Back to Journals » OncoTargets and Therapy » Volume 8

Single-nucleotide polymorphisms of microRNA processing machinery genes are associated with risk for gastric cancer

Authors Xie Y, Wang Y, Zhao Y, Guo Z

Received 12 December 2014

Accepted for publication 16 February 2015

Published 4 March 2015 Volume 2015:8 Pages 567—571

DOI https://doi.org/10.2147/OTT.S79150

Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 3

Editor who approved publication: Dr Jianmin Xu



Ying Xie, Yingnan Wang, Yuefei Zhao, Zhanjun Guo

Department of Gastroenterology and Hepatology, The Fourth Hospital of Hebei Medical University, Shijiazhuang, People’s Republic of China

Abstract: Recent studies demonstrate that microRNA-related single-nucleotide polymorphisms (miR-SNPs) are associated with the development of numerous human cancers. In this study, we investigated six miR-SNPs in microRNA processing machinery genes, including rs11077 of the XPO5 gene, rs14035 of the RAN gene, rs3742330 of the Dicer gene, rs9623117 of the TNRC6B gene, rs197412 of the GEMIN3 gene, and rs2740348 of the GEMIN4 gene, in gastric cancer patients and subsequently evaluated their potential roles in gastric cancer risk in a case control study. The results indicate that the C/C genotype of rs14035 from RAN, the A/A genotype of rs3742330 from Dicer, and the T/T genotype of rs9623117 from TNRC6B are significantly associated with gastric cancer risk. In conclusion, these miR-SNPs can be used as predictive biomarkers in gastric cancer.

Keywords: cancer risk, gastric cancer, miR-SNPs

Introduction

Gastric cancer (GC) is the fourth-most-common cancer and the second leading cause of cancer-related deaths worldwide;1,2 in addition, nearly two-thirds of GCs occur in developing regions.3 As a multifactorial disease, both environmental factors and genetic factors contribute to the etiology of this disease.4,5 Although much treatment progress has been achieved in recent years, the prognosis of GC remains poor due to the delay in diagnosis.6 MicroRNAs (miRNAs) are RNA molecules with lengths of ~22 nucleotides; they can act as posttranscriptional regulators in mRNA expression, and they regulate a variety of physiological and developmental processes, including the development and progression of numerous cancers.713 In GC, miRNAs can serve as biomarkers for both diagnosis and therapeutic targets.1417

In miRNA processing, long primary transcripts of miRNAs (pre-miRNAs) are synthesized by RNase II in the nucleus, and they are cut into an ~70 nt hairpin precursor by RNase III Drosha and by the double-stranded RNA-binding protein DiGeorge syndrome critical region 8 (DGCR8). These precursors are exported to the cytoplasm, are processed by exportin-5 (XPO5) and RAN-GTPase (RAN), and are further diced into ~22 nt miRNA duplexes by the RNase III Dicer gene, which cooperates with the transactivation response RNA-binding protein and the Argonaute protein family. MiRNA duplexes are then assembled into the miRNA-induced silencing complex (miRISC), which contains GEMIN3 and GEMIN4. The miRISC will select one strand as the mature miRNA, and it guides the mature miRNAs to their target mRNA sites.1823 MiRNA-related single nucleotide polymorphisms (miR-SNPs), which are defined as single-nucleotide polymorphisms (SNPs) in miRNA genes at the miRNA binding site and in miRNA processing machinery, can modulate miRNA and target gene expression to influence cancer development, promote therapeutic efficacy, and affect a patient’s prognosis.2326 The miRNA machinery genes are linked to the development, progression, and prognosis of several cancer types, including ovarian and colorectal cancers, melanoma, and T-cell lymphoma.2730 However, the role of the miRNA processing machinery genes in GC remains uncertain.

