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:

EPHA5 mutation predicts the durable clinical benefit of immune checkpoint inhibitors in patients with lung adenocarcinoma

Abstract

Immune checkpoint inhibitor (ICI) therapy has shown remarkable clinical benefit in lung adenocarcinoma (LUAD) patients. Genomic mutations may be applicable to predict the response to ICIs. Eph receptor A5 (EPHA5) is frequently mutated in breast cancer, lung cancer, and other tumors; however, its association with outcome in patients who receive immunotherapy remains unknown. In this study, we report that EPHA5 mutations were associated with increased tumor mutation burden (TMB), neoantigen load, levels of immune-related gene expression signatures, and enhanced tumor-infiltrating lymphocytes (TILs) in LUAD. LUAD patients with EPHA5 mutations in the immunotherapy cohort achieved a longer progression-free survival (PFS) time than patients with wild-type EPHA5. Immune response pathways were among the top enriched pathways in samples with EPHA5 mutations. In addition, patients with EPHA5 mutations tended to be more sensitive to certain targeted molecular inhibitors, including serdemetan, lox2, and PF1-1. Collectively, our results suggest that identifying mutations in the EPHA5 gene may provide insight into the genome-wide mutational burden and may serve as a biomarker to predict the immune response of patients with LUAD.

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: Landscapes of EPHA5 gene mutations in LUAD.
Fig. 2: EPHA5 mutation is associated with tumor immunogenicity and immunotherapy outcomes in LUAD patients.
Fig. 3: EPHA5 mutation is associated with high CNV counts.
Fig. 4: EPHA5 mutation is associated with a unique immune response.
Fig. 5: EPHA5 mutation is associated with high mutation frequencies of DDR pathway genes.
Fig. 6: EPHA5 mutation and drug selection of LUAD cells.
Fig. 7: Pathway enrichment analysis of EPHA5 mutation.

Similar content being viewed by others

References

  1. Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2018;68:394–424.

    Article  PubMed  Google Scholar 

  2. Kumarakulasinghe NB, van Zanwijk N, Soo RA. Molecular targeted therapy in the treatment of advanced stage non-small cell lung cancer (NSCLC). Respirology. 2015;20:370–8.

    Article  PubMed  Google Scholar 

  3. Travis W, Brambilla E, Noguchi M, Nicholson A, Geisinger K, Yatabe Y, et al. International association for the study of lung cancer/american thoracic society/european respiratory society international multidisciplinary classification of lung adenocarcinoma. J Thorac Oncol: Off Publ Int Assoc Study Lung Cancer. 2011;6:244–85.

    Article  Google Scholar 

  4. Liu K, Guo J, Liu K, Fan P, Zeng Y, Xu C, et al. Integrative analysis reveals distinct subtypes with therapeutic implications in KRAS-mutant lung adenocarcinoma. EBioMedicine. 2018;36:196–208.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Hugo W, Zaretsky JM, Sun L, Song C, Moreno BH, Hu-Lieskovan S, et al. Genomic and transcriptomic features of response to Anti-PD-1 therapy in metastatic melanoma. Cell. 2017;168:542.

    Article  CAS  PubMed  Google Scholar 

  6. Sarfaty M, Leshno M, Gordon N, Moore A, Neiman V, Rosenbaum E, et al. Cost effectiveness of nivolumab in advanced renal cell carcinoma. Eur Urol. 2018;73:628–34.

    Article  PubMed  Google Scholar 

  7. Seiwert TY, Burtness B, Mehra R, Weiss J, Berger R, Eder JP, et al. Safety and clinical activity of pembrolizumab for treatment of recurrent or metastatic squamous cell carcinoma of the head and neck (KEYNOTE-012): an open-label, multicentre, phase 1b trial. Lancet Oncol. 2016;17:956–65.

    Article  CAS  PubMed  Google Scholar 

  8. Assi HI, Kamphorst AO, Moukalled NM, Ramalingam SS. Immune checkpoint inhibitors in advanced non-small cell lung cancer. Cancer. 2018;124:248–61.

    Article  PubMed  Google Scholar 

  9. Carbognin L, Pilotto S, Milella M, Vaccaro V, Brunelli M, Calio A, et al. Differential activity of nivolumab, pembrolizumab and MPDL3280A according to the tumor expression of programmed death-ligand-1 (PD-L1): sensitivity analysis of trials in melanoma, lung and genitourinary cancers. PLoS ONE. 2015;10:e0130142.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  10. Reck M, Rodriguez-Abreu D, Robinson AG, Hui R, Csoszi T, Fulop A, et al. Pembrolizumab versus chemotherapy for PD-L1-positive non-small-cell lung cancer. N Engl J Med. 2016;375:1823–33.

