疾病相关miRNAs识别方法研究进展
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摘要
miRNAs是一类内源性短序列非编码RNAs小分子,广泛参与细胞的增殖、分化、凋亡等生物学过程.miRNAs的异常表达与包括肿瘤在内的多种复杂疾病的发生、发展有着密切的关系,筛选与疾病相关的miRNAs,对于药物靶点的发现及新型药物的开发,具有十分重要的作用.笔者拟通过逐步递进的方式,从miRNA靶基因预测、miRNA生物功能作用机制、疾病相关miRNAs计算筛选方法、miRNA小分子药物多个方面,综述疾病相关miRNAs研究进展,为推进miRNA在临床医学中的应用提供参考.
miRNAs are a class of endogenous non-coding small RNAs, which are widely involved in cell proliferation, differentiation, apoptosis, and other biological processes. The abnormal expression of miRNAs is closely related to the occurrence and development of many complex diseases including tumors. Screening of disease-related miRNAs plays a very important guiding role in the discovery of drug targets and the development of new drugs. The authors of this paper intend to adopt a progressive approach from multiple aspects including the biological function mechanism of miRNAs, miRNA targets prediction, computational methods for screening the disease-related miRNAs, and ongoing clinical miRNAs small molecule drugs to review the research progress of disease-related miRNAs, which provides guidelines for advancing the application of miRNAs in clinical medicine.
miRNAs are a class of endogenous non-coding small RNAs, which are widely involved in cell proliferation, differentiation, apoptosis, and other biological processes. The abnormal expression of miRNAs is closely related to the occurrence and development of many complex diseases including tumors. Screening of disease-related miRNAs plays a very important guiding role in the discovery of drug targets and the development of new drugs. The authors of this paper intend to adopt a progressive approach from multiple aspects including the biological function mechanism of miRNAs, miRNA targets prediction, computational methods for screening the disease-related miRNAs, and ongoing clinical miRNAs small molecule drugs to review the research progress of disease-related miRNAs, which provides guidelines for advancing the application of miRNAs in clinical medicine.
引文
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[30] Kim S-K,Nam J-W,Rhee J-K,et al.MiTarget:microRNA target gene prediction using a support vector machine[J].BMC Bioinformatics,2006,7(1):1-12.
[31] Yang Y,Wang Y-P,Li K-B.MiRTif:A support vector machine-based microRNA target interaction filter[J].BMC Bioinformatics,2008,9(12):1-9.
[32] Chandra V,Girijadevi R,Nair A S,et al.MTar:A computational microRNA target prediction architecture for human transcriptome[J].BMC Bioinformatics,2010,11(1):1-9.
[33] Cheng S,Guo M,Wang C,et al.MiRTDL:A deep learning approach for miRNA target prediction[J].IEEE/ACM Transactions on Computational Biology,2016,13(6):1161-1169.
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[37] Jiang Q,Wang Y,Hao Y,et al.miR2Disease:A manually curated database for microRNA deregulation in human disease[J].Nucleic Acids Research,2009,37:98-104.
[38] Huang Z,Shi J,Gao Y,et al.HMDD v3.0:A database for experimentally supported human microRNA-disease associations[J].Nucleic Acids Research,2018,47(D1):1013-1017.
[39] Yang Z,Wu L,Wang A,et al.dbDEMC 2.0:Updated database of differentially expressed miRNAs in human cancers[J].Nucleic Acids Research,2017,45(D1):812-818.
[40] Derisi J L,Iyer V R,Brown P O.Exploring the metabolic and genetic control of gene expression on a genomic scale[J].Science,1997,278(5338):680-686.
[41] Pan W.A comparative review of statistical methods for discovering differentially expressed genes in replicated microarray experiments[J].Bioinformatics,2002,18(4):546-554.
[42] Leek J T,Scharpf R B,Bravo H C,et al.Tackling the widespread and critical impact of batch effects in high-throughput data[J].Nature Review Genetics,2010,11(10):733-739.
[43] Xu P,Zhu Y,Sun B,et al.Colorectal cancer characterization and therapeutic target prediction based on microRNA expression profile[J].Scientific Reports,2016,6:1-11.
[44] Garcia-Garcia F,Panadero J,Dopazo J,et al.Integrated gene set analysis for microRNA studies[J].Bioinformatics,2016,32(18):2809-2816.
