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The mutational landscapes of genetic and chemical models of Kras-driven lung cancer

Abstract

Next-generation sequencing of human tumours has refined our understanding of the mutational processes operative in cancer initiation and progression, yet major questions remain regarding the factors that induce driver mutations and the processes that shape mutation selection during tumorigenesis. Here we performed whole-exome sequencing on adenomas from three mouse models of non-small-cell lung cancer, which were induced either by exposure to carcinogens (methyl-nitrosourea (MNU) and urethane) or by genetic activation of Kras (KrasLA2). Although the MNU-induced tumours carried exactly the same initiating mutation in Kras as seen in the KrasLA2 model (G12D), MNU tumours had an average of 192 non-synonymous, somatic single-nucleotide variants, compared with only six in tumours from the KrasLA2 model. By contrast, the KrasLA2 tumours exhibited a significantly higher level of aneuploidy and copy number alterations compared with the carcinogen-induced tumours, suggesting that carcinogen-induced and genetically engineered models lead to tumour development through different routes. The wild-type allele of Kras has been shown to act as a tumour suppressor in mouse models of non-small-cell lung cancer. We demonstrate that urethane-induced tumours from wild-type mice carry mostly (94%) Kras Q61R mutations, whereas those from Kras heterozygous animals carry mostly (92%) Kras Q61L mutations, indicating a major role for germline Kras status in mutation selection during initiation. The exome-wide mutation spectra in carcinogen-induced tumours overwhelmingly display signatures of the initiating carcinogen, while adenocarcinomas acquire additional C > T mutations at CpG sites. These data provide a basis for understanding results from human tumour genome sequencing, which has identified two broad categories of tumours based on the relative frequency of single-nucleotide variations and copy number alterations1, and underline the importance of carcinogen models for understanding the complex mutation spectra seen in human cancers.

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Figure 1: Differences in mutation burden and spectra between carcinogen and genetic models.
Figure 2: Distinct copy number profiles of genetically and chemically induced tumours.
Figure 3: Consequential SNVs in high-likelihood driver genes only occur in carcinogen-induced tumours.
Figure 4: Adenocarcinomas show enrichment for a signature of genomic instability.

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European Nucleotide Archive

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The raw .bam files have been deposited in the European Nucleotide Archive under accession number ERP001454.

References

  1. Ciriello, G. et al. Emerging landscape of oncogenic signatures across human cancers. Nature Genet. 45, 1127–1133 (2013)

    Article  CAS  Google Scholar 

  2. Stratton, M. R., Campbell, P. J. & Futreal, P. A. The cancer genome. Nature 458, 719–724 (2009)

    Article  ADS  CAS  Google Scholar 

  3. Alexandrov, L. B. et al. Signatures of mutational processes in human cancer. Nature 500, 415–421 (2013)

    Article  CAS  Google Scholar 

  4. Lawrence, M. S. et al. Mutational heterogeneity in cancer and the search for new cancer-associated genes. Nature 499, 214–218 (2013)

    Article  ADS  CAS  Google Scholar 

  5. Johnson, L. et al. Somatic activation of the K-ras oncogene causes early onset lung cancer in mice. Nature 410, 1111–1116 (2001)

    Article  ADS  CAS  Google Scholar 

  6. You, M., Candrian, U., Maronpot, R. R., Stoner, G. D. & Anderson, M. W. Activation of the Ki-ras protooncogene in spontaneously occurring and chemically induced lung tumours of the strain A mouse. Proc. Natl Acad. Sci. USA 86, 3070–3074 (1989)

    Article  ADS  CAS  Google Scholar 

  7. Prior, I. A., Lewis, P. D. & Mattos, C. A comprehensive survey of Ras mutations in cancer. Cancer Res. 72, 2457–2467 (2012)

    Article  CAS  Google Scholar 

  8. Jackson, E. L. et al. Analysis of lung tumour initiation and progression using conditional expression of oncogenic K-ras. Genes Dev. 15, 3243–3248 (2001)

    Article  CAS  Google Scholar 

  9. Zhang, Z. et al. Wildtype Kras2 can inhibit lung carcinogenesis in mice. Nature Genet. 29, 25–33 (2001)

    Article  CAS  Google Scholar 

  10. To, M. D. et al. Kras regulatory elements and exon 4A determine mutation specificity in lung cancer. Nature Genet. 40, 1240–1244 (2008)

    Article  CAS  Google Scholar 

  11. Govindan, R. et al. Genomic landscape of non-small cell lung cancer in smokers and never-smokers. Cell 150, 1121–1134 (2012)

