  37. Nikkanen, J. et al. Mitochondrial DNA replication defects disturb cellular dNTP pools and remodel one-carbon metabolism. Cell Metab. 23, 635–648 (2016).

    CAS  PubMed  Google Scholar 

  38. Rodriguez-Colman, M. J. et al. Interplay between metabolic identities in the intestinal crypt supports stem cell function. Nature 543, 424–427 (2017).

    CAS  PubMed  Google Scholar 

  39. Stringari, C. et al. Metabolic trajectory of cellular differentiation in small intestine by Phasor Fluorescence Lifetime Microscopy of NADH. Sci. Rep. 2, 568 (2012).

    PubMed  PubMed Central  Google Scholar 

  40. Yang, M. & Vousden, K. H. Serine and one-carbon metabolism in cancer. Nat. Rev. Cancer 16, 650–662 (2016).

    CAS  PubMed  Google Scholar 

  41. Hollinshead, K. E. R. et al. Oncogenic IDH1 mutations promote enhanced proline synthesis through PYCR1 to support the maintenance of mitochondrial redox homeostasis. Cell Rep. 22, 3107–3114 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  42. Lee-Six, H. et al. The landscape of somatic mutation in normal colorectal epithelial cells. Nature 574, 532–537 (2019).

    CAS  PubMed  Google Scholar 

  43. De Laat, P. et al. Clinical features and heteroplasmy in blood, urine and saliva in 34 Dutch families carrying the m.3243A > G mutation. J. Inherit. Metab. Dis. 35, 1059–1069 (2012).

    PubMed  PubMed Central  Google Scholar 

  44. Frederiksen, A. L. et al. Tissue specific distribution of the 3243A→G mtDNA mutation. J. Med. Genet. 43, 671–677 (2006).

    CAS  PubMed  PubMed Central  Google Scholar 

  45. Grady, J. P. et al. mtDNA heteroplasmy level and copy number indicate disease burden in m.3243A>G mitochondrial disease. EMBO Mol. Med. https://doi.org/10.15252/emmm.201708262 (2018).

  46. Olsson, C. et al. The level of the mitochondrial mutation A3243G decreases upon ageing in epithelial cells from individuals with diabetes and deafness. Eur. J. Hum. Genet. 9, 917–921 (2001).

    CAS  PubMed  Google Scholar 

  47. Rahman, S., Poulton, J., Marchington, D. & Suomalainen, A. Decrease of 3243 A>G mtDNA mutation from blood in MELAS syndrome: a longitudinal study. Am. J. Hum. Genet. 68, 238–240 (2001).

    CAS  PubMed  Google Scholar 

  48. Su, T. et al. Inherited pathogenic mitochondrial DNA mutations and gastrointestinal stem cell populations. J. Pathol. 246, 427–432 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  49. Filograna, R. et al. Modulation of mtDNA copy number ameliorates the pathological consequences of a heteroplasmic mtDNA mutation in the mouse. Sci. Adv. 5, eaav9824 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  50. Kauppila, J. H. K. et al. A phenotype-driven approach to generate mouse models with pathogenic mtDNA mutations causing mitochondrial disease. Cell Rep. 16, 2980–2990 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  51. Betts, J. et al. Gastrointestinal tract involvement associated with the 3243A>G mitochondrial DNA mutation. Neurology 70, 1290–1292 (2008).

    CAS  PubMed  Google Scholar 

  52. Coxhead, J. et al. Somatic mtDNA variation is an important component of Parkinson’s disease. Neurobiol. Aging 38, 217.e1–217.e6 (2016).

    CAS  Google Scholar 

  53. 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 

  54. Pertea, M., Kim, D., Pertea, G. M., Leek, J. T. & Salzberg, S. L. Transcript-level expression analysis of RNA-seq experiments with HISAT, StringTie and Ballgown. Nat. Protocols 11, 1650–1667 (2016).

    CAS  PubMed  Google Scholar 

  55. Pertea, M. et al. StringTie enables improved reconstruction of a transcriptome from RNA-seq reads. Nat. Biotechnol. 33, 290–295 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  56. Frazee, A. C. et al. Ballgown bridges the gap between transcriptome assembly and expression analysis. Nat. Biotechnol. 33, 243–246 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  57. Kim, D., Langmead, B. & Salzberg, S. L. HISAT: a fast spliced aligner with low memory requirements. Nat. Methods 12, 357–360 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  58. Chen, E. Y. et al. Enrichr: interactive and collaborative HTML5 gene list enrichment analysis tool. BMC Bioinformatics 14, 128 (2013).