[45] Peng F,Zhang Y,Wang R,et al.Identification of differentially expressed miRNAs in individual breast cancer patient and application in personalized medicine[J].Oncogenesis,2016,5:1-8.
[46] Tan A C,Naiman D Q,Xu L,et al.Simple decision rules for classifying human cancers from gene expression profiles[J].Bioinformatics,2005,21(20):3896-3904.
[47] Geman D,D'avignon C,Naiman D Q,et al.Classifying gene expression profiles from pairwise mRNA comparisons[J].Statistical Applications in Genetics and Molecular Biology,2004,3:1-22.
[48] Xu J,Li C X,Li Y S,et al.MiRNA-miRNA synergistic network:Construction via co-regulating functional modules and disease miRNA topological features[J].Nucleic Acids Research,2011,39(3):825-836.
[49] Li Y,Liang C,Wong K C,et al.Mirsynergy:Detecting synergistic miRNA regulatory modules by overlapping neighbourhood expansion[J].Bioinformatics,2014,30(18):2627-2635.
[50] 郭茂祖,王诗鸣,刘晓燕,等.miRNA与疾病关联关系预测算法[J].软件学报,2017,28(11):3094-3102.
[51] Zhao X M,Liu K Q,Zhu G,et al.Identifying cancer-related microRNAs based on gene expression data[J].Bioinformatics,2014,31(8):1226-1234.
[52] Liu W,Cui Z,Zan X.Identifying cancer-related microRNAs based on subpathways[J].IET Systems Biology,2018,12(6):273-278.
[53] Gumireddy K,Young D D,Xiong X,et al.Small-molecule inhibitors of microrna miR-21 function[J].Angewandte Chemie,2008,120 (39):7592-7594.
[54] Jiang W,Chen X,Liao M,et al.Identification of links between small molecules and miRNAs in human cancers based on transcriptional responses[J].Scientific Reports,2012,2(1):1-8.
[55] Liu X,Wang S,Meng F,et al.SM2miR:A database of the experimentally validated small molecules' effects on microRNA expression[J].Bioinformatics,2012,29(3):409-411.
[56] Chen X,Xie W B,Xiao P P,et al.mTD:A database of microRNAs affecting therapeutic effects of drugs[J].Journal of Genetics and Genomics,2017,44(5):269-271.
[57] Rupaimoole R,Slack F J.MicroRNA therapeutics:Towards a new era for the management of cancer and other diseases[J].Nature Reviews Drug Discovery,2017,16(3):203-222.
[2] Segal E,Friedman N,Koller D,et al.A module map showing conditional activity of expression modules in cancer[J].Nature Genetics,2004,36(10):1090-1098.
[3] Subramanian A,Tamayo P,Mootha V K,et al.Gene set enrichment analysis:A knowledge-based approach for interpreting genome-wide expression profiles[J].Proceedings of the National Academy of Sciences of the United States of America,2005,102(43):15545-15550.
[4] Chen C Z.MicroRNAs as oncogenes and tumor suppressors[J].New England Journal of Medicine,2005,353(17):1768-1771.
[5] Lee Y,Ahn C,Han J,et al.The nuclear RNase III Drosha initiates microRNA processing[J].Nature,2003,425(6956):415-419.
[6] Chen C Z,Li L,Lodish H F,et al.MicroRNAs modulate hematopoietic lineage differentiation[J].Science,2004,303(5654):83-86.
[7] Zeng Y,Wagner E J,Cullen B R.Both natural and designed micro RNAs can inhibit the expression of cognate mRNAs when expressed in human cells[J].Molecular Cell,2002,9(6):1327-1333.
[8] Lund E,Guttinger S,Calado A,et al.Nuclear export of microRNA precursors[J].Science,2004,303(5654):95-98.
[9] Bernstein E,Caudy A A,Hammond S M,et al.Role for a bidentate ribonuclease in the initiation step of RNA interference[J].Nature,2001,409(6818):363-366.
[10] Bartel D P.MicroRNAs:Genomics,biogenesis,mechanism,and function[J].Cell,2004,116(2):281-297.
[11] Lai E C.microRNAs:Runts of the genome assert themselves[J].Current Biology,2003,13(23):925-936.
