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Dissecting the m6A methylation affection on afatinib resistance in non-small cell lung cancer

The Pharmacogenomics Journal volume 20, pages 227–234 (2020)Cite this article

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Abstract

Non-small cell lung cancer (NSCLC) is one of the leading causes of cancer deaths. Afatinib is the first-line anti-cancer agent for treatment of NSCLC. However, unexpected resistance has been a major obstacle for its clinical efficacy. In this study, we dissected afatinib resistance from the perspective of N6-Methyladenosine (m6A) modification. First, we depicted the m6A modification profiles for the afatinib resistant and sensitive NSCLC cell lines (H1299 and A549). We found that the sum enrichment scores of the resistant cell line (H1299) was much higher than that of the sensitive cell line (A549). Next, we identified the functionally m6A-modified genes, which were the intersection of the differentially m6A methylated genes and the differentially expressed genes between H1299 and A549, as well as negative correlation between m6A modification levels and gene expression levels. In addition, functional enrichment analysis of the functionally m6A-modified genes indicated that m6A methylation might modify cell cycle to affect afatinib response. Furthermore, the functionally m6A-modified genes were over-represented in the putative drug resistance-associated genes and the FDA-approved drug targets, and had significantly higher average degree and clustering coefficient than other genes in protein–protein interaction (PPI) network. We also identified five network modules, which were all related to drug resistance functions. Finally, survival analysis demonstrated that m6A modification could affect prognosis of NSCLC patients. In conclusion, we conducted a first attempt to dissect m6A methylation affection on afatinib resistance in NSCLC, and brought inspiration for the study of epigenetic roles in drug resistance.

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References

  1. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2017. CA Cancer J Clin. 2017;67:7–30.

    PubMed  Google Scholar 

  2. Chunhacha P, Chanvorachote P. Roles of caveolin-1 on anoikis resistance in non small cell lung cancer. Int J Physiol Pathophysiol Pharmacol. 2012;4:149–55.

    CAS  PubMed  PubMed Central  Google Scholar 

  3. Herbst RS, Heymach JV, Lippman SM. Lung cancer. New Engl J Med. 2008;359:1367–80.

    Article  CAS  PubMed  Google Scholar 

  4. Keating GM. Afatinib: a review in advanced non-small cell lung cancer. Target Oncol. 2016;11:825–35.

    Article  PubMed  Google Scholar 

  5. Schuler M, Wu YL, Hirsh V, O’Byrne K, Yamamoto N, Mok T, et al. First-line afatinib versus chemotherapy in patients with non-small cell lung cancer and common epidermal growth factor receptor gene mutations and brain metastases. J Thorac Oncol. 2016;11:380–90.

    Article  PubMed  Google Scholar 

  6. Park K, Tan EH, O’Byrne K, Zhang L, Boyer M, Mok T, et al. Afatinib versus gefitinib as first-line treatment of patients with EGFR mutation-positive non-small-cell lung cancer (LUX-Lung 7): a phase 2B, open-label, randomised controlled trial. Lancet Oncol. 2016;17:577–89.

    Article  CAS  PubMed  Google Scholar 

  7. Yang JC, Wu YL, Schuler M, Sebastian M, Popat S, Yamamoto N, et al. Afatinib versus cisplatin-based chemotherapy for EGFR mutation-positive lung adenocarcinoma (LUX-Lung 3 and LUX-Lung 6): analysis of overall survival data from two randomised, phase 3 trials. Lancet Oncol. 2015;16:141–51.

    Article  CAS  PubMed  Google Scholar 

  8. Eberlein CA, Stetson D, Markovets AA, Al-Kadhimi KJ, Lai Z, Fisher PR, et al. Acquired resistance to the mutant-selective EGFR inhibitor AZD9291 is associated with increased dependence on RAS signaling in preclinical models. Cancer Res. 2015;75:2489–500.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Torigoe H, Shien K, Takeda T, Yoshioka T, Namba K, Sato H, et al. Therapeutic strategies for afatinib-resistant lung cancer harboring HER2 alterations. Cancer Sci. 2018;109:1493–502.

  10. Sharma SV, Lee DY, Li B, Quinlan MP, Takahashi F, Maheswaran S, et al. A chromatin-mediated reversible drug-tolerant state in cancer cell subpopulations. Cell. 2010;141:69–80.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Teodoridis JM, Hall J, Marsh S, Kannall HD, Smyth C, Curto J, et al. CpG island methylation of DNA damage response genes in advanced ovarian cancer. Cancer Res. 2005;65:8961–7.