In the present study, we genotyped six miR-SNPs in the miRNA processing machinery genes, including XPO5 (rs11077), RAN (rs14035), Dicer (rs3742330), TNRC6B (rs9623117), GEMIN3 (rs197412), and GEMIN4 (rs2740348) in GC patients to evaluate the relationships of these genes with risk for development of GC.

Materials and methods

Sample collection and DNA extraction

Blood samples were collected from GC patients who underwent GC resection at the Department of General Surgery at the Fourth Hospital of Hebei Medical University from 2007–2008. Blood samples were also collected from normal controls without a history of any cancer. Genomic DNA was immediately extracted using the Wizard® Genomic DNA Purification Kit (Promega Corporation, Fitchburg, WI, USA) and was stored at −20°C. All procedures were supervised and approved by the Human Tissue Research Committee of the Fourth Hospital of Hebei Medical University. Written consent was obtained from all the patients and healthy controls enrolled in this study.

Genotyping of miR-SNPs

The miR-SNPs of the miRNA processing gene, including XPO5 (rs11077), RAN (rs14035), Dicer (rs3742330), TNRC6B (rs9623117), GEMIN3 (rs197412), and GEMIN4 (rs2740348), according to the National Center for Biotechnology Information (NCBI) SNP database (http://www.ncbi.nlm.nih.gov/snp/), were genotyped using the polymerase chain reaction (PCR)–ligase detection reaction assay with the primers and probes listed in Table 1. PCR was performed with the PCR Master Mix Kit according to the manufacturer’s instructions (Promega, Madison, WI, USA). Ligation was performed using the different probes that were matched to the miR-SNPs, and the ligated products were separated using the ABI PRISM Genetic Analyzer 3730XL (Applied Biosystems, Foster City, CA, USA) to access the length differences of the ligated products.

Table 1 All the primers and probes used for genotyping of miR-SNPs
Notes: F: represents forward primer for PCR; R: represents reverse primer for PCR; S1 and S2 represent probes match to different allele of the SNP; S3 represents probes downstream of the SNP.
Abbreviations: NCBI, National Center for Biotechnology Information; PCR, polymerase chain reaction; SNP, single-nucleotide polymorphism.

Statistical analysis

The χ2 test was applied to analyze dichotomous variables, such as the presence or absence of an individual SNP in patients and healthy controls. The odds ratios and 95% confidence intervals (CI) were calculated using an unconditional logistic regression model. All of the statistical analyses were performed with the SPSS version 18.0 software package (IBM Corporation, Armonk, NY, USA). A P-value <0.05 was considered statistically significant.

Results

A total of 137 GC patients and 142 healthy controls were included in this study. The clinical characteristics of the cases and controls are listed in Table 2. Six miR-SNPs were detected from the blood samples of the healthy controls and GC patients.

Table 2 Clinical characteristics in patients with gastric cancer and controls

When individual SNPs were compared between GC patients and controls in terms of their distribution frequency, statistically significant increases for the C/C genotype of rs14035 in the RAN gene (95% CI: 1.601–14.925; P=0.002), the T/T genotype of rs9623117 in the TNRC6B gene (95% CI: 0.03–0.608; P=0.003), and the A/A genotype of rs3742330 in the Dicer gene (95% CI: 1.223–3.178; P=0.005) were observed in GC patients. These results indicate that the carriers of these alleles are susceptible to GC (Table 3).

Table 3 miR-SNPs frequency difference between patients with gastric cancer and controls
Abbreviations: CI, confidence interval; miR-SNP, microRNA-related single-nucleotide polymorphism; OR, odds ratio.

Discussion

The miR-SNPs in RAN, Dicer, and TNRC6B were associated with the carcinogenesis of GC in our analysis. To our knowledge, this is the first report to indicate that the SNP sites in the miRNA processing machinery genes have predictive value for determining the incidence of GC.

