Skip to main content

Advertisement

SpringerLink
Log in

Blood-based multiple-microRNA assay displays a better diagnostic performance than single-microRNA assay in the diagnosis of breast tumor

  • Research Article
  • Published:
Tumor Biology

Abstract

Accumulating evidence has suggested that concentrations of blood-based circulating micro-ribonucleic acids (microRNAs, miRNAs) in breast tumor patients are significantly higher/lower than that in normal individuals, indicating that circulating miRNAs may serve as novel blood-based biomarkers for breast tumor. However, the results of previous studies on this issue have been inconclusive. Therefore, we perform a meta-analysis to determine whether aberrant miRNA expression can be used as molecular markers in blood for the diagnosis of breast tumor. PubMed and other databases were searched to identify eligible studies. The sensitivity and specificity were used to plot the summary receiver operator characteristic curve and calculate the area under the curve (AUC). Finally, 15 articles with a total of 1,428 breast tumor patients and 952 healthy individuals were involved. The summary estimates revealed that the pooled sensitivity was 76 % with 95 % confidence interval (CI) of 67–83 %; the specificity was 87 % with 95 % CI of 77–93 %; the PLR was 5.9 with 95 % CI of 3.3–10.4; the NLR was 0.28 with 95 % CI of 0.20–0.39; the DOR was 21 with 95 % CI of 10–44; and the AUC was 0.88 with 95 % CI of 0.84–0.90. The most noteworthy is that multiple-miRNA assay displayed a better diagnostic performance than single-miRNA assay. In summary, the results of the present meta-analysis suggested that blood-based miRNAs may serve as novel molecular biomarkers for breast tumor, with a relative high level of accuracy, especially based on multiple-miRNA assay. Further large-scale prospective studies are necessary to validate their potential applicability for breast tumor prognosis, treatment, and surveillance.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  1. Dinnes J, Deeks J, Kirby J, Roderick P. A methodological review of how heterogeneity has been examined in systematic reviews of diagnostic test accuracy. Health Technol Assess. 2005;9:1–113. iii.

    CAS  PubMed  Google Scholar 

  2. Jemal A, Bray F, Center MM, Ferlay J, Ward E, Forman D. Global tumor statistics. CA Tumor J Clin. 2011;61:69–90. doi:10.3322/caac.20107.

    Google Scholar 

  3. Parkin DM, Bray F, Ferlay J, Pisani P. Global tumor statistics, 2002. CA Tumor J Clin. 2005;55:74–108.

    Google Scholar 

  4. Yang L, Parkin DM, Ferlay J, Li L, Chen Y. Estimates of tumor incidence in China for 2000 and projections for 2005. Tumor Epidemiol Biomarkers Prev. 2005;14:243–50.

    Google Scholar 

  5. Duffy MJ. Role of tumor markers in patients with solid tumors: a critical review. Eur J Intern Med. 2007;18:175–84. doi:10.1016/j.ejim.2006.12.001.

    CAS  PubMed  Google Scholar 

  6. Roulston JE. Limitations of tumour markers in screening. Br J Surg. 1990;77:961–2.

    CAS  PubMed  Google Scholar 

  7. Rembold H. Metabolism and metabolic roles of 6-polyhydroxyalkylpterins. J Inherit Metab Dis. 1978;1:61–2.

    CAS  PubMed  Google Scholar 

  8. Fassan M, Volinia S, Palatini J, Pizzi M, Baffa R, De Bernard M, et al. MicroRNA expression profiling in human Barrett’s carcinogenesis. Int J Tumor. 2011;129:1661–70. doi:10.1002/ijc.25823.

    CAS  Google Scholar 

  9. Jones CM, Athanasiou T. Summary receiver operating characteristic curve analysis techniques in the evaluation of diagnostic tests. Ann Thorac Surg. 2005;79:16–20. doi:10.1016/j.athoracsur.2004.09.040.

    PubMed  Google Scholar 

  10. Heneghan HM, Miller N, Kelly R, Newell J, Kerin MJ. Systemic miRNA-195 differentiates breast tumor from other malignancies and is a potential biomarker for detecting noninvasive and early stage disease. Oncologist. 2010;15:673–82. doi:10.1634/theoncologist.2010-0103.

