Int. J. Mol. Sci. 2012, 13(10), 12544-12555; doi:10.3390/ijms131012544

Review
MicroRNAs as Diagnostic Biomarkers in Gastric Cancer
Ying Yin , Jun Li , Shujie Chen , Tianhua Zhou and Jianmin Si *
Institute of Clinical Research of Gastroenterology, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, 3 East Qingchun Road, Hangzhou 310016, China; E-Mails: dy1225@gmail.com (Y.Y.); lj_lcyxmajor@yahoo.cn (J.L.); chensj77@hotmail.com (S.C.); tzhou@zju.edu.cn (T.Z.)
*
Author to whom correspondence should be addressed; E-Mail: sijm@zju.edu.cn; Tel./Fax: +86-571-8600-6788.
Received: 24 July 2012; in revised form: 31 August 2012 / Accepted: 5 September 2012 /
Published: 1 October 2012

Abstract

: Considering the high mortality rates and the unfavorable prognosis of gastric cancer (GC) as well as the lack of a clinical predictive marker, which is sufficiently sensitive to GC, it is of great significance to investigate new sensitive and specific markers for GC diagnosis. MicroRNAs (miRNAs) could be a practical form of potential biomarkers in the diagnosis of human disease, and they are confirmed to be closely associated with GC. In this review, we discuss the recent research results that indicate the feasibility and clinical applications of miRNAs in GC. Although several challenges remain to be addressed, miRNAs have the potential to be applied in the diagnosis of GC.
Keywords:
microRNAs; gastric cancer; biomarkers; diagnosis

1. Introduction

Gastric cancer (GC) has a high incidence and ranks second in the leading causes of cancer mortality [1,2]. The prognosis of GC is highly dependent on the stage of the disease at diagnosis [3]. However, very few cases are detected at an early stage. Due to the high mortality rate and poor prognosis of the disease, primary prevention should be of high priority [46].

Recently, a cascade of premalignant conditions and lesions has been proposed, including chronic atrophic gastritis, intestinal metaplasia, and intraepithelial neoplasia (dysplasia) [7], whose identification and characterization might help to stratify the individual risk. The present classification systems of GC based on pathology has failed to efficiently predict the risk of sequential development from premalignant lesions such as intestinal metaplasia and even dysplasia to malignant lesions. Recent studies of molecular biology have revealed that certain gene alterations might be associated with some premalignant lesions. For example, a mutation in the p53 gene was detected in intestinal metaplasia lesions adjacent to GC [8], so was the over-expression of cyclooxygenase-2 [9]. Boussioutas et al. found a series of genes probably related with tumor progression by the expression profile of 124 gastric mucosa samples including gastritis, intestinal metaplasia, and adenocarcinoma [10].

As a result, it could be a long-term dynamic process from the premalignant conditions to GC, in which there could be the canceration of genes firstly, followed by malignant pathological changes in the gastric mucosa after the short-term malignant transformation progress [1113]. And there could be a number of molecules associated with GC under research as possible prediction markers in the early stage of GC, even in late premalignant conditions. However, there is no good biomarker that is able to efficiently diagnose the corresponding stages of GC. To date, the existing cancer biomarkers such as MG7-Ag, CEA, CA199 and CA50 in clinical diagnosis cannot be effectively applied to the clinical diagnosis of GC because of their low sensitivity and specificity.

Besides the former gene biomarkers, microRNAs (miRNAs) could be another form of potential biomarkers in the diagnosis of human disease, and they are determined to be closely associated with cancers [14]. Meanwhile, it is promising that the miRNA network biomarkers could be applied to classify the expression data sets in different progression stages from premalignant conditions to GC.

2. The Mode of Action of MicroRNAs

MicroRNAs (miRNAs) are non-coding RNAs of approximately 19–25 nucleotides (nt), which suppress the translation of target genes by binding to their mRNAs. They are widely found in organisms such as plants, nematodes, fruit flies and mammals, and are conserved during evolution [15]. During miRNA biogenesis, genomic DNA is first transcribed by RNA polymerase II to produce the primary miRNA transcripts (pri-miRNA). The Drosha-DGCR8 complex initiates miRNA maturation by precise cleavage of the stem loop that is embedded in the primary transcript, producing a 60 to 70 nt miRNA precursor (pre-miRNA) in the nucleus [16]. Subsequently, the pre-miRNA is transported to the cytoplasm by means of GTP energy decomposition [17,18] and it is processed to a double-stranded RNA molecule of about 19 to 25 nt in length by the RNA endonuclease Dicer. Then, RNA interference is implemented through the action of the RNA-induced silencing complex (RISC) to regulate target genes. The final product is the single-stranded mature miRNA molecule, which can cleave the target mRNA when associated with RISC [1921]. It is speculated that the total number of miRNAs may be much larger and that several of them have emerged only in primates.