    Article  CAS  PubMed  Google Scholar 

  11. Le DT, Durham JN, Smith KN, Wang H, Bartlett BR, Aulakh LK, et al. Mismatch repair deficiency predicts response of solid tumors to PD-1 blockade. Science. 2017;357:409–13.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Taube JM, Klein A, Brahmer JR, Xu H, Pan X, Kim JH, et al. Association of PD-1, PD-1 ligands, and other features of the tumor immune microenvironment with response to anti-PD-1 therapy. Clin Cancer Res. 2014;20:5064–74.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Rizvi H, Sanchez-Vega F, La K, Chatila W, Jonsson P, Halpenny D, et al. Molecular determinants of response to anti-programmed cell death (PD)-1 and anti-programmed death-ligand 1 (PD-L1) blockade in patients with non-small-cell lung cancer profiled with targeted next-generation sequencing. J Clin Oncol. 2018;36:633–41.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Tang H, Wang Y, Chlewicki LK, Zhang Y, Guo J, Liang W, et al. Facilitating T cell infiltration in tumor microenvironment overcomes resistance to PD-L1 blockade. Cancer Cell. 2016;29:285–96.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Lauss M, Donia M, Harbst K, Andersen R, Mitra S, Rosengren F, et al. Mutational and putative neoantigen load predict clinical benefit of adoptive T cell therapy in melanoma. Nat Commun. 2017;8:1738.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  16. Dong ZY, Zhong WZ, Zhang XC, Su J, Xie Z, Liu SY, et al. Potential predictive value of TP53 and KRAS mutation status for response to PD-1 blockade immunotherapy in lung adenocarcinoma. Clin Cancer Res. 2017;23:3012–24.

    Article  CAS  PubMed  Google Scholar 

  17. Gale NW, Holland SJ, Valenzuela DM, Flenniken A, Pan L, Ryan TE, et al. Eph receptors and ligands comprise two major specificity subclasses and are reciprocally compartmentalized during embryogenesis. Neuron. 1996;17:9–19.

    Article  CAS  PubMed  Google Scholar 

  18. Shiuan E, Chen J. Eph receptor tyrosine kinases in tumor immunity. Cancer Res. 2016;76:6452–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Chiari R, Hames G, Stroobant V, Texier C, Maillere B, Boon T, et al. Identification of a tumor-specific shared antigen derived from an Eph receptor and presented to CD4 T cells on HLA class II molecules. Cancer Res. 2000;60:4855–63.

    CAS  PubMed  Google Scholar 

  20. Tatsumi T, Herrem CJ, Olson WC, Finke JH, Bukowski RM, Kinch MS, et al. Disease stage variation in CD4+ and CD8+ T-cell reactivity to the receptor tyrosine kinase EphA2 in patients with renal cell carcinoma. Cancer Res. 2003;63:4481–9.

    CAS  PubMed  Google Scholar 

  21. Alves PM, Faure O, Graff-Dubois S, Gross DA, Cornet S, Chouaib S, et al. EphA2 as target of anticancer immunotherapy: identification of HLA-A*0201-restricted epitopes. Cancer Res. 2003;63:8476–80.

    CAS  PubMed  Google Scholar 

  22. Aasheim HC, Delabie J, Finne EF. Ephrin-A1 binding to CD4+ T lymphocytes stimulates migration and induces tyrosine phosphorylation of PYK2. Blood. 2005;105:2869–76.

    Article  CAS  PubMed  Google Scholar 

  23. Hjorthaug HS, Aasheim HC. Ephrin-A1 stimulates migration of CD8+CCR7+ T lymphocytes. Eur J Immunol. 2007;37:2326–36.

    Article  CAS  PubMed  Google Scholar 

  24. Holen HL, Nustad K, Aasheim HC. Activation of EphA receptors on CD4+CD45RO+ memory cells stimulates migration. J Leukoc Biol. 2010;87:1059–68.

    Article  CAS  PubMed  Google Scholar 

  25. Zhang J, Zhang Z, Song W, Liu J, Zhang Y. EPHA5 mutation impairs natural killer cell-mediated cytotoxicity against non-small lung cancer cells and promotes cancer cell migration and invasion. Mol Cell Probes. 2020;52:101566.

    Article  CAS  PubMed  Google Scholar 

  26. Colaprico A, Silva TC, Olsen C, Garofano L, Cava C, Garolini D, et al. TCGAbiolinks: an R/Bioconductor package for integrative analysis of TCGA data. Nucleic Acids Res. 2016;44:e71.

    Article  PubMed  CAS  Google Scholar 

  27. Cerami E, Gao J, Dogrusoz U, Gross BE, Sumer SO, Aksoy BA, et al. The cBio cancer genomics portal: an open platform for exploring multidimensional cancer genomics data. Cancer Discov. 2012;2:401–4.

    Article  PubMed  Google Scholar 

  28. Yang W, Soares J, Greninger P, Edelman E, Lightfoot H, Forbes S, et al. Genomics of drug sensitivity in cancer (GDSC): a resource for therapeutic biomarker discovery in cancer cells. Nucleic Acids Res. 2013;41:D955–61.