    PubMed  PubMed Central  Google Scholar 

  11. Mao Q, Guo H, Gao L, Wang H, Ma X. Peroxisome proliferator-activated receptor gamma2 Pro12Ala (rs1801282) polymorphism and breast tumor susceptibility: a meta-analysis. Mol Med Rep. 2013;8:1773–8. doi:10.3892/mmr.2013.1735.

    CAS  PubMed  Google Scholar 

  12. Zamora J, Abraira V, Muriel A, Khan K, Coomarasamy A. Meta-DiSc: a software for meta-analysis of test accuracy data. BMC Med Res Methodol. 2006;6:31. doi:10.1186/1471-2288-6-31.

    PubMed  PubMed Central  Google Scholar 

  13. Zhu J, Wu L, Kohlmeier M, Ye F, Cai W. Association between MTHFR C677T, MTHFR A1298C and MS A2756G polymorphisms and risk of cervical intraepithelial neoplasia II/III and cervical tumor: a meta-analysis. Mol Med Rep. 2013;8:919–27. doi:10.3892/mmr.2013.1589.

    CAS  PubMed  Google Scholar 

  14. Glas AS, Lijmer JG, Prins MH, Bonsel GJ, Bossuyt PM. The diagnostic odds ratio: a single indicator of test performance. J Clin Epidemiol. 2003;56:1129–35.

    PubMed  Google Scholar 

  15. Zhang J, Wang Y, Liu Y, Zhang X. Lack of association between CYP1A1 T6235C polymorphism and coronary artery disease: evidence from a meta-analysis. Mol Med Rep. 2013;7:543–8. doi:10.3892/mmr.2012.1212.

    CAS  PubMed  Google Scholar 

  16. Hao SW, Jin QH. Association between the +104 T/C polymorphism in the 5’UTR of GDF5 and susceptibility to knee osteoarthritis: a meta-analysis. Mol Med Rep. 2013;7:485–8. doi:10.3892/mmr.2012.1179.

    CAS  PubMed  Google Scholar 

  17. Wang YJ, Pan Y. Angiotensinogen gene M235T polymorphism and risk of coronary artery disease: a meta-analysis. Mol Med Rep. 2012;6:884–8. doi:10.3892/mmr.2012.1011.

    CAS  PubMed  Google Scholar 

  18. Liu G, Sun G, Wang Y, Wang D, Hu W, Zhang J. Association between manganese superoxide dismutase gene polymorphism and breast tumor risk: a meta-analysis of 17,842 subjects. Mol Med Rep. 2012;6:797–804. doi:10.3892/mmr.2012.998.

    CAS  PubMed  Google Scholar 

  19. Ding DL, Liu SJ, Zhu HZ. Association between the CCR2-Val64Ile polymorphism and susceptibility to HIV-1 infection: a meta-analysis. Mol Med Rep. 2011;4:181–6. doi:10.3892/mmr.2010.400.

    CAS  PubMed  Google Scholar 

  20. Zeng XT, Tang XJ, Wang XJ, Li MZ, Guo Y, Huang W, et al. AlloDerm implants for prevention of Frey syndrome after parotidectomy: a systematic review and meta-analysis. Mol Med Rep. 2012;5:974–80. doi:10.3892/mmr.2012.762.

    CAS  PubMed  PubMed Central  Google Scholar 

  21. Garzon R, Fabbri M, Cimmino A, Calin GA, Croce CM. MicroRNA expression and function in tumor. Trends Mol Med. 2006;12:580–7. doi:10.1016/j.molmed.2006.10.006.

    CAS  PubMed  Google Scholar 

  22. Jay C, Nemunaitis J, Chen P, Fulgham P, Tong AW. miRNA profiling for diagnosis and prognosis of human tumor. DNA Cell Biol. 2007;26:293–300. doi:10.1089/dna.2006.0554.