3. Feasibility of Using MicroRNAs as Gastric Cancer Biomarkers

MicroRNAs have an important function in regulating RNA stability and gene expression by targeting mRNAs for cleavage or translational repression, and they are likely to influence the output of many protein-coding genes. The deregulation of miRNAs has been determined to correlate with cancer development and tumor progression [22]. They could play important roles in the regulation of almost all biological processes, including ontogeny, cell proliferation, apoptosis, migration, differentiation, metabolism and stress [23]. For example, miR-430 is involved in brain development in zebrafish [24]. Meanwhile, miR-181 could be involved in the regulation of B cell differentiation [25]. It is also found that miR-375 could regulate the development of mammalian islet cells and insulin secretion [26], while miR-221 and miR-222 could be involved in the regulation of angiogenesis [27]. In addition, genome-wide studies showed that miRNA genes are frequently located within regions of the loss of heterozygosity, amplification, fragile sites, and other cancer-associated genomic regions, suggesting the vital role of miRNAs in tumorigenesis [28].

Further investigation has shown that up-regulated and down-regulated miRNAs could be important in tumorigenesis as new broad-spectrum oncogenes and tumor suppressor genes in GC, respectively [29]. For example, findings demonstrated an oncogenic role for miR-372 in controlling cell growth, cell cycle and apoptosis through the down-regulation of a tumor suppressor gene, LATS2 [30]. Meanwhile, the over-expression of miR-650 may promote GC proliferation and growth of cancer cells, at least partially through directly targeting ING4 [31]. The down-regulation of mir-663 in tumor cells may contribute to the hyperplasia of aberrant cells, leading to the development of GC [32]. The studies showed that the aberrant over-expression of miR-126 and consequent SOX2 down-regulation might contribute to gastric carcinogenesis [33]. On the contrary, miR-9, miR-16 and miR-21 could target NF-kappaB1 and regulate the growth of GC cells, suggesting an impressive tumor suppressive activity in human GC pathogenesis [34,35]. Previous research provided a lot of important evidence that miR-148b targeted CCKBR and was significant in suppressing the growth of GC cells [36]. Furthermore, over-expression of let-7a resulted in a decrease in cell proliferation and G1 arrest, significantly suppressed anchorage-dependent growth in vitro and the tumorigenicity of GC cells in a nude mouse xenograft model [37].

Besides the association with tumorigenesis, further profiling studies have shown a correlation of miRNAs with proliferation, pathology, migration and invasion by means of targeting genes. The results suggested that miR-451 [38] and miR-141 could be involved in the development of GC through their inhibitory effect on cell proliferation [39]. Members of the miR-29 family could obviously inhibit cell proliferation, migration, and invasion of GC cells by targeting Cdc42 [40]. miR-544 could be a key regulator in switching cell cycles on or off in GC [41]. Meanwhile, the expression of miR-101 could be down-regulated in GC tissues and cells, and the ectopic expression of miR-101 significantly inhibits cellular proliferation, migration and invasion of GC cells by targeting EZH2, Cox-2, Mcl-1 and Fos [42]. Furthermore, miR-221 and miR-222 could regulate radio-sensitivity, cell growth and invasion of SGC7901 cells possibly via direct modulation of PTEN expression [43]. Jin et al. reported that both miR-192 and miR-215 were over-expressed in vivo and exerted cell growth and migration-promoting effects in vitro [44]. Liang et al. demonstrated that the over-expression of let-7f in GC could inhibit invasion and migration of GC cells through directly targeting the tumor metastasis-associated gene MYH9 [45]. Hayashi et al. showed that the cytotoxin-associated gene A of Helicobacter pylori could induce aberrant epigenetic silencing of let-7 expression, leading to Ras up-regulation [46]. Data indicated that miR-223 targeted FBXW7/hCdc4 expression at the post-transcriptional level and appeared to regulate apoptosis, proliferation, and invasion in GC [47]. In addition, miR-200b regulates ZEB2 expression and thus controls metastasis in GC [48]. miR-145 could suppress tumor metastasis by inhibiting N-cadherin protein translation, and then indirectly down-regulating its downstream effector MMP9 [49].

4. Clinical Application of miRNAs as Biomarkers in Gastric Cancer

A number of miRNAs are closely associated with GC, suggesting a potential role of these miRNAs in the diagnosis of GC [50]. By microarray technology, several miRNAs were demonstrated to be associated with GC with conspicuous expression changes. Some of these miRNAs were significantly up-regulated in GC endothelium compared to normal endothelium [5155]. Meanwhile, other miRNAs such as mir-128b, mir-129 and mir-148 were reported to be down-regulated in undifferentiated GC tissue [53], which summarized in Table 1.

Presently, there have been some preliminary findings on the relationship between miRNA expression and GC development. Unique miRNAs were associated with the progression and prognosis of GC as meaningful prognostic markers [56,57], which is summarized in Table 1. Elevated miR-21 expression was significantly correlated with size and depth [58], and low expression levels of miR-451 [38] and miR-125a-5p was associated with enhanced malignant potential such as tumor size, tumor invasion, liver metastasis, and poor prognosis [59]. The patients with down-regulated miR-409-3p [60] and miR-221 [61] could be prone to suffer from lymph node metastasis. Furthermore, it was shown that miR-107 expression in GC tissues was an independent prognostic factor for overall survival (OS) and disease-free survival [62]. Additionally, multivariate analysis showed that the risk signatures could be independent predictors of OS, such as a seven-miRNA (miR-10b, miR-21, miR-223, miR-338, let-7a, miR-30a-5p, miR-126) [63] and a progression-related signature (miR-125b, miR-199a, and miR-100), which were associated with unfavorable outcomes in OS independent of clinical covariates including depth of invasion, lymph-node metastasis and stage [64]. Moreover, extracellular miR-196a detected in conditioned medium was strongly correlated with its cellular expression status, and the increased circulating miR-196a in patient serum was associated with GC disease status and relapse [65].

