Open Access

A 10‑microRNA prognosis scoring system in esophageal squamous cell carcinoma constructed using bioinformatic methods

  • Authors:
    • Qingchao Sun
    • Liang Zong
    • Haiping Zhang
    • Yanchao Deng
    • Changming Zhang
    • Liwei Zhang
  • View Affiliations

  • Published online on: February 2, 2018     https://doi.org/10.3892/mmr.2018.8550
  • Pages: 5222-5228
  • Copyright: © Sun et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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Abstract

MicroRNA (miR) signatures may aid the diagnosis and prediction of cancer; therefore, miRs associated with the prognosis of esophageal squamous cell carcinoma (ESCC) were screened. miR‑sequencing (seq) and mRNA‑seq data from early‑stage ESCC samples were downloaded from The Cancer Genome Atlas (TCGA) database, and samples from subjects with a >6‑month survival time were assessed with Cox regression analysis for prognosis‑associated miRs. A further two miR expression datasets of ESCC samples, GSE43732 and GSE13937, were downloaded from the Gene Expression Omnibus database. Common miRs between prognosis‑associated miRs, and miRs in the GSE43732 and GSE13937, datasets were used for risk score calculations for each sample, and median risk scores were applied for the stratification of low‑ and high‑risk samples. A prognostic scoring system of signature miRs was subsequently constructed and used for survival analysis for low‑ and high‑risk samples. Differentially‑expressed genes (DEGs) corresponding to all miRs were screened and functional annotation was performed. A total of 34 prognostic miRs were screened and a scoring system was created using 10 signature miRs (hsa‑miR‑140, ‑33b, ‑34b, ‑144, ‑486, ‑214, ‑129‑2, ‑374a and ‑412). Using this system, low‑risk samples were identified to be associated with longer survival compared with high‑risk samples in the TCGA and GSE43732 datasets. Age, alcohol and tobacco use, and radiotherapy were prognostic factors for samples with different risk scores and the same clinical features. There were 168 DEGs, and the top 20 risk scores positively‑correlated and the top 20 risk scores negatively‑correlated DEGs were significantly enriched for six and 10 functional terms, respectively. ‘Tight junction’ and ‘melanogenesis’ were two significantly enriched pathways of DEGs. miR‑214, miR‑129‑2, miR‑37a and miR‑486 may predict ESCC patient survival, although further studies to validate this hypothesis are required.

References

1 

Jemal A, Siegel R, Xu J and Ward E: Cancer Statistics, 2010: CA Cancer J Clin. 60:1–300. 2010.

2 

Herszényi L and Tulassay Z: Epidemiology of gastrointestinal and liver tumors. Eur Rev Med Pharmacol Sci. 14:249–258. 2010.PubMed/NCBI

3 

Ferlay J, Soerjomataram I, Dikshit R, Eser S, Mathers C, Rebelo M, Parkin DM, Forman D and Bray F: Cancer incidenceand mortality worldwide: Sources, methods and major patternsin GLOBOCAN 2012. Int J Cancer. 136:E359–E386. 2015. View Article : Google Scholar : PubMed/NCBI

4 

Pennathur A, Gibson MK, Jobe BA and Luketich JD: Oesophageal carcinoma. Lancet. 381:400–412. 2013. View Article : Google Scholar : PubMed/NCBI

5 

Rice TW, Adelstein DJ, Zuccaro G, Falk GW and Goldblum JR: Advances in the treatment of esophageal carcinoma. Gastroenterologist. 5:278–294. 1997.PubMed/NCBI

6 

Bennett C, Vakil N, Bergman J, Harrison R, Odze R, Vieth M, Sanders S, Gay L, Pech O, Longcroft-Wheaton G, et al: Consensus statements for management of Barrett's dysplasia and early-stage esophageal adenocarcinoma, based on a Delphi process. Gastroenterology. 143:336–346. 2012. View Article : Google Scholar : PubMed/NCBI

7 

Kim T, Grobmyer SR, Smith R, Ben-David K, Ang D, Vogel SB and Hochwald SN: Esophageal cancer-the five year survivors. J Surg Oncol. 103:179–183. 2011. View Article : Google Scholar : PubMed/NCBI

8 

Christein JD, Hollinger EF and Millikan KW: Prognostic factors associated with resectable carcinoma of the esophagus. Am Surg. 68:258–263. 2002.PubMed/NCBI

