Differential expression profiles of microRNAs as potential biomarkers for the early diagnosis of lung cancer

  • Authors:
    • Yanqiu Zhang
    • Jing Sui
    • Xian Shen
    • Chengyun Li
    • Wenzhuo Yao
    • Weiwei Hong
    • Hui Peng
    • Yuepu Pu
    • Lihong Yin
    • Geyu Liang
  • View Affiliations

  • Published online on: April 28, 2017     https://doi.org/10.3892/or.2017.5612
  • Pages: 3543-3553
Metrics: Total Views: 0 (Spandidos Publications: | PMC Statistics: )
Total PDF Downloads: 0 (Spandidos Publications: | PMC Statistics: )


Abstract

Lung cancer is one of the most lethal malignancies worldwide. To reduce the high morbidity and mortality of the disease, sensitive and specific biomarkers for early detection are urgently needed. Tumor-specific microRNAs (miRNAs) seem to be potential biomarkers for the early diagnosis and treatment of cancer. In this study, the microarray of miRNAs and mRNAs on the same samples was performed and the intersection taken with The Cancer Genome Atlas (TCGA) lung cancer miRNA/RNAseq dataset. Then, miRNA-mRNA regulatory network was constructed to identify miRNA candidates associated with lung cancer through integrating gene expression and miRNA-target prediction. Furthermore, the expression levels of miRNA candidates were validated by stem-loop real-time reverse transcription PCR (qRT-PCR) in larger lung cancer population. The relationship between signature miRNAs and the risk of lung cancer were assessed by conditional logistic regression analysis. Diagnostic value of these miRNAs was determined by areas under receiver operating characteristic curves (ROC). The Affymetrix microarray analysis identified a total of 116 miRNAs and 502 mRNAs that could distinguish lung tumor tissues from adjacent non-tumor tissues, of which 70 miRNAs and 136 mRNAs were upregulated, while 46 miRNAs and 366 mRNAs were downregulated, respectively. In combination with TCGA analysis, we identified 32 miRNAs and 377 mRNAs related to lung cancer. Then, 28 key miRNAs related to 61 inter­section mRNAs were identified by miRNA-mRNA network analysis. The miRNA function analysis was indicative of that 18 upregulated and 10 downregulated miRNAs involved in signaling pathways related to Environmental Information Processing and Human Diseases. Population result showed that the expression of 7 miRNAs (miR-205-5p, miR-3917, miR-30a-3p, miR-30a-5p, miR-30c-2-3p, miR-30d-5p and miR-27a-5p) was consistent with the analysis result of microarray and TCGA. In addition, upregulation of miR-205-5p, miR-3917 and downregulation of miR-30a-3p, miR-30a-5p, miR-30c-2-3p, miR-30d-5p, miR-27a-5p increased the risk of lung cancer by conditional logistic regression analysis. The diagnostic accuracy of miR-205-5p, miR-3917, miR-27a-5p, miR-30a-3p, miR-30a-5p, miR-30c-2-3p, miR-30d-5p showed that their corresponding AUCs were 0.728, 0.661, 0.637, 0.758, 0.772, 0.734, 0.776, respectively. Therefore, there are a set of signature miRNAs which may be promising biomarkers for the early screening of high-risk populations and early diagnosis of lung cancer.

References

1 

Torre LA, Bray F, Siegel RL, Ferlay J, Lortet-Tieulent J and Jemal A: Global cancer statistics, 2012. CA Cancer J Clin. 65:87–108. 2015. View Article : Google Scholar : PubMed/NCBI

2 

Chen W, Zheng R, Baade PD, Zhang S, Zeng H, Bray F, Jemal A, Yu XQ and He J: Cancer statistics in China, 2015. CA Cancer J Clin. 66:115–132. 2016. View Article : Google Scholar : PubMed/NCBI

3 

Vrijens K, Bollati V and Nawrot TS: MicroRNAs as potential signatures of environmental exposure or effect: A systematic review. Environ Health Perspect. 123:399–411. 2015.PubMed/NCBI