Generally speaking, the best cancer biomarkers for diagnosis should be peripheral blood markers in order to facilitate the health check-up of mass screening and follow-ups of those who are at higher risk. It is exciting that in 2008, three independent international research groups found the existence of stable miRNA in the peripheral blood of humans and other mammals almost at the same time. They revealed that the expression spectrum of particular peripheral blood miRNAs could constitute a “molecular fingerprint” for the diagnosis of some cancers and other diseases [6668]. Within the past few years, it has become possible to detect the serum concentration of miRNA in GC [6971]. There are only a few studies on the expression changes of miRNA in the serum of patients with GC, which are summarized in Table 2. Some miRNAs were reported to be up-regulated, including miR-20b, miR-20a, miR-17, miR-106a, miR-18a, miR-21 [72], miR-17-5p, miR-21, miR-106a and miR-106b [73]. Next-generation Solexa sequencing results demonstrated that 19 serum miRNAs were markedly up-regulated in GC patients compared to the controls, and a profile of five serum miRNAs (miR-1, miR-20a, miR-27a, miR-34 and miR-423-5p) was identified as a biomarker for GC detection. The analysis results showed that the serum miRNA-based biomarker could also indicate the progression stages of tumors [74]. Meanwhile, a study comparing pre- and post-operative plasma miRNA levels led to the identification of two miRNAs, miR-451 and miR-486, as potential biomarkers for GC, as they were highly abundant in plasma and showed a marked decrease in post-operative samples [75]. Tsujiura et al. reported that in these potential markers, the values of the area under the receiver-operating characteristic curve were 0.721 for the miR-106b assay and 0.879 for the miR-106a/let-7a ratio assay [73]. And miR-378 alone could yield a ROC curve area of 0.861 with 87.5% sensitivity and 70.73% specificity in discriminating GC patients from healthy controls [76]. The prognostic signature might be applicable and helpful for future treatment decisions. In addition, the latest study reported that the use of gastric juice miR-421 showed a remarkable improvement compared with the use of serum carcinoembryonic antigen alone [77].

Furthermore, there are still a lot of challenges in analyzing miRNAs, which concern quantification, normalization and data processing steps in miRNA analysis. The main quantification methods for analysis of miRNAs are the relative quantification by a stem-loop reverse transcription PCR [78], microarrays [79] and next-generation sequencing [69]. Quantitative RT-PCR has been widely used for the sensitive detection of low abundant circulating miRNAs with high reproducibility [78]. And sequencing technologies could result in a steep increase of the rate of newly described microRNAs [80]. Furthermore, due to the considerably variable results, it is needed for better standardization methods. So far, several normalization strategies for the analysis of circulating miRNAs are available especially housekeeping miRNAs, such as miR-16 [74] and RUN6B [73].

5. Conclusions

In conclusion, GC-specific miRNAs may improve future cancer diagnosis and prognosis due to the close association of miRNAs with GC in several stages. Many important functions of GC-specific miRNAs during the processes of cancer development were found and several promising miRNAs as biomarkers were reported. However, the quantification and normalization strategies should be standardized before any of the novel miRNA biomarkers is applicable for clinical routine, and the function of miRNAs needs to be further identified for the proper use of miRNA biomarkers in evidence-based medicine.