RAN is a member of the Ras superfamily of GTPases and is essential for the translocation of pre-miRNAs from the nucleus to the cytoplasm. XPO5 binds to pre-miRNA and RAN-GTPase in the nucleus (via the XPO5RAN GTP–pre-miRNA heteroternary complex) to mediate the nuclear export of pre-miRNA in a RAN GTP-dependent manner.31 Disruption of pre-miRNA nucleocytoplasmic transport would impair the production of mature miRNAs in cancer cells. The fact that RAN is overexpressed in some cancer cell lines, including colon cancer, implies its role in tumor transformation; moreover, RAN was reported to suppress the activation of C-Jun-NH2-kinase and inhibit the apoptosis induced by an anticancer drug.32,33 The rs14035 located in RAN might alter RAN expression, so as to initiate carcinogenesis by modulating the production of mature miRNAs.

Dicer was also implicated in the oncogenic process of several cancers, but the data were controversial; downregulated Dicer expression has been identified in lung cancer, ovarian cancer, nasopharyngeal cancers, breast cancer, and esophageal cancer, whereas upregulated Dicer expression was found in lung adenocarcinoma, colorectal cancer, and primary cutaneous T-cell lymphomas.27,3440 The mechanism underlying how the rs3742330 SNP modified the GC risk remains unclear; the location of this SNP in the 3′-untranslated region of Dicer might potentially influence the stability and expression of the gene.

TNRC6B (or KIAA1093), localized on the mRNA-degrading cytoplasmic P bodies, is one of the three Argonaute-interacting protein paralogs in vertebrates. They assist in the formation of miRNA ribonucleoparticles or miRISCs, so as to mediate miRNA-guided mRNA cleavage.16,4144 The T/T genotype of rs9623117 in TNRC6B has been found to be associated with prostate cancer risk. Alterations in TNRC6B gene expression due to genetic variations of rs9623117 might perturb the levels of miRNA species normally under its control, thus contributing to carcinogenesis.45

The frequency distribution of these six SNPs and the patients’ clinical characteristics (including their sex, age, and tumor stage) do not appear to be associated, as determined by our analysis (data not shown). These six miR-SNPs were analyzed for their relationship with postoperative survival in 95 patients for whom 3-year follow-up data were available. It was found that rs2740348 showed a marginally statistically significant association with survival (P=0.06; our unpublished data). These findings should be validated with a larger sample size.

Although the results of this study require further validation among a larger GC cohort, as well as in laboratory-based functional studies, our data are encouraging because they demonstrate that miR-SNPs can be used to predict the risk for developing GC.

Acknowledgment

This work was supported by the Key basic research program of Hebei (14967713D).

Author contributions

All authors made substantial contributions to data generation and analysis, drafting or critical revision of the manuscript, and approval for the final version to be published.

Disclosure

The authors report no conflicts of interest in this work.


References

1.

Parkin DM, Bray FI, Devesa SS. Cancer burden in the year 2000. The global picture. Eur J Cancer. 2001;37 Suppl 8:S4–S66.

2.

Parkin DM. International variation. Oncogene. 2004;23(38):6329–6340.

3.

Stadtländer CT, Waterbor JW. Molecular epidemiology, pathogenesis and prevention of gastric cancer. Carcinogenesis. 1999;20(12):2195–2208.

4.

Crew KD, Neugut AI. Epidemiology of gastric cancer. World J Gastroenterol. 2006;12(3):354–362.

5.

Forman D, Burley VJ. Gastric cancer: global pattern of the disease and an overview of environmental risk factors. Best Pract Res Clin Gastroenterol. 2006;20(4):633–649.

6.

Xia J, Guo X, Yan J, Deng K. The role of miR-148a in gastric cancer. J Cancer Res Clin Oncol. 2014;140(9):1451–1456.

7.

Wang C, Guo Z, Wu C, Li Y, Kang S. A polymorphism at the miR-502 binding site in the 3′ untranslated region of the SET8 gene is associated with the risk of epithelial ovarian cancer. Cancer Genet. 2012;205(7–8):373–376.

