Login Register Cart 0
Research Article

Significant Association of miR-605 rs2043556 with Susceptibility to Breast Cancer

Author(s): Arezu Kazemi and Sadeq Vallian*

Volume 9, Issue 2, 2020

Page: [133 - 141] Pages: 9

DOI: 10.2174/2211536608666190926155149

Open Access Journals Promotions 2
Abstract

Background: MicroRNAs (miRNAs) are noncoding RNA molecules, which directly regulate gene expression. It has been documented that single nucleotide polymorphisms in miRNA genes could alter the regulation of miRNA expression and function.

Objective: In this study, the allele and genotype frequency of miR-605 rs2043556 and its association with breast cancer were investigated in the Iranian population.

Methods: Genotyping was performed in 162 females affected with breast cancer and 180 healthy individuals. Genotyping was performed using Restriction Fragment Length Polymorphism (RFLP) followed by Sanger sequencing.

Results: The data showed the presence of Hardy Weinberg equilibrium (HWE) for this marker in the Iranian population. Allelic frequency for A and G allele was 0.75 and 0.25, respectively. Odd ratios for the association between miR-605 rs2043556 AG/GG genotypes was 3.86 with p-value= 0.

Conclusion: The results indicated an increased risk for breast cancer susceptibility for miR-605 rs2043556 in the Iranian population.

Keywords: Breast neoplasms, microRNA, MIRN605, polymorphism, single nucleotide, genotype.

