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:

Distinct patterns of somatic genome alterations in lung adenocarcinomas and squamous cell carcinomas

Abstract

To compare lung adenocarcinoma (ADC) and lung squamous cell carcinoma (SqCC) and to identify new drivers of lung carcinogenesis, we examined the exome sequences and copy number profiles of 660 lung ADC and 484 lung SqCC tumor–normal pairs. Recurrent alterations in lung SqCCs were more similar to those of other squamous carcinomas than to alterations in lung ADCs. New significantly mutated genes included PPP3CA, DOT1L, and FTSJD1 in lung ADC, RASA1 in lung SqCC, and KLF5, EP300, and CREBBP in both tumor types. New amplification peaks encompassed MIR21 in lung ADC, MIR205 in lung SqCC, and MAPK1 in both. Lung ADCs lacking receptor tyrosine kinase–Ras–Raf pathway alterations had mutations in SOS1, VAV1, RASA1, and ARHGAP35. Regarding neoantigens, 47% of the lung ADC and 53% of the lung SqCC tumors had at least five predicted neoepitopes. Although targeted therapies for lung ADC and SqCC are largely distinct, immunotherapies may aid in treatment for both subtypes.

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

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

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

Figure 1: Distinct somatic alterations in lung ADC and lung SqCC.
Figure 2: Comparison of mutational signatures in lung cancer.
Figure 3: Significantly mutated genes in lung cancer as compared to other cancer types.
Figure 4: New significantly mutated genes in lung cancer.
Figure 5: Significant amplifications in lung cancer.
Figure 6: Fusions involving MET and NTRK2.
Figure 7: New alterations in the RTK–Rho/Ras–Raf pathway in lung ADC.
Figure 8: Neoepitope load in lung cancer.

Similar content being viewed by others

References

  1. Stewart, B.W. & Wild, C.P. World Cancer Report 2014 (International Agency for Research on Cancer, 2014).

  2. Siegel, R.L., Miller, K.D. & Jemal, A. Cancer statistics, 2015. CA Cancer J. Clin. 65, 5–29 (2015).

    Article  PubMed  Google Scholar 

  3. Samet, J.M. et al. Lung cancer in never smokers: clinical epidemiology and environmental risk factors. Clin. Cancer Res. 15, 5626–5645 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  4. Cardarella, S. & Johnson, B.E. The impact of genomic changes on treatment of lung cancer. Am. J. Respir. Crit. Care Med. 188, 770–775 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Vaishnavi, A. et al. Oncogenic and drug-sensitive NTRK1 rearrangements in lung cancer. Nat. Med. 19, 1469–1472 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Cancer Genome Atlas Research Network. Comprehensive molecular profiling of lung adenocarcinoma. Nature 511, 543–550 (2014).

  7. Cancer Genome Atlas Research Network. Comprehensive genomic characterization of squamous cell lung cancers. Nature 489, 519–525 (2012).

  8. Imielinski, M. et al. Mapping the hallmarks of lung adenocarcinoma with massively parallel sequencing. Cell 150, 1107–1120 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Roberts, S.A. et al. An APOBEC cytidine deaminase mutagenesis pattern is widespread in human cancers. Nat. Genet. 45, 970–976 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Lawrence, M.S. et al. Discovery and saturation analysis of cancer genes across 21 tumour types. Nature 505, 495–501 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Hoadley, K.A. et al. Multiplatform analysis of 12 cancer types reveals molecular classification within and across tissues of origin. Cell 158, 929–944 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Cancer Genome Atlas Network. Comprehensive genomic characterization of head and neck squamous cell carcinomas. Nature 517, 576–582 (2015).

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Alexandrov, L.B., Nik-Zainal, S., Wedge, D.C., Campbell, P.J. & Stratton, M.R. Deciphering signatures of mutational processes operative in human cancer. Cell Reports 3, 246–259 (2013).

    CAS  PubMed  Google Scholar 

  17. Forbes, S.A. et al. COSMIC: exploring the world's knowledge of somatic mutations in human cancer. Nucleic Acids Res. 43, D805–D811 (2015).