    Article  CAS  PubMed  Google Scholar 

  12. Dai W, Teodoridis JM, Graham J, Zeller C, Huang TH, Yan P, et al. Methylation linear discriminant analysis (MLDA) for identifying differentially methylated CpG islands. BMC Bioinformatics. 2008;9:337.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Chang X, Monitto CL, Demokan S, Kim MS, Chang SS, Zhong X, et al. Identification of hypermethylated genes associated with cisplatin resistance in human cancers. Cancer Res. 2010;70:2870–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Ping XL, Sun BF, Wang L, Xiao W, Yang X, Wang WJ, et al. Mammalian WTAP is a regulatory subunit of the RNA N6-methyladenosine methyltransferase. Cell Res. 2014;24:177–89.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Dominissini D, Moshitch-Moshkovitz S, Schwartz S, Salmon-Divon M, Ungar L, Osenberg S, et al. Topology of the human and mouse m6A RNA methylomes revealed by m6A-seq. Nature. 2012;485:201–6.

    Article  CAS  PubMed  Google Scholar 

  16. Ke S, Alemu EA, Mertens C, Gantman EC, Fak JJ, Mele A, et al. A majority of m6A residues are in the last exons, allowing the potential for 3’ UTR regulation. Genes Dev. 2015;29:2037–53.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Molinie B, Wang J, Lim KS, Hillebrand R, Lu Z-X, Wittenberghe NV, et al. m(6)A-LAIC-seq reveals the census and complexity of the m(6)A epitranscriptome. Nat Methods. 2016;13:692–8.

  18. Fustin JM, Doi M, Yamaguchi Y, Hida H, Nishimura S, Yoshida M, et al. RNA-methylation-dependent RNA processing controls the speed of the circadian clock. Cell. 2013;155:793–806.

    Article  CAS  PubMed  Google Scholar 

  19. Zheng G, Dahl JA, Niu Y, Fedorcsak P, Huang CM, Li CJ, et al. ALKBH5 is a mammalian RNA demethylase that impacts RNA metabolism and mouse fertility. Mol Cell. 2013;49:18–29.

    Article  CAS  PubMed  Google Scholar 

  20. Wang X, Zhao BS, Roundtree IA, Lu Z, Han D, Ma H, et al. N(6)-methyladenosine modulates messenger RNA translation efficiency. Cell. 2015;161:1388–99.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Lin S, Choe J, Du P, Triboulet R, Gregory RI. The m(6)A methyltransferase METTL3 promotes translation in human cancer cells. Mol Cell. 2016;62:335–45.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Meyer KD, Patil DP, Zhou J, Zinoviev A, Skabkin MA, Elemento O, et al. 5’ UTR m(6)A Promotes cap-independent translation. Cell. 2015;163:999–1010.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Zhou J, Wan J, Gao X, Zhang X, Jaffrey SR, Qian SB. Dynamic m(6)A mRNA methylation directs translational control of heat shock response. Nature. 2015;526:591–4.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Wang Y, Li Y, Toth JI, Petroski MD, Zhang Z, Zhao JC. N6-methyladenosine modification destabilizes developmental regulators in embryonic stem cells. Nat Cell Biol. 2014;16:191–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Liu J, Yue Y, Han D, Wang X, Fu Y, Zhang L, et al. A METTL3-METTL14 complex mediates mammalian nuclear RNA N6-adenosine methylation. Nat Chem Biol. 2014;10:93–5.

    Article  CAS  PubMed  Google Scholar 

  26. Wang X, Lu Z, Gomez A, Hon GC, Yue Y, Han D, et al. N6-methyladenosine-dependent regulation of messenger RNA stability. Nature. 2014;505:117–20.

    Article  CAS  PubMed  Google Scholar 

  27. Niu Y, Zhao X, Wu YS, Li MM, Wang XJ, Yang YG. N6-methyl-adenosine (m6A) in RNA: an old modification with a novel epigenetic function. Genomics Proteomics Bioinformatics. 2013;11:8–17.

    Article  CAS  PubMed  Google Scholar 

  28. Yang W, Soares J, Greninger P, Edelman EJ, 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. McDermott M, Eustace AJ, Busschots S, Breen L, Crown J, Clynes M, et al. In vitro development of chemotherapy and targeted therapy drug-resistant cancer cell lines: a practical guide with case studies. Front Oncol. 2014;4:40.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Zhang C, Chen Y, Sun B, Wang L, Yang Y, Ma D, et al. m(6)A modulates haematopoietic stem and progenitor cell specification. Nature. 2017;549:273–6.

    Article  CAS  PubMed  Google Scholar 

  31. Yue Y, Liu J, He C. RNA N6-methyladenosine methylation in post-transcriptional gene expression regulation. Genes Dev. 2015;29:1343–55.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Batista PJ, Molinie B, Wang J, Qu K, Zhang J, Li L, et al. m(6)A RNA modification controls cell fate transition in mammalian embryonic stem cells. Cell Stem Cell. 2014;15:707–19.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Tong J, Cao G, Zhang T, Sefik E, Amezcua Vesely MC, Broughton JP, et al. m(6)A mRNA methylation sustains Treg suppressive functions. Cell Res. 2018;28:253–6.