    PubMed  PubMed Central  Google Scholar 

  59. Kuleshov, M. V. et al. Enrichr: a comprehensive gene set enrichment analysis web server 2016 update. Nucleic Acids Res. 44, W90–W97 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  60. Fan, Y. Y. et al. A bioassay to measure energy metabolism in mouse colonic crypts, organoids, and sorted stem cells. Am. J. Physiol. Gastrointest. Liver Physiol. 309, G1–G9 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  61. Gonzalez, P. S. et al. Mannose impairs tumour growth and enhances chemotherapy. Nature 563, 719–723 (2018).

    CAS  PubMed  Google Scholar 

  62. Ho, J., Tumkaya, T., Aryal, S., Choi, H. & Claridge-Chang, A. Moving beyond P values: data analysis with estimation graphics. Nat. Methods 16, 565–566 (2019).

    CAS  PubMed  Google Scholar 

  63. Efron, B. & Tibshirani, R. J. An Introduction to the Bootstrap (CRC Press, 1994).

  64. R Development Core Team R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2018).

  65. Ross, J. M. et al. Germline mitochondrial DNA mutations aggravate ageing and can impair brain development. Nature 501, 412–415 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We thank T. Prolla (University of Wisconsin, Washington, United States) for donating the PolgA+/mut mice, and C. Alston for assistance with the analysis of mtDNA mutations. We thank staff in the Newcastle University Comparative Biology Centre for animal husbandry, and the Newcastle University Bioimaging Unit for support and assistance with fluorescent imaging. This work was supported by the Wellcome Centre for Mitochondrial Research (203105/Z/16/Z), Newcastle University Centre for Ageing and Vitality (supported by the Biotechnology and Biological Sciences Research Council, Engineering and Physical Sciences Research Council, Economic and Social Research Council and Medical Research Council (MR/L016354/1)), UK NIHR Biomedical Research Centre Age and Age Related Diseases award (to the Newcastle upon Tyne Hospitals NHS Foundation Trust) and NC3Rs (to C.A.R.; NC/K500513/1). O.J.S. is supported by Cancer Research UK grants (A25045, A17196, A12481 and A21139). O.J.S. and D.G. were supported by ERC starting grant 311301 awarded to O.J.S. F.O. is supported by the Medical Research Council (MR/R023026/1). J.L. is supported by Cancer Research UK (C18342/A23390).

Author information

Authors and Affiliations

Authors

Contributions

L.C.G., C.B., C.S. and C.A.R. performed the breeding and phenotypic analyses of mice. A.L.M.S., D.H., M.H., J.N.S. and A.B. performed the histology, IHC, immunofluorescence and analysis of mouse and human samples. L.C.G., O.M.R., R.J. and B.G. performed the sequencing and histological analysis of human samples. S.A.C.M., I.M., S.K. and J.C.M. collected and processed the human samples. J.C.W. performed the molecular biology and cell culture experiments. G.H. and A.P. performed the sequencing and bioinformatics analyses of the mouse and human adenomas. Flow cytometric immunophenotyping of the small intestine was carried out by S.A. and G.M. J.L. and F.O. performed the immune cell IHC. L.W. carried out the imaging and analysis of the immune cell IHC. F.R. performed the statistical analysis of the RNA-Seq data. A.P.B. performed the statistical analysis of the experimental data. D.G., J.C.W. and O.J.S. performed the metabolomics analyses and analyzed the data. L.C.G., R.W.T., R.H., D.M.T., N.D.P. and O.J.S. conceived of the ideas, designed the experiments and interpreted the data. All authors contributed to writing and revising the paper.

Corresponding author

Correspondence to Laura C. Greaves.

Ethics declarations

Competing interests

F.O. is a director of Fibrofind. J.L. and F.O. are shareholders in Fibrofind. The other authors declare no competing interests.