4 

Zhang H, Li W, Nan F, Ren F, Wang H, Xu Y and Zhang F: MicroRNA expression profile of colon cancer stem-like cells in HT29 adenocarcinoma cell line. Biochem Biophys Res Commun. 404:273–278. 2011. View Article : Google Scholar : PubMed/NCBI

5 

Xia S, Huang CC, Le M, Dittmar R, Du M, Yuan T, Guo Y, Wang Y, Wang X, Tsai S, et al: Genomic variations in plasma cell free DNA differentiate early stage lung cancers from normal controls. Lung Cancer. 90:78–84. 2015. View Article : Google Scholar : PubMed/NCBI

6 

Pérez-Ramírez C, Cañadas-Garre M, Jiménez-Varo E, Faus-Dáder MJ and Calleja-Hernández MA: MET: A new promising biomarker in non-small-cell lung carcinoma. Pharmacogenomics. 16:631–647. 2015. View Article : Google Scholar : PubMed/NCBI

7 

Fan L, Qi H, Teng J, Su B, Chen H, Wang C and Xia Q: Identification of serum miRNAs by nano-quantum dots microarray as diagnostic biomarkers for early detection of non-small cell lung cancer. Tumour Biol. 37:7777–7784. 2016. View Article : Google Scholar : PubMed/NCBI

8 

Geng Q, Fan T, Zhang B, Wang W, Xu Y and Hu H: Five microRNAs in plasma as novel biomarkers for screening of early-stage non-small cell lung cancer. Respir Res. 15:1492014. View Article : Google Scholar : PubMed/NCBI

9 

Inamura K and Ishikawa Y: MicroRNA in lung cancer: Novel biomarkers and potential tools for treatment. J Clin Med. 5:52016. View Article : Google Scholar :

10 

Kim JO, Gazala S, Razzak R, Guo L, Ghosh S, Roa WH and Bédard EL: Non-small cell lung cancer detection using microRNA expression profiling of bronchoalveolar lavage fluid and sputum. Anticancer Res. 35:1873–1880. 2015.PubMed/NCBI

11 

Wang Y, Zhang X, Liu L, Li H, Yu J, Wang C and Ren X: Clinical implication of microRNA for lung cancer. Cancer Biother Radiopharm. 28:261–267. 2013. View Article : Google Scholar : PubMed/NCBI

12 

Solomides CC, Evans BJ, Navenot JM, Vadigepalli R, Peiper SC and Wang ZX: MicroRNA profiling in lung cancer reveals new molecular markers for diagnosis. Acta Cytol. 56:645–654. 2012. View Article : Google Scholar : PubMed/NCBI

13 

Singh DK, Bose S and Kumar S: Role of microRNA in regulating cell signaling pathways, cell cycle, and apoptosis in non-small cell lung cancer. Curr Mol Med. 16:474–486. 2016. View Article : Google Scholar

14 

Razzak R, Bédard EL, Kim JO, Gazala S, Guo L, Ghosh S, Joy A, Nijjar T, Wong E and Roa WH: MicroRNA expression profiling of sputum for the detection of early and locally advanced non-small-cell lung cancer: A prospective case-control study. Curr Oncol. 23:e86–e94. 2016. View Article : Google Scholar : PubMed/NCBI

15 

Pu Q, Huang Y, Lu Y, Peng Y, Zhang J, Feng G, Wang C, Liu L and Dai Y: Tissue-specific and plasma microRNA profiles could be promising biomarkers of histological classification and TNM stage in non-small cell lung cancer. Thorac Cancer. 7:348–354. 2016. View Article : Google Scholar : PubMed/NCBI

16 

Krutakova M, Sarlinova M, Matakova T, Dzian A, Hamzik J, Pec M, Javorkova S and Halasova E: The role of dysregulated microRNA expression in lung cancer. Adv Exp Med Biol. 911:1–8. 2016. View Article : Google Scholar : PubMed/NCBI

17 

Li JH, Liu S, Zhou H, Qu LH and Yang JH: starBase v2.0: Decoding miRNA-ceRNA, miRNA-ncRNA and protein-RNA interaction networks from large-scale CLIP-Seq data. Nucleic Acids Res. 42:D92–D97. 2014. View Article : Google Scholar : PubMed/NCBI

18 

Hsu SD, Tseng YT, Shrestha S, Lin YL, Khaleel A, Chou CH, Chu CF, Huang HY, Lin CM, Ho SY, et al: miRTarBase update 2014: An information resource for experimentally validated miRNA-target interactions. Nucleic Acids Res. 42:D78–D85. 2014. View Article : Google Scholar : PubMed/NCBI

19 

Li CY, Liang GY, Yao WZ, Sui J, Shen X, Zhang YQ, Peng H, Hong WW, Ye YC, Zhang ZY, et al: Integrated analysis of long non-coding RNA competing interactions reveals the potential role in progression of human gastric cancer. Int J Oncol. 48:1965–1976. 2016.PubMed/NCBI

20 

Yang YL, Xu LP, Zhuo FL and Wang TY: Prognostic value of microRNA-10b overexpression in peripheral blood mononuclear cells of nonsmall-cell lung cancer patients. Tumour Biol. 36:7069–7075. 2015. View Article : Google Scholar : PubMed/NCBI

21 

Xu C, Zheng Y, Lian D, Ye S, Yang J and Zeng Z: Analysis of microRNA expression profile identifies novel biomarkers for non-small cell lung cancer. Tumori. 101:104–110. 2015. View Article : Google Scholar : PubMed/NCBI

22 

Wiwanitkit V: MicroRNA assays for diagnosis lung cancer biopsy. J Thorac Oncol. 10:e52–53. 2015. View Article : Google Scholar : PubMed/NCBI

23 

Wang P, Yang D, Zhang H, Wei X, Ma T, Cheng Z, Hong Q, Hu J, Zhuo H, Song Y, et al: Early detection of lung cancer in serum by a panel of microRNA biomarkers. Clin Lung Cancer. 16:313–319 e1. 2015. View Article : Google Scholar : PubMed/NCBI

24 

Chen X, Hu Z, Wang W, Ba Y, Ma L, Zhang C, Wang C, Ren Z, Zhao Y, Wu S, et al: Identification of ten serum microRNAs from a genome-wide serum microRNA expression profile as novel noninvasive biomarkers for nonsmall cell lung cancer diagnosis. Int J Cancer. 130:1620–1628. 2012. View Article : Google Scholar : PubMed/NCBI

25 

Yin QW, Sun XF, Yang GT, Li XB, Wu MS and Zhao J: Increased expression of microRNA-150 is associated with poor prognosis in non-small cell lung cancer. Int J Clin Exp Pathol. 8:842–846. 2015.PubMed/NCBI

26 

Wu C, Cao Y, He Z, He J, Hu C, Duan H and Jiang J: Serum levels of miR-19b and miR-146a as prognostic biomarkers for non-small cell lung cancer. Tohoku J Exp Med. 232:85–95. 2014. View Article : Google Scholar : PubMed/NCBI

27 

Molina-Pinelo S, Pastor MD, Suarez R, Romero-Romero B, González De la Peña M, Salinas A, García-Carbonero R, De Miguel MJ, Rodríguez-Panadero F, Carnero A, et al: MicroRNA clusters: Dysregulation in lung adenocarcinoma and COPD. Eur Respir J. 43:1740–1749. 2014. View Article : Google Scholar : PubMed/NCBI

28 

Yuan Y, Zheng S, Li Q, Xiang X, Gao T, Ran P, Sun L, Huang Q, Xie F, Du J, et al: Overexpression of miR-30a in lung adenocarcinoma A549 cell line inhibits migration and invasion via targeting EYA2. Acta Biochim Biophys Sin (Shanghai). 48:220–228. 2016. View Article : Google Scholar : PubMed/NCBI

29 

Chen D, Guo W, Qiu Z, Wang Q, Li Y, Liang L, Liu L, Huang S, Zhao Y and He X: MicroRNA-30d-5p inhibits tumour cell proliferation and motility by directly targeting CCNE2 in non-small cell lung cancer. Cancer Lett. 362:208–217. 2015. View Article : Google Scholar : PubMed/NCBI

