Open Access

Bioinformatics identification of lncRNA biomarkers associated with the progression of esophageal squamous cell carcinoma

  • Authors:
    • Jun Yu
    • Xiaoliu Wu
    • Kaidan Huang
    • Ming Zhu
    • Xiaomei Zhang
    • Yuanying Zhang
    • Senqing Chen
    • Xinyu Xu
    • Qin Zhang
  • View Affiliations

  • Published online on: May 2, 2019     https://doi.org/10.3892/mmr.2019.10213
  • Pages: 5309-5320
  • Copyright: © Yu et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

Metrics: Total Views: 0 (Spandidos Publications: | PMC Statistics: )
Total PDF Downloads: 0 (Spandidos Publications: | PMC Statistics: )


Abstract

The poor outcome of patients with esophageal squamous cell carcinoma (ESCC) highlights the importance of the identification of novel effective prognostic biomarkers. Long non‑coding RNAs (lncRNAs) serve regulatory roles in various types of cancer. The aim of the present study was to investigate the lncRNA expression profile in ESCC and to identify lncRNAs associated with the prognosis of ESCC by performing comprehensive bioinformatics analyses. The RNA‑sequencing (Seq) expression dataset GSE53625 generated from ESCC samples was used as a training dataset. Additional RNA‑Seq datasets relative to ESCC samples were downloaded from The Cancer Genome Atlas and used as a validation dataset. Data were screened using the limma package, and differentially expressed lncRNAs between early‑ and late‑stage ESCC were identified. A random forest algorithm was used to select the optimal lncRNA biomarkers, which were then analyzed using the support vector machine (SVM) algorithm with R software. The identified lncRNA biomarkers were examined in the validation dataset by bidirectional hierarchical clustering and using an SVM classifier. Subsequently, univariate and multivariate Cox regression analyses were performed to analyze the potential ability lncRNAs to predict the survival rate of patients with ESCC. By examining the training group, 259 deregulated lncRNAs between early‑ and advanced‑stage ESCC were identified. Further bioinformatics analyses identified a nine‑lncRNA signature, including AC098973, AL133493, RP11‑51M24, RP11‑317N8, RP11‑834C11, RP11‑69C17, LINC00471, LINC01193 and RP1‑124C. This nine‑lncRNA signature was used to predict the tumor stage and patient survival rate with high reliability and accuracy in the training and validation datasets. Furthermore, these nine lncRNA biomarkers were primarily involved in regulating the cell cycle and DNA replication, and these processes were previously identified to be associated with the progression of ESCC. The identified nine‑lncRNA signature was identified to be associated with the tumor stage, and could be used as predictor of the survival rate of patients with ESCC.

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 

van Hagen P, Hulshof M, van Lanschot J, Steyerberg EW, van Berge Henegouwen MI, Wijnhoven BP, Richel DJ, Nieuwenhuijzen GA, Hospers GA, Bonenkamp JJ, et al: Preoperative chemoradiotherapy for esophageal or junctional cancer. N Engl J Med. 366:2074–2084. 2012. View Article : Google Scholar : PubMed/NCBI

3 

Matsushima K, Isomoto H, Yamaguchi N, Inoue N, Machida H, Nakayama T, Hayashi T, Kunizaki M, Hidaka S, Nagayasu T, et al: MiRNA-205 modulates cellular invasion and migration via regulating zinc finger E-box binding homeobox 2 expression in esophageal squamous cell carcinoma cells. J Transl Med. 9:302011. View Article : Google Scholar : PubMed/NCBI

4 

Ohashi S, Miyamoto S, Kikuchi O, Goto T, Amanuma Y and Muto M: Recent advances from basic and clinical studies of esophageal squamous cell carcinoma. Gastroenterology. 149:1700–1715. 2015. View Article : Google Scholar : PubMed/NCBI

5 

Hirajima S, Komatsu S, Ichikawa D, Takeshita H, Konishi H, Shiozaki A, Morimura R, Tsujiura M, Nagata H, Kawaguchi T, et al: Clinical impact of circulating miR-18a in plasma of patients with oesophageal squamous cell carcinoma. Br J Cancer. 108:1822–1829. 2013. View Article : Google Scholar : PubMed/NCBI

6 

Kosugi S, Nishimaki T, Kanda T, Nakagawa S, Ohashi M and Hatakeyama K: Clinical significance of serum carcinoembryonic antigen, carbohydrate antigen 19-9, and squamous cell carcinoma antigen levels in esophageal cancer patients. World J Surg. 28:680–685. 2004. View Article : Google Scholar : PubMed/NCBI