    Article  CAS  Google Scholar 

  12. Forkert, P. G. Mechanisms of lung tumourigenesis by ethyl carbamate and vinyl carbamate. Drug Metab. Rev. 42, 355–378 (2010)

    Article  CAS  Google Scholar 

  13. Kurowska, M., Labocha-Pawlowska, A., Gnizda, D., Maluszynski, M. & Szarejko, I. Molecular analysis of point mutations in a barley genome exposed to MNU and gamma rays. Mutat. Res. 738–739, 52–70 (2012)

    Article  Google Scholar 

  14. Pfeifer, G. P. Mutagenesis at methylated CpG sequences. Curr. Top. Microbiol. Immunol. 301, 259–281 (2006)

    CAS  PubMed  Google Scholar 

  15. Welch, J. S. et al. The origin and evolution of mutations in acute myeloid leukemia. Cell 150, 264–278 (2012)

    Article  CAS  Google Scholar 

  16. Drugan, J. K. et al. Ras interaction with two distinct binding domains in Raf-1 may be required for Ras transformation. J. Biol. Chem. 271, 233–237 (1996)

    Article  CAS  Google Scholar 

  17. Spoerner, M., Herrmann, C., Vetter, I. R., Kalbitzer, H. R. & Wittinghofer, A. Dynamic properties of the Ras switch I region and its importance for binding to effectors. Proc. Natl Acad. Sci. USA 98, 4944–4949 (2001)

    Article  ADS  CAS  Google Scholar 

  18. Fawdar, S. et al. Targeted genetic dependency screen facilitates identification of actionable mutations in FGFR4, MAP3K9, and PAK5 in lung cancer. Proc. Natl Acad. Sci. USA 110, 12426–12431 (2013)

    Article  ADS  CAS  Google Scholar 

  19. Vogelstein, B. et al. Cancer genome landscapes. Science 339, 1546–1558 (2013)

    Article  ADS  CAS  Google Scholar 

  20. Di Benedetto, M. et al. Mutation analysis of the 8p22 candidate tumour suppressor gene ATIP/MTUS1 in hepatocellular carcinoma. Mol. Cell. Endocrinol. 252, 207–215 (2006)

    Article  CAS  Google Scholar 

  21. Frank, B. et al. Copy number variant in the candidate tumour suppressor gene MTUS1 and familial breast cancer risk. Carcinogenesis 28, 1442–1445 (2007)

    Article  CAS  Google Scholar 

  22. Zuern, C. et al. Down-regulation of MTUS1 in human colon tumours. Oncol. Rep. 23, 183–189 (2010)

    CAS  PubMed  Google Scholar 

  23. Xiao, J. et al. Reduced expression of MTUS1 mRNA is correlated with poor prognosis in bladder cancer. Oncol Lett 4, 113–118 (2012)

    Article  CAS  Google Scholar 

  24. Shedden, K. et al. Gene expression-based survival prediction in lung adenocarcinoma: a multi-site, blinded validation study. Nature Med. 14, 822–827 (2008)

    Article  CAS  Google Scholar 

  25. To, M. D. et al. Progressive genomic instability in the FVB/KrasLA2 mouse model of lung cancer. Mol. Cancer Res. 9, 1339–1345 (2011)

    Article  CAS  Google Scholar 

  26. Ahmed, N. N., Grimes, H. L., Bellacosa, A., Chan, T. O. & Tsichlis, P. N. Transduction of interleukin-2 antiapoptotic and proliferative signals via Akt protein kinase. Proc. Natl Acad. Sci. USA 94, 3627–3632 (1997)

    Article  ADS  CAS  Google Scholar 

  27. McFadden, D. G. et al. Genetic and clonal dissection of murine small cell lung carcinoma progression by genome sequencing. Cell 156, 1298–1311 (2014)

    Article  CAS  Google Scholar 

  28. Nuzum, E. O., Malkinson, A. M. & Beer, D. G. Specific Ki-ras codon 61 mutations may determine the development of urethan-induced mouse lung adenomas or adenocarcinomas. Mol. Carcinog. 3, 287–295 (1990)

    Article  CAS  Google Scholar 

  29. Berndt, A. et al. Identification of Fat4 and Tsc22d1 as novel candidate genes for spontaneous pulmonary adenomas. Cancer Res. 71, 5779–5791 (2011)

    Article  CAS  Google Scholar 

  30. To, M. D., Rosario, R. D., Westcott, P. M., Banta, K. L. & Balmain, A. Interactions between wild-type and mutant Ras genes in lung and skin carcinogenesis. Oncogene 32, 4028–4033 (2013)