    Article  PubMed  PubMed Central  Google Scholar 

  34. Di Nicolantonio F, Mercer SJ, Knight LA, Gabriel FG, Whitehouse PA, Sharma S, et al. Cancer cell adaptation to chemotherapy. BMC Cancer. 2005;5:78.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Wang J, Zhou F, Li Y, Li Q, Wu Z, Yu L, et al. Cdc20 overexpression is involved in temozolomide-resistant glioma cells with epithelial-mesenchymal transition. Cell Cycle. 2017;16:2355–65.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Vasiliou V, Vasiliou K, Nebert DW. Human ATP-binding cassette (ABC) transporter family. Hum Genomics. 2009;3:281–90.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Cree IA, Charlton P. Molecular chess? Hallmarks of anti-cancer drug resistance. BMC Cancer. 2017;17:10.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Kim S, Kim TM, Kim DW, Go H, Keam B, Lee SH, et al. Heterogeneity of genetic changes associated with acquired crizotinib resistance in ALK-rearranged lung cancer. J Thorac Oncol. 2013;8:415–22.

    Article  CAS  PubMed  Google Scholar 

  39. Murdock CC, Moller-Jacobs LL, Thomas MB. Complex environmental drivers of immunity and resistance in malaria mosquitoes. Proc Biol Sci. 2013;280:20132030.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Fonseca JD, Knight GM, McHugh TD. The complex evolution of antibiotic resistance in Mycobacterium tuberculosis. Int J Infect Dis. 2015;32:94–100.

    Article  CAS  PubMed  Google Scholar 

  41. Cheng F, Desai RJ, Handy DE, Wang R, Schneeweiss S, Barabási A-L, et al. Network-based approach to prediction and population-based validation of in silico drug repurposing. Nat Commun. 2018;9:2691.

  42. Cheng F, Kovacs IA, Barabasi AL. Network-based prediction of drug combinations. Nat Commun. 2019;10:1197.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Katsman A, Umezawa K, Bonavida B. Chemosensitization and immunosensitization of resistant cancer cells to apoptosis and inhibition of metastasis by the specific NF-kappaB inhibitor DHMEQ. Curr Pharm Des. 2009;15:792–808.

    Article  CAS  PubMed  Google Scholar 

  44. Dalton WS. The tumor microenvironment as a determinant of drug response and resistance. Drug Resist Updat. 1999;2:285–8.

    Article  CAS  PubMed  Google Scholar 

  45. Damiano JS, Cress AE, Hazlehurst LA, Shtil AA, Dalton WS. Cell adhesion mediated drug resistance (CAM-DR): role of integrins and resistance to apoptosis in human myeloma cell lines. Blood. 1999;93:1658–67.

    Article  CAS  PubMed  Google Scholar 

  46. Sethi T, Rintoul RC, Moore SM, MacKinnon AC, Salter D, Choo C, et al. Extracellular matrix proteins protect small cell lung cancer cells against apoptosis: a mechanism for small cell lung cancer growth and drug resistance in vivo. Nat Med. 1999;5:662–8.

    Article  CAS  PubMed  Google Scholar 

  47. Zheng Y, Zhou J, Tong Y. Gene signatures of drug resistance predict patient survival in colorectal cancer. Pharmacogenomics J. 2015;15:135–43.

    Article  CAS  PubMed  Google Scholar 

  48. Zhou M, Wang X, Shi H, Cheng L, Wang Z, Zhao H, et al. Characterization of long non-coding RNA-associated ceRNA network to reveal potential prognostic lncRNA biomarkers in human ovarian cancer. Oncotarget. 2016;7:12598–611.

    PubMed  PubMed Central  Google Scholar 

  49. Modjtahedi H, Essapen S. Epidermal growth factor receptor inhibitors in cancer treatment: advances, challenges and opportunities. Anti-Cancer Drugs. 2009;20:851–5.

    Article  CAS  PubMed  Google Scholar 

  50. Misale S, Arena S, Lamba S, Siravegna G, Lallo A, Hobor S, et al. Blockade of EGFR and MEK intercepts heterogeneous mechanisms of acquired resistance to anti-EGFR therapies in colorectal cancer. Sci Transl Med. 2014;6:224ra26.

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

This work was supported by the Foundation for The National Natural Science Foundation of China (61571169, 61872183, and 61801150) and the Fundamental Research Funds for the Central Universities (NE2018101).

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  1. These authors contributed equally: Qianqian Meng, Shuyuan Wang

Authors and Affiliations

  1. College of Bioinformatics Science and Technology, Harbin Medical University, 150081, Harbin, China

    Qianqian Meng, Shuyuan Wang, Xueyan Ma, Xu Zhou, Hui Liu, Chaohan Xu & Wei Jiang

  2. College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, 211106, Nanjing, China

    Shunheng Zhou, Haizhou Liu & Wei Jiang

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Meng, Q., Wang, S., Zhou, S. et al. Dissecting the m6A methylation affection on afatinib resistance in non-small cell lung cancer. Pharmacogenomics J 20, 227–234 (2020). https://doi.org/10.1038/s41397-019-0110-4

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