7 

Jones PA and Baylin SB: The fundamental role of epigenetic events in cancer. Nat Rev Genet. 3:415–428. 2002. View Article : Google Scholar : PubMed/NCBI

8 

Evans JR, Feng FY and Chinnaiyan AM: The bright side of dark matter: lncRNAs in cancer. J Clin Invest. 126:2775–2782. 2016. View Article : Google Scholar : PubMed/NCBI

9 

Schmitt AM and Chang HY: Long noncoding RNAs in cancer pathways. Cancer Cell. 29:452–463. 2016. View Article : Google Scholar : PubMed/NCBI

10 

Clark MB, Johnston RL, Inostroza-Ponta M, Fox AH, Fortini E, Moscato P, Dinger ME and Mattick JS: Genome-wide analysis of long noncoding RNA stability. Genome Res. 22:885–898. 2012. View Article : Google Scholar : PubMed/NCBI

11 

Rinn JL and Chang HY: Genome regulation by long noncoding RNAs. Annu Rev Biochem. 81:145–166. 2012. View Article : Google Scholar : PubMed/NCBI

12 

ENCODE Project Consortium, ; Birney E, Stamatoyannopoulos JA, Dutta A, Guigó R, Gingeras TR, Margulies EH, Weng Z, Snyder M, Dermitzakis ET, et al: Identification and analysis of functional elements in 1% of the human genome by the ENCODE pilot project. Nature. 447:799–816. 2007. View Article : Google Scholar : PubMed/NCBI

13 

Nagano T and Fraser P: No-nonsense functions for long noncoding RNAs. Cell. 145:178–181. 2011. View Article : Google Scholar : PubMed/NCBI

14 

Yoon JH, Abdelmohsen K, Srikantan S, Yang X, Martindale JL, De S, Huarte M, Zhan M, Becker KG and Gorospe M: LincRNA-p21 suppresses target mRNA translation. Mol Cell. 47:648–655. 2012. View Article : Google Scholar : PubMed/NCBI

15 

Guttman M and Rinn JL: Modular regulatory principles of large non-coding RNAs. Nature. 482:339–346. 2012. View Article : Google Scholar : PubMed/NCBI

16 

Gupta RA, Shah N, Wang KC, Kim J, Horlings HM, Wong DJ, Tsai MC, Hung T, Argani P, Rinn JL, et al: Long non-coding RNA HOTAIR reprograms chromatin state to promote cancer metastasis. Nature. 464:1071–1076. 2010. View Article : Google Scholar : PubMed/NCBI

17 

Yu W, Gius D, Onyango P, Muldoon-Jacobs K, Karp J, Feinberg AP and Cui H: Epigenetic silencing of tumour suppressor gene p15 by its antisense RNA. Nature. 451:202–206. 2008. View Article : Google Scholar : PubMed/NCBI

18 

Ren S, Wang F, Shen J, Sun Y, Xu W, Lu J, Wei M, Xu C, Wu C, Zhang Z, et al: Long non-coding RNA metastasis associated in lung adenocarcinoma transcript 1 derived miniRNA as a novel plasma-based biomarker for diagnosing prostate cancer. Eur J Cancer. 49:2949–2959. 2013. View Article : Google Scholar : PubMed/NCBI

19 

Ji P, Diederichs S, Wang W, Böing S, Metzger R, Schneider PM, Tidow N, Brandt B, Buerger H, Bulk E, et al: MALAT-1, a novel noncoding RNA, and thymosin beta4 predict metastasis and survival in early-stage non-small cell lung cancer. Oncogene. 22:8031–8041. 2003. View Article : Google Scholar : PubMed/NCBI

20 

Li CQ, Huang GW, Wu ZY, Xu YJ, Li XC, Xue YJ, Zhu Y, Zhao JM, Li M, Zhang J, et al: Integrative analyses of transcriptome sequencing identify novel functional lncRNAs in esophageal squamous cell carcinoma. Oncogenesis. 6:e2972017. View Article : Google Scholar : PubMed/NCBI

21 

Cao W, Wu W, Shi F, Chen X, Wu L, Yang K, Tian F, Zhu M, Chen G, Wang W, et al: Integrated analysis of long noncoding RNA and coding RNA expression in esophageal squamous cell carcinoma. Int J Genomics. 2013:4805342013. View Article : Google Scholar : PubMed/NCBI

