We use cookies to improve your experience. By continuing to browse this site, you accept our cookie policy.×
Skip main navigation
Aging Health
Bioelectronics in Medicine
Biomarkers in Medicine
Breast Cancer Management
CNS Oncology
Colorectal Cancer
Concussion
Epigenomics
Future Cardiology
Future Medicine AI
Future Microbiology
Future Neurology
Future Oncology
Future Rare Diseases
Future Virology
Hepatic Oncology
HIV Therapy
Immunotherapy
International Journal of Endocrine Oncology
International Journal of Hematologic Oncology
Journal of 3D Printing in Medicine
Lung Cancer Management
Melanoma Management
Nanomedicine
Neurodegenerative Disease Management
Pain Management
Pediatric Health
Personalized Medicine
Pharmacogenomics
Regenerative Medicine
Research Article

Comprehensive epigenetic analysis of the signature genes in lung adenocarcinoma

    Yunfeng Zhang

    *Author for correspondence: Tel.: +86 29 8532 4615; Fax: +86 29 8525 2580;

    E-mail Address: zyf100@xjtu.edu.cn

    Second Department of Thoracic Surgery, First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China

    ,
    Weidong Zhao

    Department of Oncosurgery, Weinan Central Hospital of Shanxi Province, Weinan, China

    &
    Jia Zhang

    Second Department of Thoracic Surgery, First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China

    Published Online:https://doi.org/10.2217/epi-2017-0023

    Aim: This study aimed to explore the epigenetic modifications of signature genes in lung adenocarcinoma. Materials & methods: The data of miRNA expression, mRNA expression and DNA methylation were downloaded from The Cancer Genome Atlas. Differential analysis was performed, followed by correlation analysis of miRNA–mRNA and DNA methylation-mRNA. Results: A total of 14 significant inverse correlations between gene expression and DNA methylation were identified, the expressions of which were selected for further validation via GSE27262, displaying similar pattern with that of the integrated analysis. In addition, qRT-PCR results showed that the expression profiling results of six mRNAs and one miRNA were consistent with the findings of integrated analysis. Five genes showed higher diagnostic value, which was also associated with overall survival of patients. Conclusion: Taken together, the epigenetic alterations of signature genes may hold promise for becoming biomarkers for the early detection of lung adenocarcinoma.

