Identification of potential diagnostic and prognostic biomarkers in non-small cell lung cancer based on microarray data

Huang,Ru; Gao,Lei

doi:10.3892/ol.2018.8153

Identification of potential diagnostic and prognostic biomarkers in non-small cell lung cancer based on microarray data

Authors:
- Ru Huang
- Lei Gao
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Affiliations: Department of Heart Failure, Research Center for Translational Medicine, Shanghai East Hospital, Tongji University School of Medicine, Shanghai 200120, P.R. China
Published online on: March 1, 2018 https://doi.org/10.3892/ol.2018.8153
Pages: 6436-6442
Copyright: © Huang et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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Abstract

Non-small cell lung cancer (NSCLC) is the most commonly diagnosed subtype of lung cancer, and the leading cause of cancer-associated mortalities worldwide. However, NSCLC is typically diagnosed at a late stage of disease due to a lack of effective diagnostic methods. In the present study, the GSE19804 dataset was obtained from the Gene Expression Omnibus, and a number of differentially expressed genes were identified between NSCLC and adjacent normal tissues. Based on functional and pathway enrichment analyses, five hub genes (cell‑division cycle 20, centromere protein F, kinesin family member 2C, BUB1 mitotic checkpoint serine/threonine kinase and ZW10 interacting kinetochore protein) were selected. After verifying that the mRNA level of these hub genes was also upregulated in NSCLC tissues by using the GSE10072 dataset and in cell lines by reverse transcription‑quantitative polymerase chain reaction. The diagnostic and prognostic potentials of these five gene candidates were evaluated using receiver operating characteristic curves and survival analyses. Taken together, the present study identified five candidates that are overexpressed in NSCLC tissues and could also serve as potential diagnostic and prognostic biomarkers for patients with NSCLC.

