Display options
Share it on

Nature. 2021 Oct;598(7881):473-478. doi: 10.1038/s41586-021-03974-6. Epub 2021 Oct 13.

Convergent somatic mutations in metabolism genes in chronic liver disease.

Nature

Stanley W K Ng, Foad J Rouhani, Simon F Brunner, Natalia Brzozowska, Sarah J Aitken, Ming Yang, Federico Abascal, Luiza Moore, Efterpi Nikitopoulou, Lia Chappell, Daniel Leongamornlert, Aleksandra Ivovic, Philip Robinson, Timothy Butler, Mathijs A Sanders, Nicholas Williams, Tim H H Coorens, Jon Teague, Keiran Raine, Adam P Butler, Yvette Hooks, Beverley Wilson, Natalie Birtchnell, Huw Naylor, Susan E Davies, Michael R Stratton, Iñigo Martincorena, Raheleh Rahbari, Christian Frezza, Matthew Hoare, Peter J Campbell

Affiliations

  1. Cancer Genome Project, Wellcome Sanger Institute, Hinxton, UK.
  2. Department of Surgery, Addenbrooke's Hospital, Cambridge, UK.
  3. CRUK Cambridge Institute, Cambridge, UK.
  4. Department of Pathology, Addenbrooke's Hospital, Cambridge, UK.
  5. MRC Toxicology Unit, University of Cambridge, Cambridge, UK.
  6. MRC Cancer Unit, University of Cambridge, Cambridge, UK.
  7. Department of Hematology, Erasmus University Medical Center, Rotterdam, The Netherlands.
  8. CRUK Cambridge Institute, Cambridge, UK. [email protected].
  9. Department of Medicine, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK. [email protected].
  10. Cancer Genome Project, Wellcome Sanger Institute, Hinxton, UK. [email protected].
  11. Stem Cell Institute, University of Cambridge, Cambridge, UK. [email protected].

PMID: 34646017 DOI: 10.1038/s41586-021-03974-6

Abstract

The progression of chronic liver disease to hepatocellular carcinoma is caused by the acquisition of somatic mutations that affect 20-30 cancer genes

© 2021. The Author(s), under exclusive licence to Springer Nature Limited.