    CAS  PubMed  Google Scholar 

  23. Motoyama K, Inoue H, Takatsuno Y, Tanaka F, Mimori K, Uetake H, et al. Over- and under-expressed microRNAs in human colorectal tumor. Int J Oncol. 2009;34:1069–75.

    CAS  PubMed  Google Scholar 

  24. Xie Y, Todd NW, Liu Z, Zhan M, Fang H, Peng H, et al. Altered miRNA expression in sputum for diagnosis of non-small cell lung tumor. Lung Tumor. 2010;67:170–6. doi:10.1016/j.lungcan.2009.04.004.

    Google Scholar 

  25. Tsujiura M, Ichikawa D, Komatsu S, Shiozaki A, Takeshita H, Kosuga T, et al. Circulating microRNAs in plasma of patients with gastric tumors. Br J Tumor. 2010;102:1174–9. doi:10.1038/sj.bjc.6605608.

    CAS  Google Scholar 

  26. Schepeler T, Reinert JT, Ostenfeld MS, Christensen LL, Silahtaroglu AN, Dyrskjot L, et al. Diagnostic and prognostic microRNAs in stage II colon tumor. Tumor Res. 2008;68:6416–24. doi:10.1158/0008-5472.CAN-07-6110.

    CAS  Google Scholar 

  27. Heneghan HM, Miller N, Lowery AJ, Sweeney KJ, Newell J, Kerin MJ. Circulating microRNAs as novel minimally invasive biomarkers for breast tumor. Ann Surg. 2010;251:499–505. doi:10.1097/SLA.0b013e3181cc939f.

    PubMed  Google Scholar 

  28. Mar-Aguilar F, Mendoza-Ramirez JA, Malagon-Santiago I, Espino-Silva PK, Santuario-Facio SK, Ruiz-Flores P, et al. Serum circulating microRNA profiling for identification of potential breast tumor biomarkers. Dis Markers. 2013;34:163–9. doi:10.3233/dma-120957.

    CAS  PubMed  PubMed Central  Google Scholar 

  29. Asaga S, Kuo C, Nguyen T, Terpenning M, Giuliano AE, Hoon DS. Direct serum assay for microRNA-21 concentrations in early and advanced breast tumor. Clin Chem. 2011;57:84–91. doi:10.1373/clinchem.2010.151845.

    CAS  PubMed  Google Scholar 

  30. Moher D, Liberati A, Tetzlaff J, Altman DG. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Ann Intern Med. 2009;151:264–9. W264.

    PubMed  Google Scholar 

  31. 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. doi:10.7326/0003-4819-155-8-201110180-00009.

    PubMed  Google Scholar 

  32. Higgins JP, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in meta-analyses. BMJ. 2003;327:557–60. doi:10.1136/bmj.327.7414.557.

    Article  Google Scholar 

  33. Jackson D, White IR, Thompson SG. Extending DerSimonian and Laird’s methodology to perform multivariate random effects meta-analyses. Stat Med. 2010;29:1282–97. doi:10.1002/sim.3602.

    PubMed  Google Scholar 

  34. Deeks JJ, Macaskill P, Irwig L. The performance of tests of publication bias and other sample size effects in systematic reviews of diagnostic test accuracy was assessed. J Clin Epidemiol. 2005;58:882–93. doi:10.1016/j.jclinepi.2005.01.016.

    PubMed  Google Scholar 

  35. Guo LJ, Zhang QY. Decreased serum miR-181a is a potential new tool for breast tumor screening. Int J Mol Med. 2012;30:680–6. doi:10.3892/ijmm.2012.1021.

    CAS  PubMed  Google Scholar 

  36. Hu Z, Dong J, Wang LE, Ma H, Liu J, Zhao Y, et al. Serum microRNA profiling and breast tumor risk: the use of miR-484/191 as endogenous controls. Carcinogenesis. 2012;33:828–34. doi:10.1093/carcin/bgs030.

    CAS  PubMed  Google Scholar 

  37. Madhavan D, Zucknick M, Wallwiener M, Cuk K, Modugno C, Scharpff M, et al. Circulating miRNAs as surrogate markers for circulating tumor cells and prognostic markers in metastatic breast tumor. Clin Tumor Res. 2012;18:5972–82. doi:10.1158/1078-0432.ccr-12-1407.