    References

    • 1 Jemal A, Bray F, Center MM, Ferlay J, Ward E, Forman D. Global cancer statistics. CA Cancer J. Clin. 61(2), 69–90 (2011).
    • 2 Molina JR, Yang P, Cassivi SD, Schild SE, Adjei AA. Non-small-cell lung cancer: epidemiology, risk factors, treatment, and survivorship. Mayo Clin. Proc. 83(5), 584–594 (2008).
    • 3 Tian Z, Wen S, Zhang Y et al. Identification of dysregulated long non-coding RNAs/microRNAs/mRNAs in TNM I stage lung adenocarcinoma. Oncotarget doi:10.18632/oncotarget.18512 (2017) (Epub ahead of print).
    • 4 Ricordel C, Labalette-Tiercin M, Lespagnol A et al. EFGR-mutant lung adenocarcinoma and Li–Fraumeni syndrome: report of two cases and review of the literature. Lung Cancer 87(1), 80–84 (2015).
    • 5 Yano T, Haro A, Shikada Y, Maruyama R, Maehara Y. Non-small-cell lung cancer in never smokers as a representative ‘non-smoking-associated lung cancer’: epidemiology and clinical features. Int. J. Clin. Oncol. 16(4), 287–293 (2011).
    • 6 Du J, Zhang L. Integrated analysis of DNA methylation and microRNA regulation of the lung adenocarcinoma transcriptome. Oncol. Rep. 34(2), 585–594 (2015).
    • 7 Suzuki A, Makinoshima H, Wakaguri H et al. Aberrant transcriptional regulations in cancers: genome, transcriptome and epigenome analysis of lung adenocarcinoma cell lines. Nucleic Acids Res. 42(22), 13557–13572 (2014).
    • 8 Yang ZH, Zheng R, Gao Y, Zhang Q, Zhang H. Abnormal gene expression and gene fusion in lung adenocarcinoma with high-throughput RNA sequencing. Cancer Gene Ther. 21(2), 74–82 (2014).
    • 9 Seo JS, Ju YS, Lee WC et al. The transcriptional landscape and mutational profile of lung adenocarcinoma. Genome Res. 22(11), 2109–2119 (2012).
    • 10 Zhang S, Zhong B, Chen M et al. Epigenetic reprogramming reverses the malignant epigenotype of the MMP/TIMP axis genes in tumor cells. Int. J. Cancer 134(7), 1583–1594 (2014).
    • 11 Valdmanis PN, Roy-Chaudhuri B, Kim HK et al. Upregulation of the microRNA cluster at the Dlk1-Dio3 locus in lung adenocarcinoma. Oncogene 34(1), 94–103 (2013).
    • 12 Johnson SM, Grosshans H, Shingara J et al. RAS is regulated by the let-7 microRNA family. Cell 120(5), 635–647 (2005).
    • 13 Heyn H, Esteller M. DNA methylation profiling in the clinic: applications and challenges. Nat. Rev. Genet. 13(10), 679–692 (2012).
    • 14 Esteller M. Epigenetics in cancer. N. Engl. J. Med. 358(11), 1148–1159 (2008).
    • 15 Esteller M. Epigenetic gene silencing in cancer: the DNA hypermethylome. Hum. Mol. Genet. 16(R1), R50–R59 (2007).
    • 16 Robertson KD. DNA methylation and human disease. Nat. Rev. Genet. 6(8), 597–610 (2005).
    • 17 Selamat SA, Chung BS, Girard L et al. Genome-scale analysis of DNA methylation in lung adenocarcinoma and integration with mRNA expression. Genome Res. 22(7), 1197–1211 (2012).
    • 18 Anders S, Huber W. Differential expression analysis for sequence count data. Genome Biol. 11(10), R106 (2010).
    • 19 Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R Stat. Soc. Series B (Methodol.) 57(1), 289–300 (1995).
    • 20 Warden CD, Lee H, Tompkins JD et al. COHCAP: an integrative genomic pipeline for single-nucleotide resolution DNA methylation analysis. Nucleic Acids Res. 41(11), e117 (2013).
    • 21 Smoot ME, Ono K, Ruscheinski J, Wang PL, Ideker T. Cytoscape 2.8: new features for data integration and network visualization. Bioinformatics 27(3), 431–432 (2011).
    • 22 Young MD, Wakefield MJ, Smyth GK, Oshlack A. Gene ontology analysis for RNA-seq: accounting for selection bias. Genome Biol. 11(2), R14 (2010).
    • 23 Kanehisa M, Goto S. KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Res. 28(1), 27–30 (2000).
    • 24 Bustin SA, Benes V, Garson JA et al. The MIQE guidelines: minimum information for publication of quantitative real-time PCR experiments. Clin. Chem. 55(4), 611–622 (2009).
    • 25 Robin X, Turck N, Hainard A et al. pROC: an open-source package for R and S+ to analyze and compare ROC curves. BMC Bioinformatics 12, 77 (2011).
    • 26 Saito M, Shiraishi K, Kunitoh H, Takenoshita S, Yokota J, Kohno T. Gene aberrations for precision medicine against lung adenocarcinoma. Cancer Sci. 107(6), 713–720 (2016).
    • 27 Krasnov GS, Dmitriev AA, Melnikova NV et al. CrossHub: a tool for multi-way analysis of The Cancer Genome Atlas (TCGA) in the context of gene expression regulation mechanisms. Nucleic Acids Res. 44(7), e62 (2016).
    • 28 Tiger CF, Fougerousse F, Grundstrom G, Velling T, Gullberg D. Alpha11beta1 integrin is a receptor for interstitial collagens involved in cell migration and collagen reorganization on mesenchymal nonmuscle cells. Dev. Biol. 237(1), 116–129 (2001).
    • 29 Wang KK, Liu N, Radulovich N et al. Novel candidate tumor marker genes for lung adenocarcinoma. Oncogene 21(49), 7598–7604 (2002).
    • 30 Chong IW, Chang MY, Chang HC et al. Great potential of a panel of multiple hMTH1, SPD, ITGA11 and COL11A1 markers for diagnosis of patients with non-small-cell lung cancer. Oncol. Rep. 16(5), 981–988 (2006).
    • 31 Xu JB, Bao Y, Liu X, Liu Y, Huang S, Wang JC. Defective expression of transforming growth factor beta type II receptor (TGFBR2) in the large cell variant of non-small-cell lung carcinoma. Lung Cancer 58(1), 36–43 (2007).
    • 32 Dmitriev AA, Kashuba VI, Haraldson K et al. Genetic and epigenetic analysis of non-small-cell lung cancer with NotI-microarrays. Epigenetics 7(5), 502–513 (2012).
    • 33 Qu H, Zhu M, Tao Y, Zhao Y. Suppression of peripheral myelin protein 22 (PMP22) expression by miR29 inhibits the progression of lung cancer. Neoplasma 62(6), 881–886 (2015).
    • 34 Iruela-Arispe ML, Luque A, Lee N. Thrombospondin modules and angiogenesis. Int. J. Biochem. Cell Biol. 36(6), 1070–1078 (2004).
    • 35 Lawler J. The functions of thrombospondin-1 and-2. Curr. Opin. Cell Biol. 12(5), 634–640 (2000).
    • 36 Chijiwa T, Abe Y, Inoue Y et al. Cancerous, but not stromal, thrombospondin-2 contributes prognosis in pulmonary adenocarcinoma. Oncol. Rep. 22(2), 279–283 (2009).
    • 37 Metodieva SN, Nikolova DN, Cherneva RV, Dimova Ii, Petrov DB, Toncheva DI. Expression analysis of angiogenesis-related genes in Bulgarian patients with early-stage non-small-cell lung cancer. Tumori 97(1), 86–94 (2011).
    • 38 Tessema M, Yingling CM, Snider AM et al. GATA2 is epigenetically repressed in human and mouse lung tumors and is not requisite for survival of KRAS mutant lung cancer. J. Thorac. Oncol. 9(6), 784–793 (2014).
    • 39 Zhang ML, Nie FQ, Sun M et al. HOXA5 indicates poor prognosis and suppresses cell proliferation by regulating p21 expression in non-small-cell lung cancer. Tumour Biol. 36(5), 3521–3531 (2015).
    • 40 Kim DS, Kim MJ, Lee JY et al. Epigenetic inactivation of Homeobox A5 gene in non-small-cell lung cancer and its relationship with clinicopathological features. Mol. Carcinog. 48(12), 1109–1115 (2009).
    • 41 Huang T, Li J, Zhang C et al. Distinguishing lung adenocarcinoma from lung squamous cell carcinoma by two hypomethylated and three hypermethylated genes: a meta-analysis. PLoS ONE 11(2), e0149088 (2016).
    • 42 Yin D, Jia Y, Yu Y et al. SOX17 methylation inhibits its antagonism of Wnt signaling pathway in lung cancer. Discov. Med. 14(74), 33–40 (2012).
    • 43 Li W, Huang K, Guo H, Cui G. Meis1 regulates proliferation of non-small-cell lung cancer cells. J. Thorac. Dis. 6(6), 850–855 (2014).
    • 44 Rauch TA, Wang Z, Wu X, Kernstine KH, Riggs AD, Pfeifer GP. DNA methylation biomarkers for lung cancer. Tumour Biol. 33(2), 287–296 (2012).
    • 45 Waddington CH. The epigenotype. 1942. Int. J. Epidemiol. 41(1), 10–13 (2012).