[12] Vasudevan S,Tong Y,Steitz J A.Switching from repression to activation:MicroRNAs can up-regulate translation[J].Science,2007,318(5858):1931-1934.
[13] Xiao M,Li J,Li W,et al.MicroRNAs activate gene transcription epigenetically as an enhancer trigger[J].RNA Biology,2017,14(10):1326-1334.
[14] Bartel D P.MicroRNAs:Target recognition and regulatory functions[J].Cell,2009,136(2):215-233.
[15] Yousef M,Showe L,Showe M.A study of microRNAs in silico and in vivo:Bioinformatics approaches to microRNA discovery and target identification[J].Febs Journal,2009,276(8):2150-2156.
[16] Riffo-Campos A L,Riquelme I,Brebi-Mieville P.Tools for sequence-based miRNA target prediction:What to choose?[J].International Journal of Molecular Sciences,2016,17(12):1-18.
[17] Oh M,Rhee S,Moon J H,et al.Literature-based condition-specific miRNA-mRNA target prediction[J].PLoS One,2017,12(3):1-15.
[18] Huang Y,Gao X C,Ren H T,et al.Characterization of conserved and novel miRNAs using deep sequencing and prediction of miRNA targets in Crucian carp (Carassius auratus)[J].Gene,2017,635:61-68.
[19] Enright A J,John B,Gaul U,et al.MicroRNA targets in Drosophila[J].Genome Biology,2004,5(1):1-14.
[20] Betel D,Koppal A,Agius P,et al.Comprehensive modeling of microRNA targets predicts functional non-conserved and non-canonical sites[J].Genome Biology,2010,11(8):1-14.
[21] John B,Enright A J,Aravin A,et al.Human microRNA targets[J].PLoS Biology,2004,2(11):1862-1879.
[22] Smith T F,Waterman M S.Identification of common molecular subsequences[J].Journal of Molecular Biology,1981,147(1):195-197.
[23] Agarwal V,Bell G W,Nam J-W,et al.Predicting effective microRNA target sites in mammalian mRNAs[J].Elife,2015,4:1-38.
[24] Lewis B P,Burge C B,Bartel D P.Conserved seed pairing,often flanked by adenosines,indicates that thousands of human genes are microRNA targets[J].Cell,2005,120(1):15-20.
[25] Lewis B P,Shih I-H,Jones-Rhoades M W,et al.Prediction of mammalian microRNA targets[J].Cell,2003,115(7):787-798.
[26] Krek A,Grun D,Poy M N,et al.Combinatorial microRNA target predictions[J].Nature Genetics,2005,37(5):495-500.
[27] Liu X,Wang Y,Ji H,et al.Personalized characterization of diseases using sample-specific networks[J].Nucleic Acids Research,2016,44(22):1-8.
[28] Kertesz M,Iovino N,Unnerstall U,et al.The role of site accessibility in microRNA target recognition[J].Nature Genetics,2007,39(10):1278-1284.
[29] Saetrom O,Snve O,S?trom P.Weighted sequence motifs as an improved seeding step in microRNA target prediction algorithms[J].RNA,2005,11(7):995-1003.
[30] Kim S-K,Nam J-W,Rhee J-K,et al.MiTarget:microRNA target gene prediction using a support vector machine[J].BMC Bioinformatics,2006,7(1):1-12.
[31] Yang Y,Wang Y-P,Li K-B.MiRTif:A support vector machine-based microRNA target interaction filter[J].BMC Bioinformatics,2008,9(12):1-9.
[32] Chandra V,Girijadevi R,Nair A S,et al.MTar:A computational microRNA target prediction architecture for human transcriptome[J].BMC Bioinformatics,2010,11(1):1-9.
[33] Cheng S,Guo M,Wang C,et al.MiRTDL:A deep learning approach for miRNA target prediction[J].IEEE/ACM Transactions on Computational Biology,2016,13(6):1161-1169.
[34] Lee R C,Feinbaum R L,Ambros V.The C-Elegans heterochronic gene Lin-4 encodes small rnas with antisense complementarity to Lin-14[J].Cell,1993,75(5):843-854.
[35] Reinhart B J,Slack F J,Basson M,et al.The 21-nucleotide let-7 RNA regulates developmental timing in Caenorhabditis elegans[J].Nature,2000,403(6772):901-906.