30 

Hu J, Ni S, Cao Y, Zhang T, Wu T, Yin X, Lang Y and Lu H: The angiogenic effect of microRNA-21 targeting TIMP3 through the regulation of MMP2 and MMP9. PLoS One. 11:e01495372016. View Article : Google Scholar : PubMed/NCBI

31 

Jiang M, Zhang P, Hu G, Xiao Z, Xu F, Zhong T, Huang F, Kuang H and Zhang W: Relative expressions of miR-205-5p, miR-205-3p, and miR-21 in tissues and serum of non-small cell lung cancer patients. Mol Cell Biochem. 383:67–75. 2013. View Article : Google Scholar : PubMed/NCBI

32 

Wang F, Lu J, Peng X, Wang J, Liu X, Chen X, Jiang Y, Li X and Zhang B: Integrated analysis of microRNA regulatory network in nasopharyngeal carcinoma with deep sequencing. J Exp Clin Cancer Res. 35:172016.doi: 10.1186/s13046-016-0292-4. View Article : Google Scholar : PubMed/NCBI

33 

Stoecklin-Wasmer C, Guarnieri P, Celenti R, Demmer RT, Kebschull M and Papapanou PN: MicroRNAs and their target genes in gingival tissues. J Dent Res. 91:934–940. 2012. View Article : Google Scholar : PubMed/NCBI

34 

Wang W, Lin H, Zhou L, Zhu Q, Gao S, Xie H, Liu Z, Xu Z, Wei J, Huang X, et al: MicroRNA-30a-3p inhibits tumor proliferation, invasiveness and metastasis and is downregulated in hepatocellular carcinoma. Eur J Surg Oncol. 40:1586–1594. 2014. View Article : Google Scholar : PubMed/NCBI

35 

Moch H and Lukamowicz-Rajska M: miR-30c-2-3p and miR-30a-3p: New pieces of the jigsaw puzzle in HIF2α regulation. Cancer Discov. 4:22–24. 2014. View Article : Google Scholar : PubMed/NCBI

36 

Li W, Liu C, Zhao C, Zhai L and Lv S: Downregulation of β3 integrin by miR-30a-5p modulates cell adhesion and invasion by interrupting Erk/Ets-1 network in triple-negative breast cancer. Int J Oncol. 48:1155–1164. 2016.PubMed/NCBI

37 

Li WF, Dai H, Ou Q, Zuo GQ and Liu CA: Overexpression of microRNA-30a-5p inhibits liver cancer cell proliferation and induces apoptosis by targeting MTDH/PTEN/AKT pathway. Tumour Biol. 37:5885–5895. 2016. View Article : Google Scholar : PubMed/NCBI

Related Articles

Journal Cover

June 2017
Volume 37 Issue 6

Print ISSN: 1021-335X
Online ISSN:1791-2431

Sign up for eToc alerts

Recommend to Library

Copy and paste a formatted citation
APA
Zhang, Y., Sui, J., Shen, X., Li, C., Yao, W., Hong, W. ... Liang, G. (2017). Differential expression profiles of microRNAs as potential biomarkers for the early diagnosis of lung cancer. Oncology Reports, 37, 3543-3553. https://doi.org/10.3892/or.2017.5612
MLA
Zhang, Y., Sui, J., Shen, X., Li, C., Yao, W., Hong, W., Peng, H., Pu, Y., Yin, L., Liang, G."Differential expression profiles of microRNAs as potential biomarkers for the early diagnosis of lung cancer". Oncology Reports 37.6 (2017): 3543-3553.
Chicago
Zhang, Y., Sui, J., Shen, X., Li, C., Yao, W., Hong, W., Peng, H., Pu, Y., Yin, L., Liang, G."Differential expression profiles of microRNAs as potential biomarkers for the early diagnosis of lung cancer". Oncology Reports 37, no. 6 (2017): 3543-3553. https://doi.org/10.3892/or.2017.5612