9 

Wang VE, Grandis JR and Ko AH: New strategies in esophageal carcinoma: Translational insights from signaling pathways and immune checkpoints. Clin Cancer Res. 22:4283–4290. 2016. View Article : Google Scholar : PubMed/NCBI

10 

Fang YX and Gao WQ: Roles of microRNAs during prostatic tumorigenesis and tumor progression. Oncogene. 33:135–147. 2014. View Article : Google Scholar : PubMed/NCBI

11 

Li B, Xu WW, Han L, Chan KT, Tsao SW, Lee NPY, Law S, Xu LY, Li EM, Chan KW, et al: MicroRNA-377 suppresses initiation and progression of esophageal cancer by inhibiting CD133 and VEGF. Oncogene. 36:3986–4000. 2017. View Article : Google Scholar : PubMed/NCBI

12 

Xie R, Wu SN, Gao CC, Yang XZ, Wang HG, Zhang JL, Yan W and Ma TH: Prognostic value of combined and individual expression of microRNA-1290 and its target gene nuclear factor I/X in human esophageal squamous cell carcinoma. Cancer Biomark. 20:325–331. 2017. View Article : Google Scholar : PubMed/NCBI

13 

Guan S, Wang C, Chen X, Liu B, Tan B, Liu F, Wang D, Han L, Wang L, Huang X, et al: MiR-613: A novel diagnostic and prognostic biomarker for patients with esophageal squamous cell carcinoma. Tumor Biol. 37:4383–4391. 2016. View Article : Google Scholar

14 

Guo Y, Chen Z, Zhang L, Zhou F, Shi S, Feng X, Li B, Meng X, Ma X, Luo M, et al: Distinctive microRNA profiles relating to patient survival in esophageal squamous cell carcinoma. Cancer Res. 68:26–33. 2008. View Article : Google Scholar : PubMed/NCBI

15 

Hiroki E, Akahira J, Suzuki F, Nagase S, Ito K, Suzuki T, Sasano H and Yaegashi N: Changes in microRNA expression levels correlate with clinicopathological features and prognoses in endometrial serous adenocarcinomas. Cancer Sci. 101:241–249. 2010. View Article : Google Scholar : PubMed/NCBI

16 

Feber A, Xi L, Pennathur A, Gooding WE, Bandla S, Wu M, Luketich JD, Godfrey TE and Litle VR: MicroRNA prognostic signature for nodal metastases and survival in esophageal adenocarcinoma. Ann Thorac Surg. 91:1523–1530. 2011. View Article : Google Scholar : PubMed/NCBI

17 

Wang P, Wang Y, Hang B, Zou X and Mao JH: A novel gene expression-based prognostic scoring system to predict survival in gastric cancer. Oncotarget. 7:55343–55351. 2016.PubMed/NCBI

18 

Zhang CB, Zhu P, Yang P, Cai JQ, Wang ZL, Li QB, Bao ZS, Zhang W and Jiang T: Identification of high risk anaplastic gliomas by a diagnostic and prognostic signature derived from mRNA expression profiling. Oncotarget. 6:36643–36651. 2015.PubMed/NCBI

19 

Ritchie ME, Phipson B, Wu D, Hu Y, Law CW, Shi W and Smyth GK: limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 43:e472015. View Article : Google Scholar : PubMed/NCBI

20 

Huang da W, Sherman BT and Lempicki RA: Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc. 4:44–57. 2009. View Article : Google Scholar : PubMed/NCBI

21 

Wang LM, Kevans D, Mulcahy H, O'Sullivan J, Fennelly D, Hyland J, O'Donoghue D and Sheahan K: Tumor budding is a strong and reproducible prognostic marker in T3N0 colorectal cancer. Am J Surg Pathol. 33:134–141. 2009. View Article : Google Scholar : PubMed/NCBI

22 

Mao XY, Lee MJ, Zhu J, Zhu C, Law SM and Snijders AM: Genome-wide screen identifies a novel prognostic signature for breast cancer survival. Oncotarget. 8:14003–14016. 2017.PubMed/NCBI

23 

Yang H, Gu J, Wang KK, Zhang W, Xing J, Chen Z, Ajani JA and Wu X: MicroRNA expression signatures in barrett's esophagus and esophageal adenocarcinoma. Clin Cancer Res. 15:5744–5752. 2009. View Article : Google Scholar : PubMed/NCBI