22 

Pan Z, Mao W, Bao Y, Zhang M, Su X and Xu X: The long noncoding RNA CASC9 regulates migration and invasion in esophageal cancer. Cancer Med. 5:2442–2447. 2016. View Article : Google Scholar : PubMed/NCBI

23 

Yao J, Huang JX, Lin M, Wu ZD, Yu H, Wang PC, Ye J, Chen P, Wu J and Zhao GJ: Microarray expression profile analysis of aberrant long non-coding RNAs in esophageal squamous cell carcinoma. Int J Oncol. 48:2543–2557. 2016. View Article : Google Scholar : PubMed/NCBI

24 

Wang W, Wei C, Li P, Wang L, Li W, Chen K, Zhang J, Zhang W and Jiang G: Integrative analysis of mRNA and lncRNA profiles identified pathogenetic lncRNAs in esophageal squamous cell carcinoma. Gene. 661:169–175. 2018. View Article : Google Scholar : PubMed/NCBI

25 

Mathé EA, Nguyen GH, Bowman ED, Zhao Y, Budhu A, Schetter AJ, Braun R, Reimers M, Kumamoto K, Hughes D, et al: MicroRNA expression in squamous cell carcinoma and adenocarcinoma of the esophagus: Associations with survival. Clin Cancer Res. 15:6192–6200. 2009. View Article : Google Scholar : PubMed/NCBI

26 

Clough E and Barrett T: The gene expression omnibus database. Methods Mol Biol. 1418:93–110. 2016. View Article : Google Scholar : PubMed/NCBI

27 

Tomczak K, Czerwinska P and Wiznerowicz M: The cancer genome atlas (TCGA): An immeasurable source of knowledge. Contemp Oncol (Pozn). 19:A68–A77. 2015.PubMed/NCBI

28 

Huang Y, Guo W, Shi S and He J: Evaluation of the 7(th) edition of the UICC-AJCC tumor, node, metastasis classification for esophageal cancer in a Chinese cohort. J Thorac Dis. 8:1672–1680. 2016. View Article : Google Scholar : PubMed/NCBI

29 

Li J, Chen Z, Tian L, Zhou C, He MY, Gao Y, Wang S, Zhou F, Shi S, Feng X, et al: LncRNA profile study reveals a three-lncRNA signature associated with the survival of patients with oesophageal squamous cell carcinoma. Gut. 63:1700–1710. 2014. View Article : Google Scholar : PubMed/NCBI

30 

Moon TK: The expectation maximization algorithm. IEEE Signal Process Mag. 13:47–60. 1996. View Article : Google Scholar

31 

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

32 

Jiao S and Zhang S: On correcting the overestimation of the permutation-based false discovery rate estimator. Bioinformatics. 24:1655–1661. 2008. View Article : Google Scholar : PubMed/NCBI

33 

Eisen MB, Spellman PT, Brown PO and Botstein D: Cluster analysis and display of genome-wide expression patterns. Proc Natl Acad Sci USA. 95:14863–14868. 1998. View Article : Google Scholar : PubMed/NCBI

34 

Wang L, Cao C, Ma Q, Zeng Q, Wang H, Cheng Z, Zhu G, Qi J, Ma H, Nian H and Wang Y: RNA-seq analyses of multiple meristems of soybean: Novel and alternative transcripts, evolutionary and functional implications. BMC Plant Biol. 14:1692014. View Article : Google Scholar : PubMed/NCBI

35 

Zapf A, Brunner E and Konietschke F: A wild bootstrap approach for the selection of biomarkers in early diagnostic trials. BMC Med Res Methodol. 15:432015. View Article : Google Scholar : PubMed/NCBI

36 

Cutler A and Stevens JR: Random forests for microarrays. Methods Enzymol. 411:422–432. 2006. View Article : Google Scholar : PubMed/NCBI

37 

Wang Q and Liu X: Screening of feature genes in distinguishing different types of breast cancer using support vector machine. OncoTargets Ther. 8:2311–2317. 2015.