References

  1. Jemal, A.; Bray, F.; Center, M.M.; Ferlay, J.; Ward, E.; Forman, D. Global cancer statistics. CA Cancer J. Clin 2011, 61, 69–90.
  2. Jemal, A.; Siegel, R.; Ward, E.; Hao, Y.; Xu, J.; Murray, T.; Thun, M.J. Cancer statistics, 2008. CA Cancer J. Clin 2008, 58, 71–96.
  3. Kampschoer, G.H.; Fujii, A.; Masuda, Y. Gastric cancer detected by mass survey. Comparison between mass survey and outpatient detection. Scand. J. Gastroenterol 1989, 24, 813–817.
  4. Baba, H.; Maehara, Y.; Takeuchi, H.; Inutsuka, S.; Okuyama, T.; Adachi, Y.; Akazawa, K.; Sugimachi, K. Effect of lymph node dissection on the prognosis in patients with node-negative early gastric cancer. Surgery 1995, 117, 165–169.
  5. Hisamichi, S. Screening for gastric cancer. World J. Surg 1989, 13, 31–37.
  6. Hundahl, S.A.; Stemmermann, G.N.; Oishi, A. Racial factors cannot explain superior Japanese outcomes in stomach cancer. Arch. Surg 1996, 131, 170–175.
  7. Correa, P. Human gastric carcinogenesis: A multistep and multifactorial process—First American Cancer Society Award Lecture on Cancer Epidemiology and Prevention. Cancer Res 1992, 52, 6735–6740.
  8. Morgan, C.; Jenkins, G.J.; Ashton, T.; Griffiths, A.P.; Baxter, J.N.; Parry, E.M.; Parry, J.M. Detection of p53 mutations in precancerous gastric tissue. Br. J. Cancer 2003, 89, 1314–1319.
  9. Leung, W.K.; Ng, E.K.; Chan, F.K.; Chan, W.Y.; Chan, K.F.; Auyeung, A.C.; Lam, C.C.; Lau, J.Y.; Sung, J.J. Effects of long-term rofecoxib on gastric intestinal metaplasia: Results of a randomized controlled trial. Clin. Cancer Res 2006, 12, 4766–4772.
  10. Boussioutas, A.; Li, H.; Liu, J.; Waring, P.; Lade, S.; Holloway, A.J.; Taupin, D.; Gorringe, K.; Haviv, I.; Desmond, P.V.; et al. Distinctive patterns of gene expression in premalignant gastric mucosa and gastric cancer. Cancer Res 2003, 63, 2569–2577.
  11. Nardone, G.; Rocco, A.; Malfertheiner, P. Review article: Helicobacter pylori and molecular events in precancerous gastric lesions. Aliment. Pharmacol. Ther 2004, 20, 261–270.
  12. Tahara, E. Genetic pathways of two types of gastric cancer. IARC Sci. Publ 2004, 157, 327–349.
  13. Yuasa, Y. Control of gut differentiation and intestinal-type gastric carcinogenesis. Nat. Rev. Cancer 2003, 3, 592–600.
  14. Brenner, B.; Hoshen, M.B.; Purim, O.; David, M.B.; Ashkenazi, K.; Marshak, G.; Kundel, Y.; Brenner, R.; Morgenstern, S.; Halpern, M.; et al. MicroRNAs as a potential prognostic factor in gastric cancer. World J. Gastroenterol 2011, 17, 3976–3985.
  15. Kim, V.N.; Han, J.; Siomi, M.C. Biogenesis of small RNAs in animals. Nat. Rev. Mol. Cell Biol 2009, 10, 126–139.
  16. Han, J.; Lee, Y.; Yeom, K.H.; Nam, J.W.; Heo, I.; Rhee, J.K.; Sohn, S.Y.; Cho, Y.; Zhang, B.T.; Kim, V.N. Molecular basis for the recognition of primary microRNAs by the Drosha-DGCR8 complex. Cell 2006, 125, 887–901.
  17. Lund, E.; Guttinger, S.; Calado, A.; Dahlberg, J.E.; Kutay, U. Nuclear export of microRNA precursors. Science 2004, 303, 95–98.
  18. Bohnsack, M.T.; Czaplinski, K.; Gorlich, D. Exportin 5 is a RanGTP-dependent dsRNA-binding protein that mediates nuclear export of pre-miRNAs. RNA 2004, 10, 185–191.
  19. Chendrimada, T.P.; Gregory, R.I.; Kumaraswamy, E.; Norman, J.; Cooch, N.; Nishikura, K.; Shiekhattar, R. TRBP recruits the Dicer complex to Ago2 for microRNA processing and gene silencing. Nature 2005, 436, 740–744.
  20. Gregory, R.I.; Chendrimada, T.P.; Cooch, N.; Shiekhattar, R. Human RISC couples microRNA biogenesis and posttranscriptional gene silencing. Cell 2005, 123, 631–640.
  21. Bentwich, I.; Avniel, A.; Karov, Y.; Aharonov, R.; Gilad, S.; Barad, O.; Barzilai, A.; Einat, P.; Einav, U.; Meiri, E.; et al. Identification of hundreds of conserved and nonconserved human microRNAs. Nat. Genet 2005, 37, 766–770.
  22. Bartel, D.P. MicroRNAs: Genomics, biogenesis, mechanism, and function. Cell 2004, 116, 281–297.
  23. Ambros, V. The functions of animal microRNAs. Nature 2004, 431, 350–355.
  24. Giraldez, A.J.; Cinalli, R.M.; Glasner, M.E.; Enright, A.J.; Thomson, J.M.; Baskerville, S.; Hammond, S.M.; Bartel, D.P.; Schier, A.F. MicroRNAs regulate brain morphogenesis in zebrafish. Science 2005, 308, 833–838.
  25. Chen, C.Z.; Li, L.; Lodish, H.F.; Bartel, D.P. MicroRNAs modulate hematopoietic lineage differentiation. Science 2004, 303, 83–86.
