Tumor Biology

, Volume 35, Issue 11, pp 10789–10798 | Cite as

Clinical significance of microRNA expressions in diagnosing uterine cancer and predicting lymph node metastasis

  • Changlong Hou
  • Guosheng Tan
  • Shiting Feng
Research Article


Recently, accumulating lines of evidence have demonstrated the association between microRNA (miRNAs) expression and uterine cancer, indicating that they may serve as promising novel biomarkers for uterine cancer. Therefore, we conducted this study to systematically evaluate the diagnostic accuracy of miRNAs in discriminating the uterine cancer patients from controls and further to determine their diagnostic values in lymph node metastasis (LNM) prediction. The pooled sensitivity, specificity, and other parameters, together with summary receiver operating characteristic (SROC) curve were used to assess the overall test performance. All statistical analyses were conducted using STATA 12.0 software. A total of nine articles were included in this meta-analysis. As for the accuracy of miRNAs in differentiating uterine cancer from controls, the pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and area under curve (AUC) were 0.84, 0.83, 4.8, 0.19, 25, and 0.90, respectively. As for the diagnostic accuracy of miRNAs in differentiating patients with LNM from those without LNM, the pooled sensitivity, specificity, PLR, NLR, DOR, and AUC were 0.75, 0.78, 3.5, 0.32, 011, and 0.83, respectively. In addition, subgroup analyses based on miRNA profiles suggested that multiple-miRNA assay displayed much better accuracy than single-miRNA assay, with an excellent AUC of 0.98 (92 % sensitivity and 96 % specificity). The high accuracy of multiple-miRNA assay, together with the application of miRNAs in LNM prediction, suggested that miRNAs may serve as non-invasive diagnostic markers of uterine cancer and further improve the comprehensive management of patients with uterine cancer. However, further larger studies are needed to confirm our findings.


MicroRNAs Uterine cancer Lymph node metastasis Diagnosis Accuracy Meta-analysis 


Conflicts of interest


Supplementary material

13277_2014_2382_MOESM1_ESM.eps (998 kb)
Figure S1 Meta-regression for uterine cancer vs. control group (EPS 997 kb)
13277_2014_2382_MOESM2_ESM.eps (1.1 mb)
Figure S2 Sensitivity analysis for uterine cancer vs. control group: (a) graphical depiction of residual-based goodness-of-fit, (b) bivariate normality, (c) influence, and (d) outlier detection analyses (EPS 1152 kb)
13277_2014_2382_MOESM3_ESM.eps (1 mb)
Figure S3 Sensitivity analysis for LNM vs. non-LNM group: (a) graphical depiction of residual-based goodness-of-fit, (b) bivariate normality, (c) influence, and (d) outlier detection analyses (EPS 1024 kb)