38 

Fushiki T: Estimation of prediction error by using K-fold cross-validation. Statistics Computing. 21:137–146. 2011. View Article : Google Scholar

39 

Langfelder P and Horvath S: Fast R functions for robust correlations and hierarchical clustering. J Stat Softw. 46(pii): i112012.PubMed/NCBI

40 

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. Nucleic Acids Res 43 (Database Issue). D447–D452. 2015. View Article : Google Scholar

41 

Kanehisa M and Goto S: KEGG: Kyoto encyclopedia of genes and genomes. Nucleic Acids Res. 28:27–30. 2000. View Article : Google Scholar : PubMed/NCBI

42 

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

43 

Enzinger PC and Mayer RJ: Esophageal cancer. N Engl J Med. 349:2241–2252. 2003. View Article : Google Scholar : PubMed/NCBI

44 

Dai L, Li JL, Liang XQ, Li L, Feng Y, Liu HZ, Wei WE, Ning SF and Zhang LT: Flowers of Camellia nitidissima cause growth inhibition, cell-cycle dysregulation and apoptosis in a human esophageal squamous cell carcinoma cell line. Mol Med Rep. 14:1117–1122. 2016. View Article : Google Scholar : PubMed/NCBI

45 

Dadkhah E, Naseh H, Farshchian M, Memar B, Sankian M, Bagheri R, Forghanifard MM, Montazer M, Kazemi Noughabi M, Hashemi M and Abbaszadegan MR: A cancer-array approach elucidates the immune escape mechanism and defects in the DNA repair system in esophageal squamous cell carcinoma. Arch Iran Med. 16:463–470. 2013.PubMed/NCBI

46 

Yang F, Zhang L, Huo XS, Yuan JH, Xu D, Yuan SX, Zhu N, Zhou WP, Yang GS, Wang YZ, et al: Long noncoding RNA high expression in hepatocellular carcinoma facilitates tumor growth through enhancer of zeste homolog 2 in humans. Hepatology. 54:1679–1689. 2011. View Article : Google Scholar : PubMed/NCBI

47 

Kogo R, Shimamura T, Mimori K, Kawahara K, Imoto S, Sudo T, Tanaka F, Shibata K, Suzuki A, Komune S, et al: Long non-coding RNA HOTAIR regulates Polycomb-dependent chromatin modification and is associated with poor prognosis in colorectal cancers. Cancer Res. 71:6320–6326. 2011. View Article : Google Scholar : PubMed/NCBI

48 

Ito T, Shimada Y, Kan T, David S, Cheng Y, Mori Y, Agarwal R, Paun B, Jin Z, Olaru A, et al: Pituitary tumor-transforming 1 increases cell motility and promotes lymph node metastasis in esophageal squamous cell carcinoma. Cancer Res. 68:3214–3224. 2008. View Article : Google Scholar : PubMed/NCBI

49 

Ma S, Bao JYJ, Kwan PS, Chan YP, Tong CM, Fu L, Zhang N, Tong AHY, Qin YR, Tsao SW, et al: Identification of PTK6, via RNA sequencing analysis, as a suppressor of esophageal squamous cell carcinoma. Gastroenterology. 143:675–686.e12. 2012. View Article : Google Scholar : PubMed/NCBI

50 

Sawada G, Niida A, Uchi R, Hirata H, Shimamura T, Suzuki Y, Shiraishi Y, Chiba K, Imoto S, Takahashi Y, et al: Genomic landscape of esophageal squamous cell carcinoma in a Japanese population. Gastroenterology. 150:1171–1182. 2016. View Article : Google Scholar : PubMed/NCBI

Related Articles

Journal Cover

June 2019
Volume 19 Issue 6

Print ISSN: 1791-2997
Online ISSN:1791-3004

Sign up for eToc alerts

Recommend to Library

Copy and paste a formatted citation
APA
Yu, J., Wu, X., Huang, K., Zhu, M., Zhang, X., Zhang, Y. ... Zhang, Q. (2019). Bioinformatics identification of lncRNA biomarkers associated with the progression of esophageal squamous cell carcinoma. Molecular Medicine Reports, 19, 5309-5320. https://doi.org/10.3892/mmr.2019.10213
MLA
Yu, J., Wu, X., Huang, K., Zhu, M., Zhang, X., Zhang, Y., Chen, S., Xu, X., Zhang, Q."Bioinformatics identification of lncRNA biomarkers associated with the progression of esophageal squamous cell carcinoma". Molecular Medicine Reports 19.6 (2019): 5309-5320.
Chicago
Yu, J., Wu, X., Huang, K., Zhu, M., Zhang, X., Zhang, Y., Chen, S., Xu, X., Zhang, Q."Bioinformatics identification of lncRNA biomarkers associated with the progression of esophageal squamous cell carcinoma". Molecular Medicine Reports 19, no. 6 (2019): 5309-5320. https://doi.org/10.3892/mmr.2019.10213