    Article  CAS  PubMed  Google Scholar 

  18. Alexandrov, L.B. et al. Clock-like mutational processes in human somatic cells. Nat. Genet. 47, 1402–1407 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Quesada, V. et al. Exome sequencing identifies recurrent mutations of the splicing factor SF3B1 gene in chronic lymphocytic leukemia. Nat. Genet. 44, 47–52 (2012).

    Article  CAS  Google Scholar 

  20. Bernards, A. GAPs galore! A survey of putative Ras superfamily GTPase activating proteins in man and Drosophila. Biochim. Biophys. Acta 1603, 47–82 (2003).

    CAS  PubMed  Google Scholar 

  21. Hast, B.E. et al. Cancer-derived mutations in KEAP1 impair NRF2 degradation but not ubiquitination. Cancer Res. 74, 808–817 (2014).

    Article  CAS  PubMed  Google Scholar 

  22. Wan, H. et al. Kruppel-like factor 5 is required for perinatal lung morphogenesis and function. Development 135, 2563–2572 (2008).

    Article  CAS  PubMed  Google Scholar 

  23. Zhao, D., Zheng, H.Q., Zhou, Z. & Chen, C. The Fbw7 tumor suppressor targets KLF5 for ubiquitin-mediated degradation and suppresses breast cell proliferation. Cancer Res. 70, 4728–4738 (2010).

    Article  CAS  PubMed  Google Scholar 

  24. Zhang, X. et al. Identification of focally amplified lineage-specific super-enhancers in human epithelial cancers. Nat. Genet. 48, 176–182 (2016).

    Article  CAS  PubMed  Google Scholar 

  25. Cancer Genome Atlas Research Network. Comprehensive molecular characterization of urothelial bladder carcinoma. Nature 507, 315–322 (2014).

  26. Zack, T.I. et al. Pan-cancer patterns of somatic copy number alteration. Nat. Genet. 45, 1134–1140 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Akagi, I. et al. Combination of protein coding and noncoding gene expression as a robust prognostic classifier in stage I lung adenocarcinoma. Cancer Res. 73, 3821–3832 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Saito, M. et al. The association of microRNA expression with prognosis and progression in early-stage, non–small cell lung adenocarcinoma: a retrospective analysis of three cohorts. Clin. Cancer Res. 17, 1875–1882 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Lebanony, D. et al. Diagnostic assay based on hsa-miR-205 expression distinguishes squamous from nonsquamous non-small-cell lung carcinoma. J. Clin. Oncol. 27, 2030–2037 (2009).

    Article  CAS  PubMed  Google Scholar 

  30. Oxnard, G.R., Binder, A. & Jänne, P.A. New targetable oncogenes in non-small-cell lung cancer. J. Clin. Oncol. 31, 1097–1104 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Stransky, N., Cerami, E., Schalm, S., Kim, J.L. & Lengauer, C. The landscape of kinase fusions in cancer. Nat. Commun. 5, 4846 (2014).

    Article  CAS  PubMed  Google Scholar 

  32. Gallant, J.N. et al. EGFR kinase domain duplication (EGFR-KDD) is a novel oncogenic driver in lung cancer that is clinically responsive to afatinib. Cancer Discov. 5, 1155–1163 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Ye, K. et al. Systematic discovery of complex insertions and deletions in human cancers. Nat. Med. 22, 97–104 (2016).

    Article  CAS  PubMed  Google Scholar 

  34. Pao, W. & Girard, N. New driver mutations in non-small-cell lung cancer. Lancet Oncol. 12, 175–180 (2011).

    Article  CAS  PubMed  Google Scholar 

  35. Pao, W. & Hutchinson, K.E. Chipping away at the lung cancer genome. Nat. Med. 18, 349–351 (2012).

    Article  CAS  PubMed  Google Scholar 

  36. Stephen, A.G., Esposito, D., Bagni, R.K. & McCormick, F. Dragging Ras back in the ring. Cancer Cell 25, 272–281 (2014).