  26. Poy, M.N.; Eliasson, L.; Krutzfeldt, J.; Kuwajima, S.; Ma, X.; Macdonald, P.E.; Pfeffer, S.; Tuschl, T.; Rajewsky, N.; Rorsman, P.; et al. A pancreatic islet-specific microRNA regulates insulin secretion. Nature 2004, 432, 226–230.
  27. Poliseno, L.; Tuccoli, A.; Mariani, L.; Evangelista, M.; Citti, L.; Woods, K.; Mercatanti, A.; Hammond, S.; Rainaldi, G. MicroRNAs modulate the angiogenic properties of HUVECs. Blood 2006, 108, 3068–3071.
  28. Calin, G.A.; Sevignani, C.; Dumitru, C.D.; Hyslop, T.; Noch, E.; Yendamuri, S.; Shimizu, M.; Rattan, S.; Bullrich, F.; Negrini, M.; et al. Human microRNA genes are frequently located at fragile sites and genomic regions involved in cancers. Proc. Natl. Acad. Sci. USA 2004, 101, 2999–3004.
  29. Link, A.; Kupcinskas, J.; Wex, T.; Malfertheiner, P. Macro-Role of microRNA in gastric cancer. Dig. Dis 2012, 30, 255–267.
  30. Cho, W.J.; Shin, J.M.; Kim, J.S.; Lee, M.R.; Hong, K.S.; Lee, J.H.; Koo, K.H.; Park, J.W.; Kim, K.S. MiR-372 regulates cell cycle and apoptosis of AGS human gastric cancer cell line through direct regulation of LATS2. Mol. Cells 2009, 28, 521–527.
  31. Zhang, X.; Zhu, W.; Zhang, J.; Huo, S.; Zhou, L.; Gu, Z.; Zhang, M. MicroRNA-650 targets ING4 to promote gastric cancer tumorigenicity. Biochem. Biophys. Res. Commun 2010, 395, 275–280.
  32. Pan, J.; Hu, H.; Zhou, Z.; Sun, L.; Peng, L.; Yu, L.; Liu, J.; Yang, Z.; Ran, Y. Tumor-suppressive mir-663 gene induces mitotic catastrophe growth arrest in human gastric cancer cells. Oncol. Rep 2010, 24, 105–112.
  33. Otsubo, T.; Akiyama, Y.; Hashimoto, Y.; Shimada, S.; Goto, K.; Yuasa, Y. MicroRNA-126 inhibits SOX2 expression and contributes to gastric carcinogenesis. PLoS One 2011, 6, e16617.
  34. Wan, H.Y.; Guo, L.M.; Liu, T.; Liu, M.; Li, X.; Tang, H. Regulation of the transcription factor NF-κB1 by microRNA-9 in human gastric adenocarcinoma. Mol. Cancer 2010, 9, 16.
  35. Shin, V.Y.; Jin, H.; Ng, E.K.; Cheng, A.S.; Chong, W.W.; Wong, C.Y.; Leung, W.K.; Sung, J.J.; Chu, K.M. NF-κB targets miR-16 and miR-21 in gastric cancer: involvement of prostaglandin E receptors. Carcinogenesis 2011, 32, 240–245.
  36. Song, Y.X.; Yue, Z.Y.; Wang, Z.N.; Xu, Y.Y.; Luo, Y.; Xu, H.M.; Zhang, X.; Jiang, L.; Xing, C.Z.; Zhang, Y. MicroRNA-148b is frequently down-regulated in gastric cancer and acts as a tumor suppressor by inhibiting cell proliferation. Mol. Cancer 2011, 10, 1.
  37. Yang, Q.; Jie, Z.; Cao, H.; Greenlee, A.R.; Yang, C.; Zou, F.; Jiang, Y. Low-level expression of let-7a in gastric cancer and its involvement in tumorigenesis by targeting RAB40C. Carcinogenesis 2011, 32, 713–722.
  38. Bandres, E.; Bitarte, N.; Arias, F.; Agorreta, J.; Fortes, P.; Agirre, X.; Zarate, R.; Diaz-Gonzalez, J.A.; Ramirez, N.; Sola, J.J.; et al. MicroRNA-451 regulates macrophage migration inhibitory factor production and proliferation of gastrointestinal cancer cells. Clin. Cancer Res 2009, 15, 2281–2290.
  39. Du, Y.; Xu, Y.; Ding, L.; Yao, H.; Yu, H.; Zhou, T.; Si, J. Down-regulation of miR-141 in gastric cancer and its involvement in cell growth. J. Gastroenterol 2009, 44, 556–561.
  40. Lang, N.; Liu, M.; Tang, Q.L.; Chen, X.; Liu, Z.; Bi, F. Effects of microRNA-29 family members on proliferation and invasion of gastric cancer cell lines. Chin. J. Cancer 2010, 29, 603–610.
  41. Zhi, Q.; Guo, X.; Guo, L.; Zhang, R.; Jiang, J.; Ji, J.; Zhang, J.; Chen, X.; Cai, Q.; Li, J.; et al. Oncogenic miR-544 is an Important Molecular Target in Gastric Cancer. Anticancer Agents Med. Chem 2012. in press.
  42. Wang, H.J.; Ruan, H.J.; He, X.J.; Ma, Y.Y.; Jiang, X.T.; Xia, Y.J.; Ye, Z.Y.; Tao, H.Q. MicroRNA-101 is down-regulated in gastric cancer and involved in cell migration and invasion. Eur. J. Cancer 2010, 46, 2295–2303.
  43. Chun-Zhi, Z.; Lei, H.; An-Ling, Z.; Yan-Chao, F.; Xiao, Y.; Guang-Xiu, W.; Zhi-Fan, J.; Pei-Yu, P.; Qing-Yu, Z.; Chun-Sheng, K. MicroRNA-221 and microRNA-222 regulate gastric carcinoma cell proliferation and radioresistance by targeting PTEN. BMC Cancer 2010, 10, 367.
  44. Jin, Z.; Selaru, F.M.; Cheng, Y.; Kan, T.; Agarwal, R.; Mori, Y.; Olaru, A.V.; Yang, J.; David, S.; Hamilton, J.P.; et al. MicroRNA-192 and -215 are upregulated in human gastric cancer in vivo and suppress ALCAM expression in vitro. Oncogene 2011, 30, 1577–1585.