8.

Guo Z, Wang H, Li Y, Li B, Li C, Ding C. A microRNA-related single nucleotide polymorphism of the XPO5 gene is associated with survival of small cell lung cancer patients. Biomed Rep. 2013;1(4):545–548.

9.

Li R, Zhang L, Jia L, et al. MicroRNA-143 targets Syndecan-1 to repress cell growth in melanoma. PLoS One. 2014;9(4):e94855.

10.

Parlayan C, Ikeda S, Sato N, Sawabe M, Muramatsu M, Arai T. Association analysis of single nucleotide polymorphisms in miR-146a and miR-196a2 on the prevalence of cancer in elderly Japanese: a case-control study. Asian Pac J Cancer Prev. 2014;15(5):2101–2107.

11.

Peng Y, Liu YM, Li LC, Wang LL, Wu XL. MicroRNA-338 inhibits growth, invasion and metastasis of gastric cancer by targeting NRP1 expression. PLoS One. 2014;9(4):e94422.

12.

Wojcicka A, de la Chapelle A, Jazdzewski K. MicroRNA-related sequence variations in human cancers. Hum Genet. 2014;133(4):463–469.

13.

Xie Y, Diao L, Zhang L, Liu C, Xu Z, Liu S. A miR-SNP of the KRT81 gene is associated with the prognosis of non-Hodgkin’s lymphoma. Gene. 2014;539(2):198–202.

14.

Tie J, Pan Y, Zhao L, et al. MiR-218 inhibits invasion and metastasis of gastric cancer by targeting the Robo1 receptor. PLoS Genet. 2010;6(3):e1000879.

15.

Guo B, Li J, Liu L, et al. Dysregulation of miRNAs and their potential as biomarkers for the diagnosis of gastric cancer. Biomed Rep. 2013;1(6):907–912.

16.

Chu D, Zhao Z, Li Y, et al. Increased microRNA-630 expression in gastric cancer is associated with poor overall survival. PLoS One. 2014;9(3):e90526.

17.

Wu Q, Yang Z, An Y, et al. MiR-19a/b modulate the metastasis of gastric cancer cells by targeting the tumour suppressor MXD1. Cell Death Dis. 2014;5:e1144.

18.

Lee Y, Ahn C, Han J, et al. The nuclear RNase III Drosha initiates microRNA processing. Nature. 2003;425(6956):415–419.

19.

Yi R, Qin Y, Macara IG, Cullen BR. Exportin-5 mediates the nuclear export of pre-microRNAs and short hairpin RNAs. Genes Dev. 2003;17(24):3011–3016.

20.

Bartel DP. MicroRNAs: genomics, biogenesis, mechanism, and function. Cell. 2004;116(2):281–297.

21.

Cullen BR. Transcription and processing of human microRNA precursors. Mol Cell. 2004;16(6):861–865.

22.

Chendrimada TP, Gregory RI, Kumaraswamy E, et al. TRBP recruits the Dicer complex to Ago2 for microRNA processing and gene silencing. Nature. 2005;436(7051):740–744.

23.

Ryan BM, Robles AI, Harris CC. Genetic variation in microRNA networks: the implications for cancer research. Nat Rev Cancer. 2010;10(6):389–402.

24.

Boni V, Zarate R, Villa JC, et al. Role of primary miRNA polymorphic variants in metastatic colon cancer patients treated with 5-fluorouracil and irinotecan. Pharmacogenomics J. 2011;11(6):429–436.

25.

Campayo M, Navarro A, Viñolas N, et al. A dual role for KRT81: a miR-SNP associated with recurrence in non-small-cell lung cancer and a novel marker of squamous cell lung carcinoma. PLoS One. 2011;6(7):e22509.

26.

de Larrea CF, Navarro A, Tejero R, et al. Impact of MiRSNPs on survival and progression in patients with multiple myeloma undergoing autologous stem cell transplantation. Clin Cancer Res. 2012;18(13):3697–3704.