Additional information

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

Extended data

Extended Data Fig. 1 Generation of PolgAmut/mut;Lgr5-creER;Apcfl/fl and Lgr5-creER;Apcfl/fl mice and analysis of colonic adenomas.

a: Breeding scheme. MtDNA mutations can be transmitted down the maternal germline65 therefore it was essential that only Lgr5-creER;Apcfl/fl (red) mice from a wild-type PolgA mother used as controls. b: Kaplan-Meier survival curve showing survival time following tamoxifen administration in PolgAmut/mut mice. Survival to clinical endpoint or experimental endpoint of 60 days is shown, ‘n’ = number of mice. c: β-Catenin immunohistochemistry was performed on colon sections from n = 17 PolgAmut/mut;Apcfl/fl mice and n = 13 Apcfl/fl mice. Representative images are shown (scale bars 3 mm (first column) and 200 µm). d: Frequency of adenomas in the colon 23 days post-Apc deletion (unpaired, two tailed, t-test, p = 0.7444), n = 17 PolgAmut/mut;Apcfl/fl mice and n = 13 Apcfl/fl mice, data are mean ±s.d. e: Mean adenoma size in the colon in n = 17 PolgAmut/mut;Apcfl/fl mice and n = 13 Apcfl/fl mice 23 days post-Apc deletion. All adenomas on a section were quantified ranging from 5 to 280, mean per mouse ± s.e.m are shown. Two-sided linear mixed effect regression model with mouse ID as a random effect, P < 0.0001. f-g: Quantification of the frequency of thymidine analogue incorporation in all cells per colonic adenoma (f) and LGR5 + cells per colon adenoma per mouse (g). n = 5 mice per group with 18 adenomas analysed per mouse. Mean frequency per adenoma per mouse ± s.e.m is shown. Two-sided linear mixed effect regression model with mouse ID as a random effect, P < 0.001. h, i: Apoptotic cells were quantified using (h) cleaved caspase 3 (CC3) immunohistochemistry n = 7 PolgAmut/mut;Apcfl/fl mice and n = 9 Apcfl/fl mice and (i) TUNEL labelling (n = 9 mice per group) in mice 23 days post-Apc deletion. A minimum of 10 adenomas were analysed per mouse, mean percentage of apoptotic cells per adenoma per mouse ±s.e.m is shown. Two-sided linear mixed effect regression model with mouse ID as a random effect, CC3 P = 0.0092, TUNEL P = 0.002. * P < 0.05, **P < 0.01, ***P < 0.001.

Source data

Extended Data Fig. 2 Colonic adenomas from PolgAmut/mut;Apcfl/fl mice are deficient in mitochondrial complex I, but the majority retain expression of subunits of complexes III, IV and V.

a, b: Immunofluorescence was performed to quantify levels of OXPHOS proteins in n = 9 PolgAmut/mut;Apcfl/fl mice and n = 9 Apcfl/fl mice. Representative images are shown. Scale bars 50 µm. An adenoma deficient in complex I is highlighted by the white dashed line in a. The white dashed line highlights an adenoma deficient in complex IV, and red dashed line shows one with normal complex IV in bd: dot plots showing Z-scores calculated following quantification of mitochondrial OXPHOS protein levels in adenomas from n = 9 PolgAmut/mut;Apcfl/fl and n = 9 Apcfl/fl mice with 20 adenomas quantified per mouse. e: Categorical analysis of OXPHOS protein levels in PolgAmut/mut;Apcfl/fl (n = 9) and Apcfl/fl (n = 9) mice, error bars show mean ±s.d. f, g: dot plots showing Z-scores calculated following quantification of mitochondrial OXPHOS protein levels in normal crypts and adenomas in the small intestine (f) and the colon (g). f: For the adenomas: n = 9 PolgAmut/mut;Apcfl/fl and n = 10 Apcfl/fl mice were analysed with 20 adenomas quantified per mouse. For the normal crypts, n = 5 mice were analysed with a minimum of 13 crypts quantified per mouse. g: For the colonic adenomas: n = 9 mice per group were analysed with a minimum of 20 adenomas quantified per mouse. For the normal crypts, n = 6 Apcfl/fl mice and n = 7 PolgAmut/mut;Apcfl/fl mice were analysed with a minimum of 22 crypts quantified per mouse. h Dot plots showing raw densitometry values for mitochondrial protein levels in the colon (n numbers same as in g, error bars are s.d.). One-way ANOVA with Tukey’s post-test. P values for within genotype comparisons between normal crypts and adenomas were as follows: TOMM20: Apcfl/fl P < 0.0001, PolgAmut/mut;Apcfl/fl P < 0.0001, NDUFB8: Apcfl/fl P < 0.0001, PolgAmut/mut;Apcfl/fl P = 0.9761, UQCRFS1: Apcfl/fl P < 0.0001, PolgAmut/mut;Apcfl/fl P = 0.2901, MTCO1: Apcfl/fl P < 0.0001, PolgAmut/mut;Apcfl/fl P = 0.007, ATPB: Apcfl/fl P < 0.0001, PolgAmut/mut;Apcfl/fl P < 0.0001. For all panels: * P < 0.05, **P < 0.01, ***P < 0.001.