[36] Suzuki H I,Young R A,Sharp P A.Super-enhancer-mediated RNA processing revealed by integrative microRNA network analysis[J].Cell,2017,168(6):1000-1014,1015.
[37] Jiang Q,Wang Y,Hao Y,et al.miR2Disease:A manually curated database for microRNA deregulation in human disease[J].Nucleic Acids Research,2009,37:98-104.
[38] Huang Z,Shi J,Gao Y,et al.HMDD v3.0:A database for experimentally supported human microRNA-disease associations[J].Nucleic Acids Research,2018,47(D1):1013-1017.
[39] Yang Z,Wu L,Wang A,et al.dbDEMC 2.0:Updated database of differentially expressed miRNAs in human cancers[J].Nucleic Acids Research,2017,45(D1):812-818.
[40] Derisi J L,Iyer V R,Brown P O.Exploring the metabolic and genetic control of gene expression on a genomic scale[J].Science,1997,278(5338):680-686.
[41] Pan W.A comparative review of statistical methods for discovering differentially expressed genes in replicated microarray experiments[J].Bioinformatics,2002,18(4):546-554.
[42] Leek J T,Scharpf R B,Bravo H C,et al.Tackling the widespread and critical impact of batch effects in high-throughput data[J].Nature Review Genetics,2010,11(10):733-739.
[43] Xu P,Zhu Y,Sun B,et al.Colorectal cancer characterization and therapeutic target prediction based on microRNA expression profile[J].Scientific Reports,2016,6:1-11.
[44] Garcia-Garcia F,Panadero J,Dopazo J,et al.Integrated gene set analysis for microRNA studies[J].Bioinformatics,2016,32(18):2809-2816.
[45] Peng F,Zhang Y,Wang R,et al.Identification of differentially expressed miRNAs in individual breast cancer patient and application in personalized medicine[J].Oncogenesis,2016,5:1-8.
[46] Tan A C,Naiman D Q,Xu L,et al.Simple decision rules for classifying human cancers from gene expression profiles[J].Bioinformatics,2005,21(20):3896-3904.
[47] Geman D,D'avignon C,Naiman D Q,et al.Classifying gene expression profiles from pairwise mRNA comparisons[J].Statistical Applications in Genetics and Molecular Biology,2004,3:1-22.
[48] Xu J,Li C X,Li Y S,et al.MiRNA-miRNA synergistic network:Construction via co-regulating functional modules and disease miRNA topological features[J].Nucleic Acids Research,2011,39(3):825-836.
[49] Li Y,Liang C,Wong K C,et al.Mirsynergy:Detecting synergistic miRNA regulatory modules by overlapping neighbourhood expansion[J].Bioinformatics,2014,30(18):2627-2635.
[50] 郭茂祖,王诗鸣,刘晓燕,等.miRNA与疾病关联关系预测算法[J].软件学报,2017,28(11):3094-3102.
[51] Zhao X M,Liu K Q,Zhu G,et al.Identifying cancer-related microRNAs based on gene expression data[J].Bioinformatics,2014,31(8):1226-1234.
[52] Liu W,Cui Z,Zan X.Identifying cancer-related microRNAs based on subpathways[J].IET Systems Biology,2018,12(6):273-278.
[53] Gumireddy K,Young D D,Xiong X,et al.Small-molecule inhibitors of microrna miR-21 function[J].Angewandte Chemie,2008,120 (39):7592-7594.
[54] Jiang W,Chen X,Liao M,et al.Identification of links between small molecules and miRNAs in human cancers based on transcriptional responses[J].Scientific Reports,2012,2(1):1-8.
[55] Liu X,Wang S,Meng F,et al.SM2miR:A database of the experimentally validated small molecules' effects on microRNA expression[J].Bioinformatics,2012,29(3):409-411.
[56] Chen X,Xie W B,Xiao P P,et al.mTD:A database of microRNAs affecting therapeutic effects of drugs[J].Journal of Genetics and Genomics,2017,44(5):269-271.
[57] Rupaimoole R,Slack F J.MicroRNA therapeutics:Towards a new era for the management of cancer and other diseases[J].Nature Reviews Drug Discovery,2017,16(3):203-222.
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