  45. Liang, S.; He, L.; Zhao, X.; Miao, Y.; Gu, Y.; Guo, C.; Xue, Z.; Dou, W.; Hu, F.; Wu, K.; et al. MicroRNA let-7f inhibits tumor invasion and metastasis by targeting MYH9 in human gastric cancer. PLoS One 2011, 6, e18409.
  46. Hayashi, Y.; Tsujii, M.; Jun, W.; Kondo, J.; Akasaka, T.; Jing, Y.; Li, W.; Nakamura, T.; Nishida, T.; Iijima, H.; et al. CagA mediates epigenetic regulation to attenuate let-7 expression in Helicobacter pylori-related carcinogenesis. Gut 2012, doi:10.1136/gutjnl-2011-301625.
  47. Li, J.; Guo, Y.; Liang, X.; Sun, M.; Wang, G.; De, W.; Wu, W. MicroRNA-223 functions as an oncogene in human gastric cancer by targeting FBXW7/hCdc4. J. Cancer Res. Clin. Oncol 2012, 138, 763–774.
  48. Kurashige, J.; Kamohara, H.; Watanabe, M.; Hiyoshi, Y.; Iwatsuki, M.; Tanaka, Y.; Kinoshita, K.; Saito, S.; Baba, Y.; Baba, H. MicroRNA-200b Regulates Cell Proliferation, Invasion, and Migration by Directly Targeting ZEB2 in Gastric Carcinoma. Ann. Surg. Oncol 2012, 19, 656–664.
  49. Gao, P.; Xing, A.Y.; Zhou, G.Y.; Zhang, T.G.; Zhang, J.P.; Gao, C.; Li, H.; Shi, D.B. The molecular mechanism of microRNA-145 to suppress invasion-metastasis cascade in gastric cancer. Oncogene 2012, doi:10.1038/onc.2012.61.
  50. Cho, W.C. MicroRNAs: Potential biomarkers for cancer diagnosis, prognosis and targets for therapy. Int. J. Biochem. Cell Biol 2010, 42, 1273–1281.
  51. Chan, S.H.; Wu, C.W.; Li, A.F.; Chi, C.W.; Lin, W.C. miR-21 microRNA expression in human gastric carcinomas and its clinical association. Anticancer Res 2008, 28, 907–911.
  52. Liu, T.; Tang, H.; Lang, Y.; Liu, M.; Li, X. MicroRNA-27a functions as an oncogene in gastric adenocarcinoma by targeting prohibitin. Cancer Lett 2009, 273, 233–242.
  53. Katada, T.; Ishiguro, H.; Kuwabara, Y.; Kimura, M.; Mitui, A.; Mori, Y.; Ogawa, R.; Harata, K.; Fujii, Y. MicroRNA expression profile in undifferentiated gastric cancer. Int. J. Oncol 2009, 34, 537–542.
  54. Guo, J.; Miao, Y.; Xiao, B.; Huan, R.; Jiang, Z.; Meng, D.; Wang, Y. Differential expression of microRNA species in human gastric cancer versus non-tumorous tissues. J. Gastroenterol. Hepatol 2009, 24, 652–657.
  55. Yao, Y.; Suo, A.L.; Li, Z.F.; Liu, L.Y.; Tian, T.; Ni, L.; Zhang, W.G.; Nan, K.J.; Song, T.S.; Huang, C. MicroRNA profiling of human gastric cancer. Mol. Med. Report 2009, 2, 963–970.
  56. Cho, W.C. Great potential of miRNAs as predictive and prognostic markers for cancer. Expert Rev. Mol. Diagn 2012, 12, 315–318.
  57. Cho, W.C. MicroRNAs as therapeutic targets and their potential applications in cancer therapy. Expert Opin. Ther. Targets 2012, 16, 747–759.
  58. Motoyama, K.; Inoue, H.; Mimori, K.; Tanaka, F.; Kojima, K.; Uetake, H.; Sugihara, K.; Mori, M. Clinicopathological and prognostic significance of PDCD4 and microRNA-21 in human gastric cancer. Int. J. Oncol 2010, 36, 1089–1095.
  59. Nishida, N.; Mimori, K.; Fabbri, M.; Yokobori, T.; Sudo, T.; Tanaka, F.; Shibata, K.; Ishii, H.; Doki, Y.; Mori, M. MicroRNA-125a-5p is an independent prognostic factor in gastric cancer and inhibits the proliferation of human gastric cancer cells in combination with trastuzumab. Clin. Cancer Res 2011, 17, 2725–2733.
  60. Zheng, B.; Liang, L.; Huang, S.; Zha, R.; Liu, L.; Jia, D.; Tian, Q.; Wang, Q.; Wang, C.; Long, Z.; et al. MicroRNA-409 suppresses tumor cell invasion and metastasis by directly targeting radixin in gastric cancers. Oncogene 2011, doi:10.1038/onc.2011.581.
  61. Liu, K.; Li, G.; Fan, C.; Diao, Y.; Wu, B.; Li, J. Increased expression of microRNA-221 in gastric cancer and its clinical significance. J. Int. Med. Res 2012, 40, 467–474.
  62. Inoue, T.; Iinuma, H.; Ogawa, E.; Inaba, T.; Fukushima, R. Clinicopathological and prognostic significance of microRNA-107 and its relationship to DICER1 mRNA expression in gastric cancer. Oncol. Rep 2012, 27, 1759–1764.
  63. Li, X.; Zhang, Y.; Ding, J.; Wu, K.; Fan, D. Survival prediction of gastric cancer by a seven-microRNA signature. Gut 2010, 59, 579–585.
  64. Ueda, T.; Volinia, S.; Okumura, H.; Shimizu, M.; Taccioli, C.; Rossi, S.; Alder, H.; Liu, C.G.; Oue, N.; Yasui, W.; et al. Relation between microRNA expression and progression and prognosis of gastric cancer: a microRNA expression analysis. Lancet Oncol 2010, 11, 136–146.