27.

Merritt WM, Lin YG, Han LY, et al. Dicer, Drosha, and outcomes in patients with ovarian cancer. N Engl J Med. 2008;359(25):2641–2650.

28.

Melo SA, Ropero S, Moutinho C, et al. A TARBP2 mutation in human cancer impairs microRNA processing and DICER1 function. Nat Genet. 2009;41(3):365–370.

29.

Ma Z, Swede H, Cassarino D, Fleming E, Fire A, Dadras SS. Up-regulated Dicer expression in patients with cutaneous melanoma. PLoS One. 2011;6(6):e20494.

30.

Valencak J, Schmid K, Trautinger F, et al. High expression of Dicer reveals a negative prognostic influence in certain subtypes of primary cutaneous T cell lymphomas. J Dermatol Sci. 2011;64(3):185–190.

31.

Lund E, Güttinger S, Calado A, Dahlberg JE, Kutay U. Nuclear export of microRNA precursors. Science. 2004;303(5654):95–98.

32.

Woo IS, Jang HS, Eun SY, et al. Ran suppresses paclitaxel-induced apoptosis in human glioblastoma cells. Apoptosis. 2008;13(10):1223–1231.

33.

Honma K, Takemasa I, Matoba R, et al. Screening of potential molecular targets for colorectal cancer therapy. Int J Gen Med. 2009;2:243–257.

34.

Garzon R, Fabbri M, Cimmino A, Calin GA, Croce CM. MicroRNA expression and function in cancer. Trends Mol Med. 2006;12(12):580–587.

35.

Karube Y, Tanaka H, Osada H, et al. Reduced expression of Dicer associated with poor prognosis in lung cancer patients. Cancer Sci. 2005;96(2):111–115.

36.

Sugito N, Ishiguro H, Kuwabara Y, et al. RNASEN regulates cell proliferation and affects survival in esophageal cancer patients. Clin Cancer Res. 2006;12(24):7322–7328.

37.

Grelier G, Voirin N, Ay AS, et al. Prognostic value of Dicer expression in human breast cancers and association with the mesenchymal phenotype. Br J Cancer. 2009;101(4):673–683.

38.

Guo X, Liao Q, Chen P, et al. The microRNA-processing enzymes: Drosha and Dicer can predict prognosis of nasopharyngeal carcinoma. J Cancer Res Clin Oncol. 2012;138(1):49–56.

39.

Chiosea S, Jelezcova E, Chandran U, et al. Overexpression of Dicer in precursor lesions of lung adenocarcinoma. Cancer Res. 2007;67(5):2345–2350.

40.

Faber C, Horst D, Hlubek F, Kirchner T. Overexpression of Dicer predicts poor survival in colorectal cancer. Eur J Cancer. 2011;47(9):1414–1419.

41.

Caudy AA, Myers M, Hannon GJ, Hammond SM. Fragile X-related protein and VIG associate with the RNA interference machinery. Genes Dev. 2002;16(19):2491–2496.

42.

Meister G, Landthaler M, Peters L, et al. Identification of novel argonaute-associated proteins. Curr Biol. 2005;15(23):2149–2155.

43.

Chu CY, Rana TM. Translation repression in human cells by microRNA-induced gene silencing requires RCK/p54. PLoS Biol. 2006;4(7):e210.

44.

Baillat D, Shiekhattar R. Functional dissection of the human TNRC6 (GW182-related) family of proteins. Mol Cell Biol. 2009;29(15):4144–4155.

45.

Sun J, Zheng SL, Wiklund F, et al. Sequence variants at 22q13 are associated with prostate cancer risk. Cancer Res. 2009;69(1):10–15.

Creative Commons License © 2015 The Author(s). This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution - Non Commercial (unported, v3.0) License. By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms.