Digestive Diseases and Sciences

, Volume 59, Issue 5, pp 911–919 | Cite as

Identification of Circulating MicroRNAs as Novel Potential Biomarkers for Gastric Cancer Detection: A Systematic Review and Meta-Analysis

  • Xingya Zhu
  • Mengmeng Lv
  • Hao Wang
  • Wenxian Guan



Recent studies show that microRNAs (miRNAs) in serum or plasma can be stably detected and used as potential biomarkers in cancer diagnosis.


To systematically evaluate circulating miRNAs from numerous gastric cancer (GC) expression profiling studies and to determine miRNA biomarkers for GC detection.


A systematic review and meta-analysis of published studies comparing the circulating miRNA expressions between GC patients and healthy controls were carried out. An miRNA ranking system that considered the number of comparisons in agreement, total number of samples, and average fold change was used. Then the receiver-operating characteristic curve (ROC) results of the top miRNAs were combined to further evaluate their diagnostic value by using Meta-disc 1.4.


A total of 35 miRNAs were reported in the 22 included studies, with 7 miRNAs reported in at least 2 studies. MiR-21 is the most consistently reported miRNA with upregulation. In further analysis, the sensitivity, specificity, and area under the curve of summary ROC for miR-21 in GC diagnosis are 0.78 (95 % CI 0.71–0.85), 0.89 (95 % CI 0.82–0.94), and 0.91, respectively.


Circulating miR-21 can serve as a potential biomarker for detection of GC.


Gastric cancer Circulating microRNAs Diagnosis Meta-analysis 



The authors appreciate all the researchers whose articles were included in the study.

Conflict of interest



  1. 1.
    Seevaratnam R, Bocicariu A, Cardoso R, et al. How many lymph nodes should be assessed in patients with gastric cancer? A systematic review. Gastric Cancer. 2012;15:S70–S88.PubMedCrossRefGoogle Scholar
  2. 2.
    Garrido M, Bustos M, Orellana E, et al. Postoperative radio-chemotherapy in locally advanced gastric cancer. Rev Med Chil. 2008;136:844–850.PubMedCrossRefGoogle Scholar
  3. 3.
    Madhavan D, Cuk K, Burwinkel B, Yang R. Cancer diagnosis and prognosis decoded by blood-based circulating microRNA signatures. Front Genet. 2013;4:116.PubMedCentralPubMedCrossRefGoogle Scholar
  4. 4.
    Ichikawa D, Komatsu S, Konishi H, Otsuji E. Circulating microRNA in digestive tract cancers. Gastroenterology. 2012;142:1074–1078.PubMedCrossRefGoogle Scholar
  5. 5.
    Wu WK, Lee CW, Cho CH, et al. MicroRNA dysregulation in gastric cancer: a new player enters the game. Oncogene. 2010;29:5761–5771.PubMedCrossRefGoogle Scholar
  6. 6.
    Blanco-Calvo M, Calvo L, Figueroa A, Haz-Conde M, Anton-Aparicio L, Valladares-Ayerbes M. Circulating microRNAs: molecular microsensors in gastrointestinal cancer. Sensors (Basel). 2012;12:9349–9362.CrossRefGoogle Scholar
  7. 7.
    Mitchell PS, Parkin RK, Kroh EM, et al. Circulating microRNAs as stable blood-based markers for cancer detection. Proc Natl Acad Sci USA. 2008;105:10513–10518.PubMedCentralPubMedCrossRefGoogle Scholar
  8. 8.
    Chan SK, Griffith OL, Tai IT, Jones SJ. Meta-analysis of colorectal cancer gene expression profiling studies identifies consistently reported candidate biomarkers. Cancer Epidemiol Biomarkers Prev. 2008;17:543–552.PubMedCrossRefGoogle Scholar
  9. 9.
    Griffith OL, Melck A, Jones SJ, Wiseman SM. Meta-analysis and meta-review of thyroid cancer gene expression profiling studies identifies important diagnostic biomarkers. J Clin Oncol. 2006;24:5043–5051.PubMedCrossRefGoogle Scholar
  10. 10.
    Ma Y, Zhang P, Yang J, Liu Z, Yang Z, Qin H. Candidate microRNA biomarkers in human colorectal cancer: systematic review profiling studies and experimental validation. Int J Cancer. 2012;130:2077–2087.PubMedCrossRefGoogle Scholar
  11. 11.
    Zhang QH, Sun HM, Zheng RZ, et al. Meta-analysis of microRNA-183 family expression in human cancer studies comparing cancer tissues with noncancerous tissues. Gene. 2013;527:26–32.PubMedCrossRefGoogle Scholar
  12. 12.
    Guan P, Yin Z, Li X, Wu W, Zhou B. Meta-analysis of human lung cancer microRNA expression profiling studies comparing cancer tissues with normal tissues. J Exp Clin Cancer Res. 2012;31:54.PubMedCentralPubMedCrossRefGoogle Scholar
  13. 13.
    Ma Y, Zhang P, Wang F, Qin H. Searching for consistently reported up- and down-regulated biomarkers in colorectal cancer: a systematic review of proteomic studies. Mol Biol Rep. 2012;39:8483–8490.PubMedCrossRefGoogle Scholar
  14. 14.
    Higgins J, Green S. Cochrane Handbook for Systematic Reviews of Interventions 5.1.0 [EB/OL]. 2011. Available at: Accessed July 5, 2013.
  15. 15.
    Whiting P, Rutjes AW, Dinnes J, Reitsma J, Bossuyt PM, Kleijnen J. Development and validation of methods for assessing the quality of diagnostic accuracy studies. Health Technol Assess. 2004;8:1–234.Google Scholar
  16. 16.
    Whiting P, Rutjes AW, Reitsma JB, Bossuyt PM, Kleijnen J. The development of QUADAS: a tool for the quality assessment of studies of diagnostic accuracy included in systematic reviews. BMC Med Res Methodol. 2003;3:25.PubMedCentralPubMedCrossRefGoogle Scholar
  17. 17.
    Cai H, Yuan Y, Hao YF, Guo TK, Wei X, Zhang YM. Plasma microRNAs serve as novel potential biomarkers for early detection of gastric cancer. Med Oncol. 2013;30:452.PubMedCrossRefGoogle Scholar
  18. 18.
    Gorur A, Balci FS, Dogruer UN, et al. Determination of plasma microRNA for early detection of gastric cancer. Mol Biol Rep. 2013;40:2091–2096.PubMedCrossRefGoogle Scholar
  19. 19.
    Kim SY, Jeon TY, Choi CI, et al. Validation of circulating miRNA biomarkers for predicting lymph node metastasis in gastric cancer. J Mol Diagn. 2013;15:661–669.PubMedCrossRefGoogle Scholar
  20. 20.
    Komatsu S, Ichikawa D, Tsujiura M, et al. Prognostic impact of circulating miR-21 in the plasma of patients with gastric carcinoma. Anticancer Res. 2013;33:271–276.PubMedGoogle Scholar
  21. 21.
    Konishi H, Ichikawa D, Komatsu S, et al. Detection of gastric cancer-associated microRNAs on microRNA microarray comparing pre- and post-operative plasma. Br J Cancer. 2012;106:740–747.PubMedCentralPubMedCrossRefGoogle Scholar
  22. 22.
    Li BS, Zhao YL, Guo G, et al. Plasma microRNAs, miR-223, miR-21 and miR-218, as novel potential biomarkers for gastric cancer detection. PLoS ONE. 2012;7:e41629.PubMedCentralPubMedCrossRefGoogle Scholar
  23. 23.
    Li C, Li JF, Cai Q, et al. MiRNA-199a-3p: a potential circulating diagnostic biomarker for early gastric cancer. J Surg Oncol. 2013;108:89–92.PubMedCrossRefGoogle Scholar
  24. 24.
    Liu H, Zhu L, Liu B, et al. Genome-wide microRNA profiles identify miR-378 as a serum biomarker for early detection of gastric cancer. Cancer Lett. 2012;316:196–203.PubMedCrossRefGoogle Scholar
  25. 25.
    Liu R, Zhang C, Hu Z, et al. A five-microRNA signature identified from genome-wide serum microRNA expression profiling serves as a fingerprint for gastric cancer diagnosis. Eur J Cancer. 2011;47:784–791.PubMedCrossRefGoogle Scholar
  26. 26.
    Lo SS, Hung PS, Chen JH, et al. Overexpression of miR-370 and downregulation of its novel target TGFbeta-RII contribute to the progression of gastric carcinoma. Oncogene. 2012;31:226–237.PubMedCrossRefGoogle Scholar
  27. 27.
    Song J, Bai Z, Han W, et al. Identification of suitable reference genes for qPCR analysis of serum microRNA in gastric cancer patients. Dig Dis Sci. 2012;57:897–904.PubMedCrossRefGoogle Scholar
  28. 28.
    Song MY, Pan KF, Su HJ, et al. Identification of serum microRNAs as novel non-invasive biomarkers for early detection of gastric cancer. PLoS ONE. 2012;7:e33608.PubMedCentralPubMedCrossRefGoogle Scholar
  29. 29.
    Tsai KW, Liao YL, Wu CW, et al. Aberrant expression of miR-196a in gastric cancers and correlation with recurrence. Genes Chromosom Cancer. 2012;51:394–401.PubMedCrossRefGoogle Scholar
  30. 30.
    Tsujiura M, Ichikawa D, Komatsu S, et al. Circulating microRNAs in plasma of patients with gastric cancers. Br J Cancer. 2010;102:1174–1179.PubMedCentralPubMedCrossRefGoogle Scholar
  31. 31.
    Valladares-Ayerbes M, Reboredo M, Medina-Villaamil V, et al. Circulating miR-200c as a diagnostic and prognostic biomarker for gastric cancer. J Transl Med. 2012;10:186.PubMedCentralPubMedCrossRefGoogle Scholar
  32. 32.
    Wang B, Zhang Q. The expression and clinical significance of circulating microRNA-21 in serum of five solid tumors. J Cancer Res Clin Oncol. 2012;138:1659–1666.PubMedCrossRefGoogle Scholar
  33. 33.
    Wang M, Gu H, Wang S, et al. Circulating miR-17-5p and miR-20a: molecular markers for gastric cancer. Mol Med Rep. 2012;5:1514–1520.PubMedGoogle Scholar
  34. 34.
    Yan Z, Xiong Y, Xu W, et al. Identification of hsa-miR-335 as a prognostic signature in gastric cancer. PLoS ONE. 2012;7:e40037.PubMedCentralPubMedCrossRefGoogle Scholar
  35. 35.
    Zhang WH, Gui JH, Wang CZ, et al. The identification of miR-375 as a potential biomarker in distal gastric adenocarcinoma. Oncol Res. 2012;20:139–147.PubMedCrossRefGoogle Scholar
  36. 36.
    Zheng Y, Cui L, Sun W, et al. MicroRNA-21 is a new marker of circulating tumor cells in gastric cancer patients. Cancer Biomark. 2011;10:71–77.PubMedGoogle Scholar
  37. 37.
    Zhou H, Guo JM, Lou YR, et al. Detection of circulating tumor cells in peripheral blood from patients with gastric cancer using microRNA as a marker. J Mol Med (Berl). 2010;88:709–717.CrossRefGoogle Scholar
  38. 38.
    Zhou H, Xiao B, Zhou F, et al. MiR-421 is a functional marker of circulating tumor cells in gastric cancer patients. Biomarkers. 2012;17:104–110.PubMedCrossRefGoogle Scholar
  39. 39.
    Mar-Aguilar F, Mendoza-Ramirez JA, Malagon-Santiago I, et al. Serum circulating microRNA profiling for identification of potential breast cancer biomarkers. Dis Markers. 2013;34:163–169.PubMedCentralPubMedCrossRefGoogle Scholar
  40. 40.
    Si H, Sun X, Chen Y, et al. Circulating microRNA-92a and microRNA-21 as novel minimally invasive biomarkers for primary breast cancer. J Cancer Res Clin Oncol. 2013;139:223–229.PubMedCentralPubMedCrossRefGoogle Scholar
  41. 41.
    Shen J, Todd NW, Zhang H, et al. Plasma microRNAs as potential biomarkers for non-small-cell lung cancer. Lab Invest. 2011;91:579–587.PubMedCentralPubMedCrossRefGoogle Scholar
  42. 42.
    Wei J, Gao W, Zhu CJ, et al. Identification of plasma microRNA-21 as a biomarker for early detection and chemosensitivity of non-small cell lung cancer. Chin J Cancer. 2011;30:407–414.PubMedCrossRefGoogle Scholar
  43. 43.
    Kanaan Z, Rai SN, Eichenberger MR, et al. Plasma miR-21: a potential diagnostic marker of colorectal cancer. Ann Surg. 2012;256:544–551.PubMedCrossRefGoogle Scholar
  44. 44.
    Arroyo JD, Chevillet JR, Kroh EM, et al. Argonaute2 complexes carry a population of circulating microRNAs independent of vesicles in human plasma. Proc Natl Acad Sci USA. 2011;108:5003–5008.PubMedCentralPubMedCrossRefGoogle Scholar
  45. 45.
    Vickers KC, Palmisano BT, Shoucri BM, Shamburek RD, Remaley AT. MicroRNAs are transported in plasma and delivered to recipient cells by high-density lipoproteins. Nat Cell Biol. 2011;13:423–433.PubMedCentralPubMedCrossRefGoogle Scholar
  46. 46.
    McDonald JS, Milosevic D, Reddi HV, Grebe SK, Algeciras-Schimnich A. Analysis of circulating microRNA: preanalytical and analytical challenges. Clin Chem. 2011;57:833–840.PubMedCrossRefGoogle Scholar
  47. 47.
    Mitchell PS, Parkin RK, Kroh EM, et al. Circulating microRNAs as stable blood-based markers for cancer detection. Proc Natl Acad Sci USA. 2008;105:10513–10518.PubMedCentralPubMedCrossRefGoogle Scholar
  48. 48.
    Dong P, Kaneuchi M, Watari H, Sudo S, Sakuragi N. MicroRNA-106b modulates epithelial-mesenchymal transition by targeting TWIST1 in invasive endometrial cancer cell lines. Mol Carcinog. 2013. doi: 10.1002/mc.21983.

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Xingya Zhu
    • 1
  • Mengmeng Lv
    • 1
  • Hao Wang
    • 2
  • Wenxian Guan
    • 2
  1. 1.First Clinical Medical CollegeNanjing Medical UniversityNanjingChina
  2. 2.Department of Gastrointestinal SurgeryNanjing Gulou Hospital Affiliated to Medical College of Nanjing UniversityNanjingChina

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