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1	Smith RA, Manassaram-Baptiste D, Brooks D, Doroshenk M, Fedewa S, Saslow D, Brawley OW and Wender R: Cancer screening in the United States, 2015: A review of current American cancer society guidelines and current issues in cancer screening. CA Cancer J Clin. 65:30–54. 2015. View Article : Google Scholar : PubMed/NCBI
2	Thomas A, Liu SV, Subramaniam DS and Giaccone G: Refining the treatment of NSCLC according to histological and molecular subtypes. Nat Rev Clin Oncol. 12:511–526. 2015. View Article : Google Scholar : PubMed/NCBI
3	van Meerbeeck JP, Fennell DA and De Ruysscher DK: Small-cell lung cancer. Lancet. 378:1741–1755. 2011. View Article : Google Scholar : PubMed/NCBI
4	Lu Y, Lemon W, Liu PY, Yi Y, Morrison C, Yang P, Sun Z, Szoke J, Gerald WL, Watson M, et al: A gene expression signature predicts survival of patients with stage I non-small cell lung cancer. PLoS Med. 3:e4672006. View Article : Google Scholar : PubMed/NCBI
5	Chen F, Xiang CX, Zhou Y, Ao XS, Zhou DQ, Peng P, Zhang HQ, Liu HD and Huang X: Gene expression profile for predicting survival of patients with meningioma. Int J Oncol. 46:791–797. 2015. View Article : Google Scholar : PubMed/NCBI
6	Xu Z, Zhou Y, Cao Y, Dinh TL, Wan J and Zhao M: Identification of candidate biomarkers and analysis of prognostic values in ovarian cancer by integrated bioinformatics analysis. Med Oncol. 33:1302016. View Article : Google Scholar : PubMed/NCBI
7	Ioannidis JP, Allison DB, Ball CA, Coulibaly I, Cui X, Culhane AC, Falchi M, Furlanello C, Game L, Jurman G, et al: Repeatability of published microarray gene expression analyses. Nat Genet. 41:149–155. 2009. View Article : Google Scholar : PubMed/NCBI
8	Lu TP, Tsai MH, Lee JM, Hsu CP, Chen PC, Lin CW, Shih JY, Yang PC, Hsiao CK, Lai LC and Chuang EY: Identification of a novel biomarker, SEMA5A, for non-small cell lung carcinoma in nonsmoking women. Cancer Epidemiol Biomarkers Prev. 19:2590–2597. 2010. View Article : Google Scholar : PubMed/NCBI
9	Landi MT, Dracheva T, Rotunno M, Figueroa JD, Liu H, Dasgupta A, Mann FE, Fukuoka J, Hames M, Bergen AW, et al: Gene expression signature of cigarette smoking and its role in lung adenocarcinoma development and survival. PLoS One. 3:e16512008. View Article : Google Scholar : PubMed/NCBI
10	Barrett T, Wilhite SE, Ledoux P, Evangelista C, Kim IF, Tomashevsky M, Marshall KA, Phillippy KH, Sherman PM, Holko M, et al: NCBI GEO: Archive for functional genomics data sets-update. Nucleic Acids Res. 41:(Database Issue). D991–D995. 2013. View Article : Google Scholar : PubMed/NCBI
11	Szklarczyk D, Franceschini A, Wyder S, Forslund K, Heller D, Huerta-Cepas J, Simonovic M, Roth A, Santos A, Tsafou KP, et al: STRING v10: Protein-protein interaction networks, integrated over the tree of life. Nucl Acids Res. 43:(Database Issue). D447–D452. 2015. View Article : Google Scholar : PubMed/NCBI
12	Sun B, Gao L, Ahsan A, Chu P, Song Y, Li H, Zhang Z, Lin Y, Peng J, Song Z, et al: Anticancer effect of SZC015 on lung cancer cells through ROS-dependent apoptosis and autophagy induction mechanisms in vitro. Int Immunopharmacol. 40:400–409. 2016. View Article : Google Scholar : PubMed/NCBI
13	Livak KJ and Schmittgen TD: Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) method. Methods. 25:402–408. 2001. View Article : Google Scholar : PubMed/NCBI
14	Győrffy B, Surowiak P, Budczies J and Lanczky A: Online survival analysis software to assess the prognostic value of biomarkers using transcriptomic data in non-small-cell lung cancer. PLoS One. 8:e822412013. View Article : Google Scholar : PubMed/NCBI
15	Shi YX, Zhu T, Zou T, Zhuo W, Chen YX, Huang MS, Zheng W, Wang CJ, Li X, Mao XY, et al: Prognostic and predictive values of CDK1 and MAD2L1 in lung adenocarcinoma. Oncotarget. 7:85235–85243. 2016. View Article : Google Scholar : PubMed/NCBI
16	Gong Y, Yao E, Shen R, Goel A, Arcila M, Teruya-Feldstein J, Zakowski MF, Frankel S, Peifer M, Thomas RK, et al: High expression levels of total IGF-1R and sensitivity of NSCLC cells in vitro to an anti-IGF-1R antibody (R1507). PLoS One. 4:e72732009. View Article : Google Scholar : PubMed/NCBI
17	Dominguez-Brauer C, Thu KL, Mason JM, Blaser H, Bray MR and Mak TW: Targeting mitosis in cancer: Emerging strategies. Mol Cell. 60:524–536. 2015. View Article : Google Scholar : PubMed/NCBI
18	Hydbring P, Malumbres M and Sicinski P: Non-canonical functions of cell cycle cyclins and cyclin-dependent kinases. Nat Rev Mol Cell Biol. 17:280–292. 2016. View Article : Google Scholar : PubMed/NCBI
19	Qian X, Song X, He Y, Yang Z, Sun T, Wang J, Zhu G, Xing W and You C: CCNB2 overexpression is a poor prognostic biomarker in Chinese NSCLC patients. Biomed Pharmacother. 74:222–227. 2015. View Article : Google Scholar : PubMed/NCBI
20	Frescas D and Pagano M: Deregulated proteolysis by the F-box proteins SKP2 and beta-TrCP: Tipping the scales of cancer. Nat Rev Cancer. 8:438–449. 2008. View Article : Google Scholar : PubMed/NCBI
21	Varis A, Salmela AL and Kallio MJ: Cenp-F (mitosin) is more than a mitotic marker. Chromosoma. 115:288–295. 2006. View Article : Google Scholar : PubMed/NCBI
22	Wordeman L: Microtubule-depolymerizing kinesins. Curr Opin Cell Biol. 17:82–88. 2005. View Article : Google Scholar : PubMed/NCBI
23	Taylor SS and McKeon F: Kinetochore localization of murine Bub1 is required for normal mitotic timing and checkpoint response to spindle damage. Cell. 89:727–735. 1997. View Article : Google Scholar : PubMed/NCBI
24	Seo Woo D, You Yeop S, Chung WJ, Cho DH, Kim JS and Oh Su J: Zwint-1 is required for spindle assembly checkpoint function and kinetochore-microtubule attachment during oocyte meiosis. Sci Rep. 5:154312015. View Article : Google Scholar : PubMed/NCBI
25	Kato T, Daigo Y, Aragaki M, Ishikawa K, Sato M and Kaji M: Overexpression of CDC20 predicts poor prognosis in primary non-small cell lung cancer patients. J Surg Oncol. 106:423–430. 2012. View Article : Google Scholar : PubMed/NCBI
26	Malumbres M: Therapeutic opportunities to control tumor cell cycles Clin Transl Oncol. 8:399–408. 2006.PubMed/NCBI