References

  1. The Cancer Genome Atlas Research Network. Comprehensive and integrative genomic characterization of hepatocellular carcinoma. Cell 169, 1327–1341 (2017). - PubMed
  2. Schulze, K. et al. Exome sequencing of hepatocellular carcinomas identifies new mutational signatures and potential therapeutic targets. Nat. Genet. 47, 505–511 (2015). - PubMed
  3. Totoki, Y. et al. Trans-ancestry mutational landscape of hepatocellular carcinoma genomes. Nat. Genet. 46, 1267–1273 (2014). - PubMed
  4. Fujimoto, A. et al. Whole-genome sequencing of liver cancers identifies etiological influences on mutation patterns and recurrent mutations in chromatin regulators. Nat. Genet. 44, 760–764 (2012). - PubMed
  5. Letouzé, E. et al. Mutational signatures reveal the dynamic interplay of risk factors and cellular processes during liver tumorigenesis. Nat. Commun. 8, 1315 (2017). - PubMed
  6. Guichard, C. et al. Integrated analysis of somatic mutations and focal copy-number changes identifies key genes and pathways in hepatocellular carcinoma. Nat. Genet. 44, 694–698 (2012). - PubMed
  7. Fujimoto, A. et al. Whole-genome mutational landscape and characterization of noncoding and structural mutations in liver cancer. Nat. Genet. 48, 500–509 (2016). - PubMed
  8. Pinyol, R. et al. Molecular characterization of hepatocellular carcinoma in patients with non-alcoholic steatohepatitis. J. Hepatol. 75, 865–878 (2021). - PubMed
  9. Nault, J. C. et al. Telomerase reverse transcriptase promoter mutation is an early somatic genetic alteration in the transformation of premalignant nodules in hepatocellular carcinoma on cirrhosis. Hepatology 60, 1983–1992 (2014). - PubMed
  10. Torrecilla, S. et al. Trunk mutational events present minimal intra- and inter-tumoral heterogeneity in hepatocellular carcinoma. J. Hepatol. 67, 1222–1231 (2017). - PubMed
  11. Zhu, M. et al. Somatic mutations increase hepatic clonal fitness and regeneration in chronic liver disease. Cell 177, 608–621 (2019). - PubMed
  12. Kim, S. K. et al. Comprehensive analysis of genetic aberrations linked to tumorigenesis in regenerative nodules of liver cirrhosis. J. Gastroenterol. 54, 628–640 (2019). - PubMed
  13. Brunner, S. F. et al. Somatic mutations and clonal dynamics in healthy and cirrhotic human liver. Nature 574, 538–542 (2019). - PubMed
  14. Blokzijl, F. et al. Tissue-specific mutation accumulation in human adult stem cells during life. Nature 538, 260–264 (2016). - PubMed
  15. Yizhak, K. et al. RNA sequence analysis reveals macroscopic somatic clonal expansion across normal tissues. Science 364, eaaw0726 (2019). - PubMed
  16. Brazhnik, K. et al. Single-cell analysis reveals different age-related somatic mutation profiles between stem and differentiated cells in human liver. Sci. Adv. 6, eaax2659 (2020). - PubMed
  17. Barneda, D. et al. The brown adipocyte protein CIDEA promotes lipid droplet fusion via a phosphatidic acid-binding amphipathic helix. Elife 4, e07485 (2015). - PubMed
  18. Sun, Z. et al. Perilipin1 promotes unilocular lipid droplet formation through the activation of Fsp27 in adipocytes. Nat. Commun. 4, 1594 (2013). - PubMed
  19. Li, J. Z. et al. Cideb regulates diet-induced obesity, liver steatosis, and insulin sensitivity by controlling lipogenesis and fatty acid oxidation. Diabetes 56, 2523–2532 (2007). - PubMed
  20. Hammond, L. E. et al. Mitochondrial glycerol-3-phosphate acyltransferase-1 is essential in liver for the metabolism of excess acyl-CoAs. J. Biol. Chem. 280, 25629–25636 (2005). - PubMed
  21. Wendel, A. A., Cooper, D. E., Ilkayeva, O. R., Muoio, D. M. & Coleman, R. A. Glycerol-3-phosphate acyltransferase (GPAT)−1, but not GPAT4, incorporates newly synthesized fatty acids into triacylglycerol and diminishes fatty acid oxidation. J. Biol. Chem. 288, 27299–27306 (2013). - PubMed
  22. Jeon, S. & Carr, R. Alcohol effects on hepatic lipid metabolism. J. Lipid Res. 61, 470–479 (2020). - PubMed
  23. Friedman, S. L., Neuschwander-Tetri, B. A., Rinella, M. & Sanyal, A. J. Mechanisms of NAFLD development and therapeutic strategies. Nat. Med. 24, 908–922 (2018). - PubMed
  24. Clugston, R. D. et al. Altered hepatic lipid metabolism in C57BL/6 mice fed alcohol: a targeted lipidomic and gene expression study. J. Lipid Res. 52, 2021–2031 (2011). - PubMed