    Article  CAS  PubMed  Google Scholar 

  37. Rajalingam, K., Schreck, R., Rapp, U.R. & Albert, S. Ras oncogenes and their downstream targets. Biochim. Biophys. Acta 1773, 1177–1195 (2007).

    Article  CAS  PubMed  Google Scholar 

  38. Lepri, F. et al. SOS1 mutations in Noonan syndrome: molecular spectrum, structural insights on pathogenic effects, and genotype–phenotype correlations. Hum. Mutat. 32, 760–772 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Swanson, K.D. et al. SOS1 mutations are rare in human malignancies: implications for Noonan syndrome patients. Genes Chromosom. Cancer 47, 253–259 (2008).

    Article  CAS  PubMed  Google Scholar 

  40. Yu, B. et al. Structural and energetic mechanisms of cooperative autoinhibition and activation of Vav1. Cell 140, 246–256 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Shan, L. et al. Concurrence of EGFR amplification and sensitizing mutations indicate a better survival benefit from EGFR-TKI therapy in lung adenocarcinoma patients. Lung Cancer 89, 337–342 (2015).

    Article  PubMed  Google Scholar 

  42. Sholl, L.M. et al. Lung adenocarcinoma with EGFR amplification has distinct clinicopathologic and molecular features in never-smokers. Cancer Res. 69, 8341–8348 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Liu, Y. et al. Metabolic and functional genomic studies identify deoxythymidylate kinase as a target in LKB1-mutant lung cancer. Cancer Discov. 3, 870–879 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Kim, H.S. et al. Systematic identification of molecular subtype–selective vulnerabilities in non-small-cell lung cancer. Cell 155, 552–566 (2013).

    Article  CAS  PubMed  Google Scholar 

  45. Brahmer, J. et al. Nivolumab versus docetaxel in advanced squamous-cell non–small-cell lung cancer. N. Engl. J. Med. 373, 123–135 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Rizvi, N.A. et al. Mutational landscape determines sensitivity to PD-1 blockade in non–small cell lung cancer. Science 348, 124–128 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Shukla, S.A. et al. Comprehensive analysis of cancer-associated somatic mutations in class I HLA genes. Nat. Biotechnol. 33, 1152–1158 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Gubin, M.M. et al. Checkpoint blockade cancer immunotherapy targets tumour-specific mutant antigens. Nature 515, 577–581 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Zhang, J. et al. Intratumor heterogeneity in localized lung adenocarcinomas delineated by multiregion sequencing. Science 346, 256–259 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. de Bruin, E.C. et al. Spatial and temporal diversity in genomic instability processes defines lung cancer evolution. Science 346, 251–256 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Peifer, M. et al. Integrative genome analyses identify key somatic driver mutations of small-cell lung cancer. Nat. Genet. 44, 1104–1110 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    CAS  PubMed  PubMed Central  Google Scholar 

  53. Cibulskis, K. et al. ContEst: estimating cross-contamination of human samples in next-generation sequencing data. Bioinformatics 27, 2601–2602 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Carter, S.L. et al. Absolute quantification of somatic DNA alterations in human cancer. Nat. Biotechnol. 30, 413–421 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Olshen, A.B., Venkatraman, E.S., Lucito, R. & Wigler, M. Circular binary segmentation for the analysis of array-based DNA copy number data. Biostatistics 5, 557–572 (2004).

    Article  PubMed  Google Scholar 

  57. Mermel, C.H. et al. GISTIC2.0 facilitates sensitive and confident localization of the targets of focal somatic copy-number alteration in human cancers. Genome Biol. 12, R41 (2011).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  58. Wang, K. et al. MapSplice: accurate mapping of RNA-seq reads for splice junction discovery. Nucleic Acids Res. 38, e178 (2010).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  59. Li, B. & Dewey, C.N. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinformatics 12, 323 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Brooks, A.N. et al. Conservation of an RNA regulatory map between Drosophila and mammals. Genome Res. 21, 193–202 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Yoshihara, K. et al. The landscape and therapeutic relevance of cancer-associated transcript fusions. Oncogene 34, 4845–4854 (2015).