Source data

Extended Data Fig. 3 Analysis of mitochondrial DNA (mtDNA) mutations detected in individual small intestinal adenomas from PolgAmut/mut;Apcfl/fl and Apcfl/fl mice.

a: The frequency of heteroplasmic variants >3% detected in adenomas from PolgAmut/mut;Apcfl/fl (n = 3 mice per group and n = 10 adenomas per mouse) and Apcfl/fl mice (n = 3 mice per group, n = 5 adenomas per mouse), mean ±s.d. are shown. b–d: Analysis of mtDNA variants present at >30% heteroplasmy in individual adenomas from PolgAmut/mut;Apcfl/fl mice (n = 413 mtDNA mutations in total). For location (b), expected values were calculated based on the proportion of the mitochondrial genome taken up by each gene category and observed and expected values compared using Chi-squared analysis. No significant deviation from the expected frequencies was detected (P = 0.4744).

Source data

Extended Data Fig. 4 Mitochondrial OXPHOS dysfunction causes upregulation of de novo serine synthesis in vivo in the mouse colon.

Immunohistochemistry images showing in situ levels of SSP proteins in the non-transformed normal colonic mucosa (a) and adenomas (b) of PolgA+/+ and PolgAmut/mut mice. Immunohistochemistry was performed on n = 4 mice per group. Representative images are shown. Scale bars 50 µm.

Extended Data Fig. 5 Immunofluorescent images showing the levels of PHGDH, PSAT1 and MTHFD2 in PolgA+/+ and PolgAmut/mut mice from 1–12 months of age.

Immunofluorescence was performed on n = 3 mice per group at each time point. Representative images are shown. Scale bars 50 µm.

Extended Data Fig. 6 Quantification of major mass isotopomers following growth of adenoma organods in 13C6-glucose and adenoma organoid growth in to the presence of metformin.

a: Quantification of major mass isotopomers following growth in the presence of 13C6-glucose for 24 h. 13C labelling is shown as M + 6 (glucose) and M + 0 denotes no labelling. No significant differences were found between organoids from Apcfl/fl mice compared with PolgAmut/mut;Apcfl/fl mice by one-tailed unpaired t-test. n = 3 mice per group with 3 technical replicates performed per mouse. Error bars show s.e.m. b: A shared group estimation plot comparing the effect of metformin on the volume of individual adenoma organoids generated from Apcfl/fl mice (n = 3) on days 1 and 5 post seeding. Volume data are normalised to day 1. On day 1 the numbers of organoids measured were: 0 µM: n = 739, 100 µM: n = 796, 250 µM: n = 711, 500 µM: n = 652. On day 5 the numbers of organoids measured were: 0 µM: n = 1060, 100 µM: n = 1515, 250 µM: n = 1088, 500 µM: n = 1431. Bootstrap estimation of group mean differences (circle) and 95% confidence intervals (vertical bars) are plotted as a sampling distribution.

Source data

Supplementary information

Supplementary Information

Supplementary Fig. 1.

Reporting Summary

Supplementary Tables

Supplementary Tables 1–6.

Source data

Source Data Fig. 1

Statistical source data.

Source Data Fig. 2

Statistical source data.

Source Data Fig. 3

Statistical source data.

Source Data Fig. 4

Statistical source data.

Source Data Fig. 5

Statistical source data.

Source Data Fig. 6

Statistical source data.

Source Data Fig. 7

Statistical source data.

Source Data Extended Data Fig. 1

Statistical source data.

Source Data Extended Data Fig. 2

Statistical source data.

Source Data Extended Data Fig. 3

Statistical source data.

Source Data Extended Data Fig. 6

Statistical source data.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Smith, A.L.M., Whitehall, J.C., Bradshaw, C. et al. Age-associated mitochondrial DNA mutations cause metabolic remodeling that contributes to accelerated intestinal tumorigenesis. Nat Cancer 1, 976–989 (2020). https://doi.org/10.1038/s43018-020-00112-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s43018-020-00112-5

This article is cited by

Search

Quick links

Nature Briefing: Cancer

Sign up for the Nature Briefing: Cancer newsletter — what matters in cancer research, free to your inbox weekly.

Get what matters in cancer research, free to your inbox weekly. Sign up for Nature Briefing: Cancer