  1. 1.
    Jemal A, Siegel R, Ward E, Hao Y, Xu J, Murray T, et al. Cancer statistics, 2008. CA Cancer J Clin. 2008;58:71–96.PubMedCrossRefGoogle Scholar
  2. 2.
    Reshmi G, Pillai MR. Beyond HPV: oncomirs as new players in cervical cancer. FEBS Lett. 2008;582:4113–6.PubMedCrossRefGoogle Scholar
  3. 3.
    Jemal A, Bray F, Center MM, Ferlay J, Ward E, Forman D. Global cancer statistics. CA Cancer J Clin. 2011;61:69–90.PubMedCrossRefGoogle Scholar
  4. 4.
    Hu X, Schwarz JK, Lewis Jr JS, Huettner PC, Rader JS, Deasy JO, et al. A microRNA expression signature for cervical cancer prognosis. Cancer Res. 2010;70:1441–8.PubMedCentralPubMedCrossRefGoogle Scholar
  5. 5.
    Gersell DJ, Mazoujian G, Mutch DG, Rudloff MA. Small-cell undifferentiated carcinoma of the cervix. A clinicopathologic, ultrastructural, and immunocytochemical study of 15 cases. Am J Surg Pathol. 1988;12:684–98.PubMedCrossRefGoogle Scholar
  6. 6.
    Van Nagell Jr JR, Powell DE, Gallion HH, Elliott DG, Donaldson ES, Carpenter AE, et al. Small cell carcinoma of the uterine cervix. Cancer. 1988;62:1586–93.PubMedCrossRefGoogle Scholar
  7. 7.
    Sevin BU, Method MW, Nadji M, Lu Y, Averette HA. Efficacy of radical hysterectomy as treatment for patients with small cell carcinoma of the cervix. Cancer. 1996;77:1489–93.PubMedCrossRefGoogle Scholar
  8. 8.
    Neoadjuvant chemotherapy for locally advanced cervical cancer: a systematic review and meta-analysis of individual patient data from 21 randomised trials. Eur J Cancer 2003;39:2470-2486.Google Scholar
  9. 9.
    Sakuragi N. Up-to-date management of lymph node metastasis and the role of tailored lymphadenectomy in cervical cancer. Int J Clin Oncol. 2007;12:165–75.PubMedCrossRefGoogle Scholar
  10. 10.
    Sturgeon CM, Duffy MJ, Hofmann BR, Lamerz R, Fritsche HA, Gaarenstroom K, et al. National Academy of Clinical Biochemistry Laboratory Medicine Practice Guidelines for use of tumor markers in liver, bladder, cervical, and gastric cancers. Clin Chem. 2010;56:e1–e48.PubMedCrossRefGoogle Scholar
  11. 11.
    Bansal N, Yendluri V, Wenham RM. The molecular biology of endometrial cancers and the implications for pathogenesis, classification, and targeted therapies. Cancer control J Moffitt Cancer Cent. 2009;16:8–13.Google Scholar
  12. 12.
    Chen J, Yao D, Li Y, Chen H, He C, Ding N, et al. Serum microRNA expression levels can predict lymph node metastasis in patients with early-stage cervical squamous cell carcinoma. Int J Mol Med. 2013;32:557–67.PubMedCentralPubMedGoogle Scholar
  13. 13.
    Ogino I, Nakayama H, Okamoto N, Kitamura T, Inoue T. The role of pretreatment squamous cell carcinoma antigen level in locally advanced squamous cell carcinoma of the uterine cervix treated by radiotherapy. Int J Gynecol Cancer Off J Int Gynecol Cancer Soc. 2006;16:1094–100.CrossRefGoogle Scholar
  14. 14.
    van de Lande J, Davelaar EM, von Mensdorff-Pouilly S, Water TJ, Berkhof J, van Baal WM, et al. SCC-Ag, lymph node metastases and sentinel node procedure in early stage squamous cell cervical cancer. Gynecol Oncol. 2009;112:119–25.PubMedCrossRefGoogle Scholar
  15. 15.
    Nakamura K, Okumura Y, Kodama J, Hongo A, Kanazawa S, Hiramatsu Y. The predictive value of measurement of SUVmax and SCC-antigen in patients with pretreatment of primary squamous cell carcinoma of cervix. Gynecol Oncol. 2010;119:81–6.PubMedCrossRefGoogle Scholar
  16. 16.
    Gaarenstroom KN, Kenter GG, Bonfrer JM, Korse CM, Van de Vijver MJ, Fleuren GJ, et al. Can initial serum cyfra 21-1, SCC antigen, and TPA levels in squamous cell cervical cancer predict lymph node metastases or prognosis? Gynecol Oncol. 2000;77:164–70.PubMedCrossRefGoogle Scholar
  17. 17.
    Juang CM, Wang PH, Yen MS, Lai CR, Ng HT, Yuan CC. Application of tumor markers CEA, TPA, and SCC-Ag in patients with low-risk FIGO stage IB and IIA squamous cell carcinoma of the uterine cervix. Gynecol Oncol. 2000;76:103–6.PubMedCrossRefGoogle Scholar
  18. 18.
    Cummins JM, Velculescu VE. Implications of micro-RNA profiling for cancer diagnosis. Oncogene. 2006;25:6220–7.PubMedCrossRefGoogle Scholar