    Article  CAS  Google Scholar 

  31. Johnson, L. et al. K-ras is an essential gene in the mouse with partial functional overlap with N-ras. Genes Dev. 11, 2468–2481 (1997)

    Article  CAS  Google Scholar 

  32. Varela, I. et al. Exome sequencing identifies frequent mutation of the SWI/SNF complex gene PBRM1 in renal carcinoma. Nature 469, 539–542 (2011)

    Article  ADS  CAS  Google Scholar 

  33. Li, H. & Durbin, R. Fast and accurate short read alignment with Burrows–Wheeler transform. Bioinformatics 25, 1754–1760 (2009)

    Article  CAS  Google Scholar 

  34. DePristo, M. A. et al. A framework for variation discovery and genotyping using next-generation DNA sequencing data. Nature Genet. 43, 491–498 (2011)

    Article  CAS  Google Scholar 

  35. Cibulskis, K. et al. Sensitive detection of somatic point mutations in impure and heterogeneous cancer samples. Nature Biotechnol. 31, 213–219 (2013)

    Article  CAS  Google Scholar 

  36. Li, H. et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics 25, 2078–2079 (2009)

    Article  Google Scholar 

  37. Wang, K., Li, M. & Hakonarson, H. ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data. Nucleic Acids Res. 38, e164 (2010)

    Article  Google Scholar 

  38. Forbes, S. A. et al. COSMIC: mining complete cancer genomes in the Catalogue of Somatic Mutations in Cancer. Nucleic Acids Res. 39, D945–D950 (2011)

    Article  CAS  Google Scholar 

  39. Sievers, F. et al. Fast, scalable generation of high-quality protein multiple sequence alignments using Clustal Omega. Mol. Syst. Biol. 7, 539 (2011)

    Article  Google Scholar 

  40. Nik-Zainal, S. et al. Mutational processes molding the genomes of 21 breast cancers. Cell 149, 979–993 (2012)

    Article  CAS  Google Scholar 

  41. Boeva, V. et al. Control-free calling of copy number alterations in deep-sequencing data using GC-content normalization. Bioinformatics 27, 268–269 (2011)

    Article  CAS  Google Scholar 

  42. Raponi, M. et al. Gene expression signatures for predicting prognosis of squamous cell and adenocarcinomas of the lung. Cancer Res. 66, 7466–7472 (2006)

    Article  CAS  Google Scholar 

Download references

Acknowledgements

This work was supported by National Cancer Institute (NCI) grants R01 CA111834, U01 CA84244, U01 CA141455 and UO1 CA176287 (to A.B.), and partly funded by the Bonnie Addario Foundation. P.M.K.W. was supported by the National Institutes of Health (NIH) training grant T32 GM007175 and a National Science Foundation GRFP award, and is currently supported by an NCI F31 NRSA award. K.D.H. was supported by the NIH training grant T32 GM007175, and is currently supported by an NCI F31 NRSA award. D.J.A. is supported by Cancer Research UK and the Wellcome Trust. We are appreciative of help and comments from our colleagues in refining this study and manuscript. We would also like to thank S. Busch for assistance with animal studies, and S. Green, T. Yuan and M. McMahon for providing the K493.1 cell line.

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Authors and Affiliations

Authors

Contributions

P.M.K.W., K.D.H., M.D.T., D.J.A. and A.B. contributed to the overall study design. P.M.K.W. carried out most of the experiments, with help from M.D.T. R.D. was responsible for all of the animal studies. Sequencing and Sequenom were performed at the Sanger Institute under the supervision of D.J.A., and data processing was carried out by K.D.H., M.R., A.G.R. and T.M.K. SNV and CNA calling were carried out by K.D.H. Data analysis was carried out primarily by P.M.K.W. and K.D.H., with help from E.F. and D.A.Q. K.-Y.J. made histological assessments of all tumours. Adenomas and adenocarcinomas from the A/J mice were provided by C.J.K. and K.E.G. The manuscript was written primarily by P.M.K.W. and A.B., with contributions from the other authors.

Corresponding author

Correspondence to Allan Balmain.

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Competing interests

The authors declare no competing financial interests.

Extended data figures and tables

Extended Data Figure 1 Distinct and consistent mutation spectra across tumours from carcinogen and genetic models.

ac, Stacked heatmaps displaying the mutation spectra of all MNU-induced (a), urethane-induced (b), and KrasLA2 tumours (c), shown as normalized frequencies of all 96 possible substitutions. Substitutions are shown below each heatmap, with 5′- and 3′-flanking base context displayed on the top and right, respectively. Tumour identifier is shown to the left of each heatmap.