  65. Tsai, K.W.; Liao, Y.L.; Wu, C.W.; Hu, L.Y.; Li, S.C.; Chan, W.C.; Ho, M.R.; Lai, C.H.; Kao, H.W.; Fang, W.L.; et al. Aberrant expression of miR-196a in gastric cancers and correlation with recurrence. Genes Chromosomes Cancer 2012, 51, 394–401.
  66. Chen, X.; Ba, Y.; Ma, L.; Cai, X.; Yin, Y.; Wang, K.; Guo, J.; Zhang, Y.; Chen, J.; Guo, X.; 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.
  67. Gilad, S.; Meiri, E.; Yogev, Y.; Benjamin, S.; Lebanony, D.; Yerushalmi, N.; Benjamin, H.; Kushnir, M.; Cholakh, H.; Melamed, N.; et al. Serum microRNAs are promising novel biomarkers. PLoS One 2008, 3, e3148.
  68. Mitchell, P.S.; Parkin, R.K.; Kroh, E.M.; Fritz, B.R.; Wyman, S.K.; Pogosova-Agadjanyan, E.L.; Peterson, A.; Noteboom, J.; O’Briant, K.C.; Allen, A.; et al. Circulating microRNAs as stable blood-based markers for cancer detection. Proc. Natl. Acad. Sci. USA 2008, 105, 10513–10518.
  69. Yu, D.C.; Li, Q.G.; Ding, X.W.; Ding, Y.T. Circulating microRNAs: Potential biomarkers for cancer. Int. J. Mol. Sci 2011, 12, 2055–2063.
  70. Brase, J.C.; Wuttig, D.; Kuner, R.; Sultmann, H. Serum microRNAs as non-invasive biomarkers for cancer. Mol. Cancer 2010, 9, 306.
  71. Kosaka, N.; Iguchi, H.; Ochiya, T. Circulating microRNA in body fluid: A new potential biomarker for cancer diagnosis and prognosis. Cancer Sci 2010, 101, 2087–2092.
  72. 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, doi:10.1007/s00432-012-1244-9.
  73. Tsujiura, M.; Ichikawa, D.; Komatsu, S.; Shiozaki, A.; Takeshita, H.; Kosuga, T.; Konishi, H.; Morimura, R.; Deguchi, K.; Fujiwara, H.; et al. Circulating microRNAs in plasma of patients with gastric cancers. Br. J. Cancer 2010, 102, 1174–1179.
  74. Liu, R.; Zhang, C.; Hu, Z.; Li, G.; Wang, C.; Yang, C.; Huang, D.; Chen, X.; Zhang, H.; Zhuang, R.; 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.
  75. Konishi, H.; Ichikawa, D.; Komatsu, S.; Shiozaki, A.; Tsujiura, M.; Takeshita, H.; Morimura, R.; Nagata, H.; Arita, T.; Kawaguchi, T.; et al. Detection of gastric cancer-associated microRNAs on microRNA microarray comparing pre- and post-operative plasma. Br. J. Cancer 2012, 106, 740–747.
  76. Liu, H.; Zhu, L.; Liu, B.; Yang, L.; Meng, X.; Zhang, W.; Ma, Y.; Xiao, H. Genome-wide microRNA profiles identify miR-378 as a serum biomarker for early detection of gastric cancer. Cancer Lett 2012, 316, 196–203.
  77. Zhang, X.; Cui, L.; Ye, G.; Zheng, T.; Song, H.; Xia, T.; Yu, X.; Xiao, B.; Le, Y.; Guo, J. Gastric juice microRNA-421 is a new biomarker for screening gastric cancer. Tumor Biol 2012, doi:10.1007/s13277-012-0497-x.
  78. Chen, C.; Ridzon, D.A.; Broomer, A.J.; Zhou, Z.; Lee, D.H.; Nguyen, J.T.; Barbisin, M.; Xu, N.L.; Mahuvakar, V.R.; Andersen, M.R.; et al. Real-time quantification of microRNAs by stem-loop RT-PCR. Nucleic Acids Res 2005, 33, e179.
  79. Lodes, M.J.; Caraballo, M.; Suciu, D.; Munro, S.; Kumar, A.; Anderson, B. Detection of cancer with serum miRNAs on an oligonucleotide microarray. PLoS One 2009, 4, e6229.
  80. Kozomara, A.; Griffiths-Jones, S. MiRBase: Integrating microRNA annotation and deep-sequencing data. Nucleic Acids Res 2011, 39, D152–D157.
  81. Guo, J.X.; Tao, Q.S.; Lou, P.R.; Chen, X.C.; Chen, J.; Yuan, G.B. MiR-181b as a potential molecular target for anticancer therapy of gastric neoplasms. Asian Pac. J. Cancer Prev 2012, 13, 2263–2267.
  82. Xu, Y.; Sun, J.; Xu, J.; Li, Q.; Guo, Y.; Zhang, Q. MiR-21 is a promising novel biomarker for lymph node metastasis in patients with gastric cancer. Gastroenterol. Res. Pract 2012, 2012, 640168.
  83. Osawa, S.; Shimada, Y.; Sekine, S.; Okumura, T.; Nagata, T.; Fukuoka, J.; Tsukada, K. MicroRNA profiling of gastric cancer patients from formalin-fixed paraffin-embedded samples. Oncology Lett 2011, 2, 613–619.
  84. Yu, B.Q.; Su, L.P.; Li, J.F.; Cai, Q.; Yan, M.; Chen, X.H.; Yu, Y.Y.; Gu, Q.L.; Zhu, Z.G.; Liu, B.Y. Microrna expression signature of gastric cancer cells relative to normal gastric mucosa. Mol. Med. Report 2012, 6, 821–826.
  85. Li, B.S.; Zhao, Y.L.; Guo, G.; Li, W.; Zhu, E.D.; Luo, X.; Mao, X.H.; Zou, Q.M.; Yu, P.W.; Zuo, Q.F.; et al. Plasma microRNAs, miR-223, miR-21 and miR-218, as novel potential biomarkers for gastric cancer detection. PLoS One 2012, 7, e41629.
Table 1. miRNAs in the tissue as diagnostic markers for gastric cancer.