24 

Yang TS, Yang XH, Wang XD, Wang YL, Zhou B and Song ZS: MiR-214 regulate gastric cancer cell proliferation, migration and invasion by targeting PTEN. Cancer Cell Int. 13:682013. View Article : Google Scholar : PubMed/NCBI

25 

Wang F, Liu M, Li X and Tang H: MiR-214 reduces cell survival and enhances cisplatin-induced cytotoxicity via down-regulation of Bcl2l2 in cervical cancer cells. FEBS Lett. 587:488–495. 2013. View Article : Google Scholar : PubMed/NCBI

26 

Zhou Y and Hong L: Prediction value of miR-483 and miR-214 in prognosis and multidrug resistance of esophageal squamous cell carcinoma. Genet Test Mol Biomarkers. 17:470–474. 2013. View Article : Google Scholar : PubMed/NCBI

27 

Phatak P, Byrnes KA, Mansour D, Liu L, Cao S, Li R, Rao JN, Turner DJ, Wang JY and Donahue JM: Overexpression of miR-214-3p in esophageal squamous cancer cells enhances sensitivity to cisplatin by targeting survivin directly and indirectly through CUG-BP1. Oncogene. 35:2087–2097. 2016. View Article : Google Scholar : PubMed/NCBI

28 

Kang M, Li Y, Liu W, Wang R, Tang A, Hao H, Liu Z and Ou H: miR-129-2 suppresses proliferation and migration of esophageal carcinoma cells through downregulation of SOX4 expression. Int J Mol Med. 32:51–58. 2013. View Article : Google Scholar : PubMed/NCBI

29 

Fesler A, Zhai H and Ju J: miR-129 as a novel therapeutic target and biomarker in gastrointestinal cancer. Onco Targets Ther. 7:1481–1485. 2014.PubMed/NCBI

30 

Võsa U, Vooder T, Kolde R, Fischer K, Välk K, Tõnisson N, Roosipuu R, Vilo J, Metspalu A and Annilo T: Identification of miR-374a as a prognostic marker for survival in patients with early-stage nonsmall cell lung cancer. Genes Chromosomes Cancer. 50:812–822. 2011. View Article : Google Scholar : PubMed/NCBI

31 

Xu X, Wang W, Su N, Zhu X, Yao J, Gao W, Hu Z and Sun Y: miR-374a promotes cell proliferation, migration and invasion by targeting SRCIN1 in gastric cancer. FEBS Lett. 589:407–413. 2015. View Article : Google Scholar : PubMed/NCBI

32 

Chen H, Ren C, Han C, Wang D, Chen Y and Fu D: Expression and prognostic value of miR-486-5p in patients with gastric adenocarcinoma. PLoS One. 10:e01193842015. View Article : Google Scholar : PubMed/NCBI

33 

Liu SG, Qin XG, Zhao BS, Qi B, Yao WJ, Wang TY, Li HC and Wu XN: Differential expression of miRNAs in esophageal cancer tissue. Oncol Lett. 5:1639–1642. 2013. View Article : Google Scholar : PubMed/NCBI

34 

Hummel R, Wang T, Watson DI, Michael MZ, van der Hoek M, Haier J and Hussey DJ: Chemotherapy-induced modification of microRNA expression in esophageal cancer. Oncol Rep. 26:1011–1017. 2011.PubMed/NCBI

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Copy and paste a formatted citation
APA
Sun, Q., Zong, L., Zhang, H., Deng, Y., Zhang, C., & Zhang, L. (2018). A 10‑microRNA prognosis scoring system in esophageal squamous cell carcinoma constructed using bioinformatic methods. Molecular Medicine Reports, 17, 5222-5228. https://doi.org/10.3892/mmr.2018.8550
MLA
Sun, Q., Zong, L., Zhang, H., Deng, Y., Zhang, C., Zhang, L."A 10‑microRNA prognosis scoring system in esophageal squamous cell carcinoma constructed using bioinformatic methods". Molecular Medicine Reports 17.4 (2018): 5222-5228.
Chicago
Sun, Q., Zong, L., Zhang, H., Deng, Y., Zhang, C., Zhang, L."A 10‑microRNA prognosis scoring system in esophageal squamous cell carcinoma constructed using bioinformatic methods". Molecular Medicine Reports 17, no. 4 (2018): 5222-5228. https://doi.org/10.3892/mmr.2018.8550