    Article  CAS  PubMed  Google Scholar 

  62. Torres-García, W. et al. PRADA: pipeline for RNA sequencing data analysis. Bioinformatics 30, 2224–2226 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  63. Alberts, B. Molecular Biology of the Cell (Garland Science, 2002).

  64. Nielsen, M., Lundegaard, C., Lund, O. & Keşmir, C. The role of the proteasome in generating cytotoxic T-cell epitopes: insights obtained from improved predictions of proteasomal cleavage. Immunogenetics 57, 33–41 (2005).

    Article  CAS  PubMed  Google Scholar 

  65. Nielsen, M. et al. Reliable prediction of T-cell epitopes using neural networks with novel sequence representations. Protein Sci. 12, 1007–1017 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Hoof, I. et al. NetMHCpan, a method for MHC class I binding prediction beyond humans. Immunogenetics 61, 1–13 (2009).

    Article  CAS  PubMed  Google Scholar 

  67. Peters, B. & Sette, A. Generating quantitative models describing the sequence specificity of biological processes with the stabilized matrix method. BMC Bioinformatics 6, 132 (2005).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  68. Kim, Y., Sidney, J., Pinilla, C., Sette, A. & Peters, B. Derivation of an amino acid similarity matrix for peptide: MHC binding and its application as a Bayesian prior. BMC Bioinformatics 10, 394 (2009).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

Download references

Acknowledgements

This work was supported by grants from the National Cancer Institute as part of The Cancer Genome Atlas project: U24CA126546, U24CA143867, U24CA143845, U24CA126544, and U24CA143883. Additionally, this work was funded by National Cancer Institute grant K08CA163677 (P.S.H.), grant 074-U01 from the government of the Russian Federation (A.A.), US Department of Defense contract W81XWH-12-1-0269 (M.M.), the American Cancer Society Research Professor Award (M.M.), and National Cancer Institute grant R35CA197568 (M.M.).

Author information

Authors and Affiliations

Authors

Consortia

Contributions

J.D.C. performed sample quality control, mutation calling and review, ABSOLUTE analysis of tumors from the cohort of Imielinski et al., identification and comparison of recurrently altered genes, mutational signature identification and characterization, identification of EGFR complex indels, and manuscript writing. A.A., M.N.A., and R.S. generated neoantigen calls. J.K. contributed to mutational signature analyses. J.W. contributed to EGFR complex indel characterization. A.H.B. contributed to oncogene-negative analysis and manuscript preparation. C.S.P. generated the pan-lung portal. A.N.B. identified MET exon 14 skipping events using RNA-seq. X.H. and R.G.W.V. generated fusion calls. S.L. and R.A. performed batch effect analyses. G. Guo contributed to MET exon 14 complex indel identification. M.R., M.I., M.S.L., and G. Getz contributed algorithms for mutation calling and analyses. B.A.M. and A.D.C. contributed to copy number and ABSOLUTE analyses. S.A.S. and C.J.W. performed HLA genotyping. C.C. contributed to sample coordination and quality control. A.R., A.D.C., E.A.C., J.N.W., P.S.H., and D.J.K. contributed to manuscript preparation. R.G. and M.M. conceived and designed the study and wrote the manuscript.

Corresponding authors

Correspondence to Ramaswamy Govindan or Matthew Meyerson.

Ethics declarations

Competing interests

Some authors received research support from Bayer Pharmaceuticals (C.S.P., B.A.M., A.D.C., and M.M.).

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–18. (PDF 9493 kb)

Supplementary Tables 1–23

Supplementary Tables 1–23. (XLSX 7951 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Campbell, J., Alexandrov, A., Kim, J. et al. Distinct patterns of somatic genome alterations in lung adenocarcinomas and squamous cell carcinomas. Nat Genet 48, 607–616 (2016). https://doi.org/10.1038/ng.3564

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/ng.3564

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