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Table 1. miRNAs in the tissue as diagnostic markers for gastric cancer.
SignificanceMicroRNAsCorrelation with GC
Up-regulatedmiR-21 [,8], miR-27a [49], mir-34b, mir-34c and mir-128a [50]-
miR-20b, miR-20a, miR-17, miR-106a, miR-18a, miR-106b, miR-18b, miR-421, miR-340 *, miR-19a and miR-658 [51], miR-223, miR-106b, miR-147, miR-34a, miR-130b *, miR-17, miR-98, miR-616 *, miR-181a-2 *, miR-185, miR-1259, miR-601, miR-196a *, miR-221 *, miR-302f, miR-340 *, miR-337-3p, miR-520c-3p, miR-575 and miR-138 [52], miR-181b [81]

Down-regulatedmir-128b, mir-129 and mir-148 [50]-

Correlated with prognosismiR-21[53], miR-125b, miR-199a, miR-100 [59], miR-451 [38] and miR-125a-5p [54]Correlated with tumor size and depth
miR-451 [38] and miR-125a-5p [54]Correlated with tumor invasion, liver metastasis
miR-409-3p [55] and miR-221 [56], miR-125b, miR-199a, miR-100 [59] and miR-21 [82]Correlated with lymph node metastasis
miR-107 [57] miR-10b, miR-21, miR-223, miR-338, let-7a, miR-30a-5p, miR-126 [58], miR-125b, miR-199a, miR-100 [59], miR-185, miR-106b, miR-425, miR-106a, miR-20a, miR-21, miR-20b, miR-200a, miR-15a, miR-103, miR-107, miR-16, miR-34a [83] and miR-93 [84]Correlated with OS
miR-196a [60]Correlated with cellular expression status
Table 2. Circulating miRNAs in the serum as diagnostic markers for gastric cancer.

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Table 2. Circulating miRNAs in the serum as diagnostic markers for gastric cancer.
ReferencesStudy designSample SizeTechnologyPromising circulating miRNAs
Tsai et al. [60]Different disease status and relapse72 GC patientsQuantitative RT-PCRmiR-196a
Wang et al. [67]Tumor vs. normal30 GC patients vs. 39 normal controlsQuantitative RT-PCRmiR-21
Tsujiura et al. [68]Tumor vs. normalScreening: eight samples and associated tissues
Validation: 69 GC patients vs. 30 healthy controls
Quantitative RT-PCRmiR-17-5p, miR-21, miR-106a, miR-106b and let-7a
Liu et al. [69]Tumor vs. normalScreening: 20 GC patients vs. 20 healthy controls
Validation: 164 GC patients vs. 127 healthy controls
Solexa Sequencing
Quantitative RT-PCR
miR-1, miR-20a, miR-27a, miR-34 and miR-423-5p Correlated with tumor stage
Konishi et al. [70]Pre-operative vs. postoperativeScreening: three GC patients
Validation: 56 GC patients vs. 30 healthy controls
Microarray analysis
Quantitative RT-PCR
miR-451 and miR-486
Liu et al. [71]Tumor vs. normalScreening: seven GC patients vs. 10 healthy controls Validation: 40 GC patients vs. 41 healthy controlsMicroarray analysis
Quantitative RT-PCR
miR-378
Li et al. [85]Tumor vs. normal10 GC patients vs. 10 healthy controlsQuantitative RT-PCRmiR-223, miR-21 and miR-218
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