  19. 19.
    Guo H, Ingolia NT, Weissman JS, Bartel DP. Mammalian microRNAs predominantly act to decrease target mRNA levels. Nature. 2010;466:835–40.PubMedCentralPubMedCrossRefGoogle Scholar
  20. 20.
    Farazi TA, Spitzer JI, Morozov P, Tuschl T. MiRNAs in human cancer. J Pathol. 2011;223:102–15.PubMedCentralPubMedCrossRefGoogle Scholar
  21. 21.
    He L, Thomson JM, Hemann MT, Hernando-Monge E, Mu D, Goodson S, et al. A microRNA polycistron as a potential human oncogene. Nature. 2005;435:828–33.PubMedCrossRefGoogle Scholar
  22. 22.
    Voorhoeve PM, le Sage C, Schrier M, Gillis AJ, Stoop H, Nagel R, et al. A genetic screen implicates miRNA-372 and miRNA-373 as oncogenes in testicular germ cell tumors. Cell. 2006;124:1169–81.PubMedCrossRefGoogle Scholar
  23. 23.
    Hede K. Small RNAs are raising big expectations. J Natl Cancer Inst. 2009;101:840–1.PubMedCrossRefGoogle Scholar
  24. 24.
    Kurman RJ, McConnell TG. Precursors of endometrial and ovarian carcinoma. Virchows Arch Int J Pathol. 2010;456:1–12.CrossRefGoogle Scholar
  25. 25.
    Yan LX, Huang XF, Shao Q, Huang MY, Deng L, Wu QL, et al. MicroRNA miR-21 overexpression in human breast cancer is associated with advanced clinical stage, lymph node metastasis and patient poor prognosis. RNA. 2008;14:2348–60.PubMedCentralPubMedCrossRefGoogle Scholar
  26. 26.
    Yu SL, Chen HY, Chang GC, Chen CY, Chen HW, Singh S, et al. MicroRNA signature predicts survival and relapse in lung cancer. Cancer Cell. 2008;13:48–57.PubMedCrossRefGoogle Scholar
  27. 27.
    Hou J, Lin L, Zhou W, Wang Z, Ding G, Dong Q, et al. Identification of miRNomes in human liver and hepatocellular carcinoma reveals mir-199a/b-3p as therapeutic target for hepatocellular carcinoma. Cancer Cell. 2011;19:232–43.PubMedCrossRefGoogle Scholar
  28. 28.
    Lee H, Choi HJ, Kang CS, Lee HJ, Lee WS, Park CS. Expression of miRNAs and PTEN in endometrial specimens ranging from histologically normal to hyperplasia and endometrial adenocarcinoma. Mod Pathol Off J US Can Acad Pathol Inc. 2012;25:1508–15.Google Scholar
  29. 29.
    Chen JY, Yao DS, He CJ, Lu Y. [Relationship between serum miR-21 and lymph node metastasis in cervical cancer]. J Xi’an Jiaotong Univ (Med Sci). 2012;33:351–5.Google Scholar
  30. 30.
    Taylor DD, Gercel-Taylor C. MicroRNA signatures of tumor-derived exosomes as diagnostic biomarkers of ovarian cancer. Gynecol Oncol. 2008;110:13–21.PubMedCrossRefGoogle Scholar
  31. 31.
    Chen X, Ba Y, Ma L, Cai X, Yin Y, Wang K, et al. Characterization of microRNAs in serum: a novel class of biomarkers for diagnosis of cancer and other diseases. Cell Res. 2008;18:997–1006.PubMedCrossRefGoogle Scholar
  32. 32.
    Zhang X, Chen J, Radcliffe T, Lebrun DP, Tron VA, Feilotter H. An array-based analysis of microRNA expression comparing matched frozen and formalin-fixed paraffin-embedded human tissue samples. J Mol Diagn JMD. 2008;10:513–9.CrossRefGoogle Scholar
  33. 33.
    Siebolts U, Varnholt H, Drebber U, Dienes HP, Wickenhauser C, Odenthal M. Tissues from routine pathology archives are suitable for microRNA analyses by quantitative PCR. J Clin Pathol. 2009;62:84–8.PubMedCentralPubMedCrossRefGoogle Scholar
  34. 34.
    McDonald JS, Milosevic D, Reddi HV, Grebe SK, Algeciras-Schimnich A. Analysis of circulating microRNA: preanalytical and analytical challenges. Clin Chem. 2011;57:833–40.PubMedCrossRefGoogle Scholar
  35. 35.
    Boren T, Xiong Y, Hakam A, Wenham R, Apte S, Wei Z, et al. MicroRNAs and their target messenger RNAs associated with endometrial carcinogenesis. Gynecol Oncol. 2008;110:206–15.PubMedCrossRefGoogle Scholar
  36. 36.
    Devor EJ, Hovey AM, Goodheart MJ, Ramachandran S, Leslie KK. MicroRNA expression profiling of endometrial endometrioid adenocarcinomas and serous adenocarcinomas reveals profiles containing shared, unique and differentiating groups of microRNAs. Oncol Rep. 2011;26:995–1002.PubMedCentralPubMedGoogle Scholar
  37. 37.