  25. Puri, P. et al. A lipidomic analysis of nonalcoholic fatty liver disease. Hepatology 46, 1081–1090 (2007). - PubMed
  26. Meister, G. et al. Identification of novel argonaute-associated proteins. Curr. Biol. 15, 2149–2155 (2005). - PubMed
  27. Rheinbay, E. et al. Analyses of non-coding somatic drivers in 2,658 cancer whole genomes. Nature 578, 102–111 (2020). - PubMed
  28. Yaffe, M. B. et al. The structural basis for 14-3-3:phosphopeptide binding specificity. Cell 91, 961–971 (1997). - PubMed
  29. Saline, M. et al. AMPK and AKT protein kinases hierarchically phosphorylate the N-terminus of the FOXO1 transcription factor, modulating interactions with 14-3-3 proteins. J. Biol. Chem. 294, 13106–13116 (2019). - PubMed
  30. Kleiner, D. E. et al. Design and validation of a histological scoring system for nonalcoholic fatty liver disease. Hepatology 41, 1313–1321 (2005). - PubMed
  31. Ishak, K. et al. Histological grading and staging of chronic hepatitis. J. Hepatol. 22, 696–699 (1995). - PubMed
  32. Ellis, P. et al. Reliable detection of somatic mutations in solid tissues by laser-capture microdissection and low-input DNA sequencing. Nat. Protoc. 16, 841–871 (2021). - PubMed
  33. Jones, D. et al. cgpCaVEManWrapper: simple execution of CaVEMan in order to detect somatic single nucleotide variants in NGS data. Curr. Protoc. Bioinformatics 56, 15.10.1–15.10.18 (2016). - PubMed
  34. Yoshida, K. et al. Tobacco smoking and somatic mutations in human bronchial epithelium. Nature 578, 266–272 (2020). - PubMed
  35. Papastamoulis, P. label.switching: an R package for dealing with the label switching problem in MCMC outputs. J. Stat. Softw. 69, Code Snippet 1 (2015). - PubMed
  36. Nik-Zainal, S. et al. The life history of 21 breast cancers. Cell 149, 994–1007 (2012). - PubMed
  37. Martincorena, I. et al. Universal patterns of selection in cancer and somatic tissues. Cell 171, 1029–1041 (2017). - PubMed
  38. Raine, K. M. et al. cgpPindel: identifying somatically acquired insertion and deletion events from paired end sequencing. Curr. Protoc. Bioinformatics 52, 15.7.1–15.7.12 (2015). - PubMed
  39. Campbell, P. J. et al. Identification of somatically acquired rearrangements in cancer using genome-wide massively parallel paired-end sequencing. Nat. Genet. 40, 722–729 (2008). - PubMed
  40. Stephens, P. J. et al. Massive genomic rearrangement acquired in a single catastrophic event during cancer development. Cell 144, 27–40 (2011). - PubMed
  41. Sohlenius-Sternbeck, A. K. Determination of the hepatocellularity number for human, dog, rabbit, rat and mouse livers from protein concentration measurements. Toxicol. Vitr. 20, 1582–1586 (2006). - PubMed
  42. Lipscomb, J. C., Fisher, J. W., Confer, P. D. & Byczkowski, J. Z. In vitro to in vivo extrapolation for trichloroethylene metabolism in humans. Toxicol. Appl. Pharmacol. 152, 376–387 (1998). - PubMed
  43. Bergstrom, E. N. et al. SigProfilerMatrixGenerator: a tool for visualizing and exploring patterns of small mutational events. BMC Genomics 20, 685 (2019). - PubMed
  44. Alexandrov, L. B. et al. The repertoire of mutational signatures in human cancer. Nature 578, 94–101 (2020). - PubMed
  45. Drost, H.-G. Philentropy: information theory and distance quantification with R. J. Open Source Softw. 3, 765 (2018). - PubMed
  46. Qiao, W. et al. PERT: a method for expression deconvolution of human blood samples from varied microenvironmental and developmental conditions. PLoS Comput. Biol. 8, (2012). - PubMed
  47. Farmery, J. H. R. et al. Telomerecat: a ploidy-agnostic method for estimating telomere length from whole genome sequencing data. Sci. Rep. 8, 1300 (2018). - PubMed
  48. Hadfield, J. D. MCMC methods for multi-response generalized linear mixed models: the MCMCglmm R package. J. Stat. Softw. 33, v033i02 (2010). - PubMed
  49. Hoare, M. et al. NOTCH1 mediates a switch between two distinct secretomes during senescence. Nat. Cell Biol. 18, 979–992 (2016). - PubMed
  50. Liao, Y., Smyth, G. K. & Shi, W. FeatureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics 30, 923–930 (2014). - PubMed
  51. Robinson, M. D., McCarthy, D. J. & Smyth, G. K. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26, 139–140 (2009). - PubMed

Publication Types

Grant support