    Article  CAS  PubMed  Google Scholar 

  29. Chalmers ZR, Connelly CF, Fabrizio D, Gay L, Ali SM, Ennis R, et al. Analysis of 100,000 human cancer genomes reveals the landscape of tumor mutational burden. Genome Med. 2017;9:34.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  30. Gu Z, Eils R, Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847–9.

    Article  CAS  PubMed  Google Scholar 

  31. Mayakonda A, Lin DC, Assenov Y, Plass C, Koeffler HP. Maftools: efficient and comprehensive analysis of somatic variants in cancer. Genome Res. 2018;28:1747–56.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Newman AM, Liu CL, Green MR, Gentles AJ, Feng W, Xu Y, et al. Robust enumeration of cell subsets from tissue expression profiles. Nat Methods. 2015;12:453–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Thorsson V, Gibbs DL, Brown SD, Wolf D, Bortone DS, Ou Yang TH, et al. The immune landscape of cancer. Immunity. 2018;48:812–30.e14.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Reich M, Liefeld T, Gould J, Lerner J, Tamayo P, Mesirov J. GenePattern 2.0. Nat Genet. 2006;38:500–1.

    Article  CAS  PubMed  Google Scholar 

  35. Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2010;26:139–40.

    Article  CAS  PubMed  Google Scholar 

  36. Yu G, Wang LG, Han Y, He QY. clusterProfiler: an R package for comparing biological themes among gene clusters. Omics. 2012;16:284–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Subramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, Gillette MA, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci USA. 2005;102:15545–50.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Davoli T, Uno H, Wooten E, Elledge S. Tumor aneuploidy correlates with markers of immune evasion and with reduced response to immunotherapy. Science. 2017;355:eaaf8399.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  39. Liu L, Bai X, Wang J, Tang XR, Wu DH, Du SS, et al. Combination of TMB and CNA stratifies prognostic and predictive responses to immunotherapy across metastatic cancer. Clin Cancer Res. 2019;25:7413–23.

    Article  CAS  PubMed  Google Scholar 

  40. Vishnubalaji R, Shaath H, Elango R, Alajez NM. Noncoding RNAs as potential mediators of resistance to cancer immunotherapy. Semin Cancer Biol. 2019;S1044-579X:30223–8.

    Google Scholar 

  41. Tuzi NL, Gullick WJ. eph, the largest known family of putative growth factor receptors. Br J Cancer. 1994;69:417–21.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Pasquale EB. The Eph family of receptors. Curr Opin Cell Biol. 1997;9:608–15.

    Article  CAS  PubMed  Google Scholar 

  43. Darling T, Lamb T. Emerging roles for Eph receptors and ephrin ligands in immunity. Front Immunol. 2019;10:1473.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Jeong HM, Kim RN, Kwon MJ, Oh E, Han J, Lee SK, et al. Targeted exome sequencing of Korean triple-negative breast cancer reveals homozygous deletions associated with poor prognosis of adjuvant chemotherapy-treated patients. Oncotarget. 2017;8:61538–50.

    Article  PubMed  PubMed Central  Google Scholar 

  45. Quinn AM, Hickson N, Adaway M, Priest L, Jaeger E, Udar N, et al. Diagnostic mutation profiling and validation of non-small-cell lung cancer small biopsy samples using a high throughput platform. J Thorac Oncol. 2015;10:784–92.

    Article  CAS  PubMed  Google Scholar 

  46. Qian J, Nie W, Lu J, Zhang L, Zhang Y, Zhang B, et al. Racial differences in characteristics and prognoses between Asian and white patients with nonsmall cell lung cancer receiving atezolizumab: an ancillary analysis of the POPLAR and OAK studies. Int J Cancer. 2019;146:3124–33.

    Article  PubMed  CAS  Google Scholar 

  47. Li Y, Chu J, Feng W, Yang M, Zhang Y, Zhang Y, et al. EPHA5 mediates trastuzumab resistance in HER2-positive breast cancers through regulating cancer stem cell-like properties. FASEB J. 2019;33:4851–65.

    Article  CAS  PubMed  Google Scholar 

  48. Gu S, Feng J, Jin Q, Wang W, Zhang S. Reduced expression of EphA5 is associated with lymph node metastasis, advanced TNM stage, and poor prognosis in colorectal carcinoma. Histol Histopathol. 2017;32:491–7.

    CAS  PubMed  Google Scholar 

  49. Staquicini F, Qian M, Salameh A, Dobroff A, Edwards J, Cimino D, et al. Receptor tyrosine kinase EphA5 is a functional molecular target in human lung cancer. J Biol Chem. 2015;290:7345–59.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to Qingwen Lyu, Linlang Guo or Jian Zhang.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

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

Supplementary information

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Huang, W., Lin, A., Luo, P. et al. EPHA5 mutation predicts the durable clinical benefit of immune checkpoint inhibitors in patients with lung adenocarcinoma. Cancer Gene Ther 28, 864–874 (2021). https://doi.org/10.1038/s41417-020-0207-6

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41417-020-0207-6

This article is cited by

Search

Quick links