    Lee JW, Park YA, Choi JJ, Lee YY, Kim CJ, Choi C, et al. The expression of the miRNA-200 family in endometrial endometrioid carcinoma. Gynecol Oncol. 2011;120:56–62.PubMedCrossRefGoogle Scholar
  38. 38.
    Whiting PF, Rutjes AW, Westwood ME, Mallett S, Deeks JJ, Reitsma JB, et al. Quadas-2: a revised tool for the quality assessment of diagnostic accuracy studies. Ann Intern Med. 2011;155:529–36.PubMedCrossRefGoogle Scholar
  39. 39.
    Mitchell AJ, Vaze A, Rao S. Clinical diagnosis of depression in primary care: a meta-analysis. Lancet. 2009;374:609–19.PubMedCrossRefGoogle Scholar
  40. 40.
    Huang L, Lin JX, Yu YH, Zhang MY, Wang HY, Zheng M. Downregulation of six microRNAs is associated with advanced stage, lymph node metastasis and poor prognosis in small cell carcinoma of the cervix. PLoS ONE. 2012;7:e33762.PubMedCentralPubMedCrossRefGoogle Scholar
  41. 41.
    Torres A, Torres K, Pesci A, Ceccaroni M, Paszkowski T, Cassandrini P, et al. Diagnostic and prognostic significance of miRNA signatures in tissues and plasma of endometrioid endometrial carcinoma patients. Int J Cancer. 2013;132:1633–45.PubMedCrossRefGoogle Scholar
  42. 42.
    Zhao S, Yao D, Chen J, Ding N. Circulating miRNA-20a and miRNA-203 for screening lymph node metastasis in early stage cervical cancer. Genet Test Mol Biomark. 2013;17:631–6.CrossRefGoogle Scholar
  43. 43.
    Tsukamoto O, Miura K, Mishima H, Abe S, Kaneuchi M, Higashijima A, Miura S, Kinoshita A, Yoshiura Ki, Masuzaki H: Identification of endometrioid endometrial carcinoma-associated microRNAs in tissue and plasma. Gynecol Oncol 2014Google Scholar
  44. 44.
    Chen YX, Ma CL, Chen ZF, Zhang W. Clinical significance of miR-143 expression in women with cervical cancer of Uyghur and Han ethnicities, in Xinjiang. Zhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi. 2013;34:1120–4.PubMedGoogle Scholar
  45. 45.
    Rockall AG, Sohaib SA, Harisinghani MG, Babar SA, Singh N, Jeyarajah AR, et al. Diagnostic performance of nanoparticle-enhanced magnetic resonance imaging in the diagnosis of lymph node metastases in patients with endometrial and cervical cancer. J Clin Oncol Off J Am Soc Clin Oncol. 2005;23:2813–21.CrossRefGoogle Scholar
  46. 46.
    Han SS, Lee SH, Kim DH, Kim JW, Park NH, Kang SB, et al. Evaluation of preoperative criteria used to predict lymph node metastasis in endometrial cancer. Acta Obstet Gynecol Scand. 2010;89:168–74.PubMedCrossRefGoogle Scholar
  47. 47.
    Lee JY, Jung DC, Park SH, Lim MC, Seo SS, Park SY, et al. Preoperative prediction model of lymph node metastasis in endometrial cancer. Int J gynecol Cancer Off J Int Gynecol Cancer Soc. 2010;20:1350–5.Google Scholar
  48. 48.
    Baraniskin A, Nopel-Dunnebacke S, Ahrens M, Jensen SG, Zollner H, Maghnouj A, et al. Circulating U2 small nuclear RNA fragments as a novel diagnostic biomarker for pancreatic and colorectal adenocarcinoma. Int J Cancer J Int du cancer. 2013;132:E48–57.CrossRefGoogle Scholar
  49. 49.
    Peltier HJ, Latham GJ. Normalization of microRNA expression levels in quantitative RT-PCR assays: identification of suitable reference RNA targets in normal and cancerous human solid tissues. RNA. 2008;14:844–52.PubMedCentralPubMedCrossRefGoogle Scholar
  50. 50.
    Becker C, Hammerle-Fickinger A, Riedmaier I, Pfaffl MW. mRNA and microRNA quality control for RT-qPCR analysis. Methods. 2010;50:237–43.PubMedCrossRefGoogle Scholar
  51. 51.
    Latham GJ. Normalization of microRNA quantitative RT-PCR data in reduced scale experimental designs. Methods Mol Biol. 2010;667:19–31.PubMedCrossRefGoogle Scholar

Copyright information

© International Society of Oncology and BioMarkers (ISOBM) 2014

Authors and Affiliations

  1. 1.Department of Interventional RadiologyThe Affiliated Provincial Hospital of Anhui Medical UniversityHefeiChina
  2. 2.Department of Interventional RadiologyThe First Affiliated Hospital of Sun Yat-sen UniversityGuangzhouChina
  3. 3.Department of RadiologyThe First Affiliated Hospital of Sun Yat-sen UniversityGuangzhouChina

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