    CAS  Google Scholar 

  38. Schrauder MG, Strick R, Schulz-Wendtland R, Strissel PL, Kahmann L, Loehberg CR, et al. Circulating micro-RNAs as potential blood-based markers for early stage breast tumor detection. PLoS ONE. 2012;7:e29770. doi:10.1371/journal.pone.0029770.

    CAS  PubMed  PubMed Central  Google Scholar 

  39. Sun Y, Wang M, Lin G, Sun S, Li X, Qi J, et al. Serum microRNA-155 as a potential biomarker to track disease in breast tumor. PLoS ONE. 2012;7:e47003. doi:10.1371/journal.pone.0047003.

    CAS  PubMed  PubMed Central  Google Scholar 

  40. Wang B, Zhang Q. The expression and clinical significance of circulating microRNA-21 in serum of five solid tumors. J Tumor Res Clin Oncol. 2012;138:1659–66. doi:10.1007/s00432-012-1244-9.

    CAS  Google Scholar 

  41. Wu Q, Wang C, Lu Z, Guo L, Ge Q. Analysis of serum genome-wide microRNAs for breast tumor detection. Clin Chim Acta. 2012;413:1058–65. doi:10.1016/j.cca.2012.02.016.

    CAS  PubMed  Google Scholar 

  42. Cuk K, Zucknick M, Heil J, Madhavan D, Schott S, Turchinovich A, et al. Circulating microRNAs in plasma as early detection markers for breast tumor. Int J Tumor. 2013;132:1602–12. doi:10.1002/ijc.27799.

    CAS  Google Scholar 

  43. Eichelser C, Flesch-Janys D, Chang-Claude J, Pantel K, Schwarzenbach H. Deregulated serum concentrations of circulating cell-free microRNAs miR-17, miR-34a, miR-155, and miR-373 in human breast tumor development and progression. Clin Chem. 2013;59:1489–96. doi:10.1373/clinchem.2013.205161.

    CAS  PubMed  Google Scholar 

  44. Gao J, Zhang Q, Xu J, Guo L, Li X. Clinical significance of serum miR-21 in breast tumor compared with CA153 and CEA. Chin J Tumor Res. 2013;25:743–8. doi:10.3978/j.issn.1000-9604.2013.12.04.

    Google Scholar 

  45. Zeng RC, Zhang W, Yan XQ, Ye ZQ, Chen ED, Huang DP, et al. Down-regulation of miRNA-30a in human plasma is a novel marker for breast tumor. Med Oncol. 2013;30:477. doi:10.1007/s12032-013-0477-z.

    PubMed  Google Scholar 

  46. McDermott AM, Miller N, Wall D, Martyn LM, Ball G, Sweeney KJ, et al. Identification and validation of oncologic miRNA biomarkers for Luminal A-like breast tumor. PLoS ONE. 2014;9:e87032. doi:10.1371/journal.pone.0087032.

    PubMed  PubMed Central  Google Scholar 

Download references

Conflicts of interest

None

Author information

Authors and Affiliations

  1. Department of Thoracic Surgery, China-Japan Union Hospital, Jilin University, No. 126, Xiantai Street, Changchun, 130033, China

    Hua Xin, Bin Yang, Lening Zhang, Zhifeng Han & Chunshan Han

  2. Department of Pharmacy, China-Japan Union Hospital, Jilin University, Changchun, 130033, China

    Xiaoli Li

Authors
  1. Hua Xin
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xiaoli Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Bin Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Lening Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Zhifeng Han
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Chunshan Han
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Chunshan Han.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplement S1

The PRISMA Checklist. (DOC 57 kb)

Supplement S2

The QUADAS-2 Checklist. (PDF 265 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Xin, H., Li, X., Yang, B. et al. Blood-based multiple-microRNA assay displays a better diagnostic performance than single-microRNA assay in the diagnosis of breast tumor. Tumor Biol. 35, 12635–12643 (2014). https://doi.org/10.1007/s13277-014-2587-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13277-014-2587-4

Keywords

Search

Navigation