« Previous Next »
Graphical Abstract

[1]
Tsai HP, Huang SF, Li CF, Chien HT, Chen SC. Differential microRNA expression in breast cancer with different onset age. PLoS One 2018; 13(1) e0191195
[http://dx.doi.org/10.1371/journal.pone.0191195] [PMID: 29324832]
[2]
Peng Y, Croce CM. The role of microRNAs in human cancer. Signal Transduct Target Ther 2016; 1: 15004.
[http://dx.doi.org/10.1038/sigtrans.2015.4] [PMID: 29263891]
[3]
Ryan BM, Robles AI, Harris CC. Genetic variation in microRNA networks: the implications for cancer research. Nat Rev Cancer 2010; 10(6): 389-402.
[http://dx.doi.org/10.1038/nrc2867] [PMID: 20495573]
[4]
Mishra PJ. The miRNA-drug resistance connection: a new era of personalized medicine using noncoding RNA begins. Pharmacogenomics 2012; 13(12): 1321-4.
[http://dx.doi.org/10.2217/pgs.12.121] [PMID: 22966880]
[5]
Gong J, Tong Y, Zhang HM, et al. Genome-wide identification of SNPs in microRNA genes and the SNP effects on microRNA target binding and biogenesis. Hum Mutat 2012; 33(1): 254-63.
[http://dx.doi.org/10.1002/humu.21641] [PMID: 22045659]
[6]
Zhang MW, Jin MJ, Yu YX, et al. Associations of lifestyle-related factors, HSA-miR-149 and HSA-miR-605 gene polymorphisms with gastrointestinal cancer risk. Mol Carcinog 2012; 51(Suppl. 1): E21-31.
[http://dx.doi.org/10.1002/mc.20863] [PMID: 21976437]
[7]
Xiao J, Lin H, Luo X, Luo X, Wang Z. miR-605 joins p53 network to form a p53: miR-605: Mdm2 positive feedback loop in response to stress. EMBO J 2011; 30(3): 524-32.
[http://dx.doi.org/10.1038/emboj.2010.347] [PMID: 21217645]
[8]
Zhou C-H, Zhang X-P, Liu F, Wang W. Involvement of miR-605 and miR-34a in the DNA damage response promotes apoptosis induction. Biophys J 2014; 106(8): 1792-800.
[http://dx.doi.org/10.1016/j.bpj.2014.02.032] [PMID: 24739178]
[9]
Li J, Tian F, Li D, et al. MiR-605 represses PSMD10/Gankyrin and inhibits intrahepatic cholangiocarcinoma cell progression. FEBS Lett 2014; 588(18): 3491-500.
[http://dx.doi.org/10.1016/j.febslet.2014.08.008] [PMID: 25131931]
[10]
Sherry ST, Ward MH, Kholodov M, et al. dbSNP: the NCBI database of genetic variation. Nucleic Acids Res 2001; 29(1): 308-11.
[http://dx.doi.org/10.1093/nar/29.1.308] [PMID: 11125122]
[11]
Hu Y, Yu C-Y, Wang J-L, Guan J, Chen H-Y, Fang J-Y. MicroRNA sequence polymorphisms and the risk of different types of cancer. Sci Rep 2014; 4: 3648.
[http://dx.doi.org/10.1038/srep03648] [PMID: 24413317]
[12]
Id Said B, Malkin D. A functional variant in miR-605 modifies the age of onset in Li-Fraumeni syndrome. Cancer Genet 2015; 208(1-2): 47-51.
[http://dx.doi.org/10.1016/j.cancergen.2014.12.003] [PMID: 25683625]
[13]
Poltronieri-Oliveira AB, Madeira FF, Nunes DBSM, Rodrigues GH, Lopes BC, Manoel-Caetano FS, et al. Polymorphisms of miR-196a2 (rs11614913) and miR-605 (rs2043556) confer susceptibility to gastric cancer. Gene Rep 2017; 7: 154-63.
[http://dx.doi.org/10.1016/j.genrep.2017.04.006]
[14]
Miao L, Wang L, Zhu L, Du J, Zhu X, Niu Y, et al. Association of microRNA polymorphisms with the risk of head and neck squamous cell carcinoma in a Chinese population: a case-control study. Chin J Cancer 2016; 77(1): 35.
[http://dx.doi.org/10.1186/s40880-016-0136-9]
[15]
Yin Z, Li H, Cui Z, et al. Polymorphisms in pre-miRNA genes and cooking oil fume exposure as well as their interaction on the risk of lung cancer in a Chinese nonsmoking female population. OncoTargets Ther 2016; 9: 395-401.
[http://dx.doi.org/10.2147/OTT.S96870] [PMID: 26855588]
[16]
Zhang M, Jin M, Yu Y, et al. Associations of miRNA polymorphisms and female physiological characteristics with breast cancer risk in Chinese population. Eur J Cancer Care (Engl) 2012; 21(2): 274-80.
[http://dx.doi.org/10.1111/j.1365-2354.2011.01308.x] [PMID: 22074121]
[17]
Chen Q-H, Wang Q-B, Zhang B. Ethnicity modifies the association between functional microRNA polymorphisms and breast cancer risk: a HuGE meta-analysis. Tumour Biol 2014; 35(1): 529-43.
[http://dx.doi.org/10.1007/s13277-013-1074-7] [PMID: 23982873]
[18]
Morales S, De Mayo T, Gulppi FA, et al. Genetic Variants in pre-miR-146a, pre-miR-499, pre-miR-125a, pre-miR-605, and pri-miR-182 are associated with breast cancer susceptibility in a South American population. Genes (Basel) 2018; 9(9) E427
[http://dx.doi.org/10.3390/genes9090427] [PMID: 30135399]
[19]
Danesh H, Hashemi M, Bizhani F, Hashemi SM, Bahari G. Association study of miR-100, miR-124-1, miR-218-2, miR-301b, miR-605, and miR-4293 polymorphisms and the risk of breast cancer in a sample of Iranian population. Gene 2018; 647: 73-8.
[http://dx.doi.org/10.1016/j.gene.2018.01.025] [PMID: 29317318]
[20]
Moazeni-Roodi A, Ghavami S, Hashemi M. Lack of Association between miR-605 rs2043556 polymorphism and overall cancer risk: a meta-analysis of case-control studies. MicroRNA 2019; 8(2): 94-100.
[http://dx.doi.org/10.2174/2211536608666181204110508] [PMID: 30514199]
[21]
Fazeli Z, Vallian S. Molecular phylogenetic study of the Iranians based on polymorphic markers. Gene 2013; 512(1): 123-6.
[http://dx.doi.org/10.1016/j.gene.2012.09.089] [PMID: 23073556]
[22]
Miller SA, Dykes DD, Polesky HF. A simple salting out procedure for extracting DNA from human nucleated cells. Nucleic Acids Res 1988; 16(3): 1215.
[http://dx.doi.org/10.1093/nar/16.3.1215] [PMID: 3344216]
[23]
Rychlik W. OLIGO 7 primer analysis software. Methods Mol Biol 2007; 402: 35-60.
[http://dx.doi.org/10.1007/978-1-59745-528-2_2] [PMID: 17951789]
[24]
Untergasser A, Cutcutache I, Koressaar T, Ye J, Faircloth BC, Remm M, et al. Primer3—new capabilities and interfaces. Nucleic Acids Res 2012; 40(15) e115
[25]
Liu K, Muse SV. PowerMarker: an integrated analysis environment for genetic marker analysis. Bioinformatics 2005; 21(9): 2128-9.
[http://dx.doi.org/10.1093/bioinformatics/bti282] [PMID: 15705655]
[26]
Charan J, Biswas T. How to calculate sample size for different study designs in medical research? Indian J Psychol Med 2013; 35(2): 121-6.
[http://dx.doi.org/10.4103/0253-7176.116232] [PMID: 24049221]
[27]
Paraskevopoulou MD, Georgakilas G, Kostoulas N, Vlachos IS, Vergoulis T, Reczko M, et al. DIANA-microT web server v50: service integration into miRNA functional analysis workflows. Nucleic Acids Res 2013; 169-73.
[28]
Gaidatzis D, van Nimwegen E, Hausser J, Zavolan M. Inference of miRNA targets using evolutionary conservation and pathway analysis. BMC Bioinformatics 2007; 8: 69.
[http://dx.doi.org/10.1186/1471-2105-8-69] [PMID: 17331257]
[29]
Griffiths-Jones S, Saini HK, van Dongen S, Enright AJ. miRBase: tools for microRNA genomics. Nucleic Acids Res 2008; 36(Database issue): D154-8.
[PMID: 17991681]
[30]
Betel D, Wilson M, Gabow A, Marks DS, Sander C. The microRNA.org resource: targets and expression. Nucleic Acids Res 2008; 36(Database issue): D149-53.
[PMID: 18158296]
[31]
Wang X. miRDB: a microRNA target prediction and functional annotation database with a wiki interface. RNA 2008; 14(6): 1012-7.
[http://dx.doi.org/10.1261/rna.965408] [PMID: 18426918]
[32]
Anders G, Mackowiak SD, Jens M, et al. doRiNA: a database of RNA interactions in post-transcriptional regulation. Nucleic Acids Res 2012; 40(Database issue): D180-6.
[http://dx.doi.org/10.1093/nar/gkr1007] [PMID: 22086949]
[33]
Kertesz M, Iovino N, Unnerstall U, Gaul U, Segal E. The role of site accessibility in microRNA target recognition. Nat Genet 2007; 39(10): 1278-84.
[http://dx.doi.org/10.1038/ng2135] [PMID: 17893677]
[34]
Agarwal V, Bell GW, Nam JW, Bartel DP. Predicting effective microRNA target sites in mammalian mRNAs. eLife 2015; 4: 4.
[http://dx.doi.org/10.7554/eLife.05005] [PMID: 26267216]
[35]
Ru Y, Kechris KJ, Tabakoff B, et al. The multiMiR R package and database: integration of microRNA-target interactions along with their disease and drug associations. Nucleic Acids Res 2014; 133(17): 42.
[36]
Huang DW, Sherman BT, Tan Q, Kir J, Liu D, Bryant D, et al. DAVID bioinformatics resources: expanded annotation database and novel algorithms to better extract biology from large gene lists. Nucleic Acids Res 2007; 35(Web Server issue): W169-W75: 169- 75.
[http://dx.doi.org/10.1093/nar/gkm415]
[37]
Kanehisa M, Goto S. KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Res 2000; 28(1): 27-30.
[http://dx.doi.org/10.1093/nar/28.1.27] [PMID: 10592173]
[38]
Shannon P, Markiel A, Ozier O, et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res 2003; 13(11): 2498-504.
[http://dx.doi.org/10.1101/gr.1239303] [PMID: 14597658]

Rights & Permissions Print Cite
Article Metrics
6
1
Wayfinder Image
Open Access Journals Promotions
© 2024 Bentham Science Publishers | Privacy Policy