Extended Data Figure 2 Highly specific mutation signatures.

a, Breakdown of G > A transitions in MNU-induced tumours. 5′-flanking purine versus pyrimidine G > A substitutions, and 3′-flanking thymidine versus all other G > A substitutions, are highly significant (P < 0.0003, Wilcoxon rank-sum test). b, c, Breakdowns of A > G transitions (b) and A > T transversions (c) in urethane-induced tumours. d, e, All 96 substitutions in urethane-induced (d) and KrasLA2 tumours (e). e, The CGN > A (NCG > T) signature mutations of genomic instability are denoted. Mutation counts per tumour were normalized to total length of sequenced trinucleotide contexts in each tumour and averaged. Error bars represent s.e.m.

Extended Data Figure 3 Kras G12D mutation induces tumours with different histologies compared with codon 61 mutants.

a, Representative papillary, solid, and mixed tumour histologies (×200 magnification). b, Breakdown of different histologies in each treatment group. Histologies from KrasLA2 and MNU groups were significantly different compared with those from urethane, but there was no significant difference between KrasLA2 and MNU (Fisher exact test, Holm’s correction for multiple comparisons).

Extended Data Figure 4 Germline Kras genotype influences mutation specificity in urethane-induced tumours.

a, Kras mutant alleles for urethane tumours are plotted as coloured squares for all three oncogenic alleles detected in these tumours. Kras genotype is indicated as either white (wild type (WT)) or black (heterozygous) squares. b, Highly significant switch in Kras codon 61 mutations between tumours from wild-type mice and Kras+/− mice (Fisher exact test). c, No significant difference was seen between the exome-wide rates of the substitutions underlying Kras Q61R (CAA > G) and Q61L (CAA > T) mutations between tumours from wild-type and Kras+/− mice (Wilcoxon rank-sum test). NS, not significant.

Extended Data Figure 5 MTUS1 is a tumour suppressor in mouse and human lung cancer.

a, Polymerase chain reaction with quantitative reverse transcription (qRT–PCR) quantification of short interfering RNA (siRNA) knockdown of Mtus1 in a Kras G12D mouse lung cancer cell line (K493.1) (Wilcoxon rank-sum test). CTL, control. b, MTT assay shows increased growth after Mtus1 knockdown (Wilcoxon rank-sum test). Four independent trials were performed and growth was significantly increased by day 3 after knockdown in each experiment. One representative trial is shown. c, MTUS1 expression is significantly associated with overall survival in human lung adenocarcinoma (P = 0.00097, χ2 = 10.9). Analysis was performed using the clinical covariates gender, age, pack years smoked, and stage.

Extended Data Figure 6 Proportion of tumours with CNAs in each treatment group.

Amplifications and deletions were defined as regions with a log2 ratio greater than 0.5 or less than −0.5, respectively. Chromosomes are arranged on the x axis in a head-to-tail formation.

Extended Data Figure 7 Histological confirmation of lung adenocarcinomas.

a, b, Representative histologies (×400 magnification) of A/J (a) and FVB/N (b) adenocarcinomas. Zoom insets show tumour cell crowding and scattered mitotic figures (black arrowheads), nuclear atypia including enlargement and moderate pleomorphism, nuclear membrane irregularity, and prominent nucleoli. Scale bars, 20 μm.

Extended Data Figure 8 Comparison of urethane signature mutations in adenomas and adenocarcinomas.

Urethane A > G transitions (left) and A > T transversions (right) are shown in A/J adenocarcinomas, FVB/N adenocarcinomas and FVB/N adenomas. Mutation counts per tumour were normalized to total length of sequenced trinucleotide contexts in each tumour and averaged. Error bars represent s.e.m.

Extended Data Table 1 Treatment groups and lung tumours for WES
Extended Data Table 2 Mouse lung adenoma SNVs in established cancer driver genes and Mtus1

Supplementary information

Supplementary Information

This file contains Supplementary Table 1 and 3-8. (PDF 321 kb)

Supplementary Data

This file contains Supplementary Table 2. (XLSX 17 kb)

Supplementary Data

VCF file of all SNVs called in the 82 lung adenomas. (TXT 5724 kb)

Supplementary Data

VCF file of all SNVs called in the 22 lung adenocarcinomas. (TXT 658 kb)

Supplementary Data

Sample to ID key file. (TXT 8 kb)

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Westcott, P., Halliwill, K., To, M. et al. The mutational landscapes of genetic and chemical models of Kras-driven lung cancer. Nature 517, 489–492 (2015). https://doi.org/10.1038/nature13898

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