Identification of miRNA-mRNA crosstalk in pancreatic cancer by integrating transcriptome analysis

被引:0
作者
Yang, J. [1 ]
Zeng, Y. [2 ]
机构
[1] Chongqing Med Univ, Affiliated Hosp 1, Dept Gastroenterol, Chongqing, Peoples R China
[2] Chongqing Med Univ, Affiliated Hosp 2, Dept Psychol, Chongqing, Peoples R China
关键词
Integrated analysis; mRNA expression data; miRNA expression data; Pancreatic cancer; miRNA target genes; EPITHELIAL-MESENCHYMAL TRANSITION; MICRORNA EXPRESSION PROFILES; C-MYC; GENE-EXPRESSION; GASTRIC-CANCER; CELLS; MIR-210; PATHWAY; METASTASIS; CARCINOMA;
D O I
暂无
中图分类号
R9 [药学];
学科分类号
1007 ;
摘要
OBJECTIVE: Pancreatic cancer is one of the most lethal diseases, and the pathogenesis remains largely unknown. To this end, we performed an integrated analysis of miRNA and mRNA expression data to explore the deregulation of miRNA and mRNA and regulatory processes underlying pancreatic cancer. MATERIALS AND METHODS: We combined mRNA and miRNA expression data with miRNA target predictions to infer new miRNA regulation activities in pancreatic cancer. We first integrated miRNA and mRNA expression profiling separately to identify differently expressed miRNA and mRNA in pancreatic cancer. Then we adopted miRWalk databases prediction to obtain potential target genes of differently expressed miRNA, and compared these target genes to the gene list of integrated mRNA expression profiling to select differentially expressed miRNA-target gene whose expression was reversely correlated with that of corresponding miRNAs. Gene Ontology (GO) classification analyses and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were employed to understand the functions and pathways of miRNA target genes. Finally we construct a miRNA-target gene regulatory network. RESULTS: 42 differentially expressed miRNAs, 1376 differentially expressed mRNAs were identified by combining three expression profiles of miRNA and mRNA separately in pancreatic cancer, 146 miRNA target genes were found in the gene list of integrated mRNA expression profiling based on bioinformatics prediction. Functional annotation was performed to understand the functions and pathways of miRNA target genes. Finally, we constructed a miRNA-target gene regulatory network including 206 miRNA-target gene pairs. Five miRNAs (hsa-miR-130b, hsa-miR-106b, hsa-miR-181c, hsa-miR-153 and hsa-miR-125a-5p) demonstrated the highest connectivities, whereas three miRNAs (MYC, E2F1 and IL6) were the mRNAs with the highest connectivities. CONCLUSIONS: Our findings may provide new insights into the knowledge of molecular mechanisms of pancreatic cancer and development of novel targeting therapies.
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页码:825 / 834
页数:10
相关论文
共 42 条
  • [1] PathwayVoyager: pathway mapping using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database
    Altermann, E
    Klaenhammer, TR
    [J]. BMC GENOMICS, 2005, 6 (1)
  • [2] The patterns and dynamics of genomic instability in metastatic pancreatic cancer
    Campbell, Peter J.
    Yachida, Shinichi
    Mudie, Laura J.
    Stephens, Philip J.
    Pleasance, Erin D.
    Stebbings, Lucy A.
    Morsberger, Laura A.
    Latimer, Calli
    McLaren, Stuart
    Lin, Meng-Lay
    McBride, David J.
    Varela, Ignacio
    Nik-Zainal, Serena A.
    Leroy, Catherine
    Jia, Mingming
    Menzies, Andrew
    Butler, Adam P.
    Teague, Jon W.
    Griffin, Constance A.
    Burton, John
    Swerdlow, Harold
    Quail, Michael A.
    Stratton, Michael R.
    Iacobuzio-Donahue, Christine
    Futreal, P. Andrew
    [J]. NATURE, 2010, 467 (7319) : 1109 - 1113
  • [3] Induction, modulation and potential targets of miR-210 in pancreatic cancer cells
    Chen, Wei-Yun
    Liu, Wen-Jing
    Zhao, Yu-Pei
    Zhou, Li
    Zhang, Tai-Ping
    Chen, Ge
    Shu, Hong
    [J]. HEPATOBILIARY & PANCREATIC DISEASES INTERNATIONAL, 2012, 11 (03) : 319 - 324
  • [4] Mutant p53 gain-of-function induces epithelial-mesenchymal transition through modulation of the miR-130b-ZEB1 axis
    Dong, P.
    Karaayvaz, M.
    Jia, N.
    Kaneuchi, M.
    Hamada, J.
    Watari, H.
    Sudo, S.
    Ju, J.
    Sakuragi, N.
    [J]. ONCOGENE, 2013, 32 (27) : 3286 - 3295
  • [5] MicroRNA-106b modulates epithelial-mesenchymal transition by targeting TWIST1 in invasive endometrial cancer cell lines
    Dong, Peixin
    Kaneuchi, Masanori
    Watari, Hidemichi
    Sudo, Satoko
    Sakuragi, Noriaki
    [J]. MOLECULAR CARCINOGENESIS, 2014, 53 (05) : 349 - 359
  • [6] miRWalk - Database: Prediction of possible miRNA binding sites by "walking" the genes of three genomes
    Dweep, Harsh
    Sticht, Carsten
    Pandey, Priyanka
    Gretz, Norbert
    [J]. JOURNAL OF BIOMEDICAL INFORMATICS, 2011, 44 (05) : 839 - 847
  • [7] Gene Expression Omnibus: NCBI gene expression and hybridization array data repository
    Edgar, R
    Domrachev, M
    Lash, AE
    [J]. NUCLEIC ACIDS RESEARCH, 2002, 30 (01) : 207 - 210
  • [8] miRNA-mRNA Integrated Analysis Reveals Roles for miRNAs in Primary Breast Tumors
    Enerly, Espen
    Steinfeld, Israel
    Kleivi, Kristine
    Leivonen, Suvi-Katri
    Aure, Miriam R.
    Russnes, Hege G.
    Ronneberg, Jo Anders
    Johnsen, Hilde
    Navon, Roy
    Rodland, Einar
    Makela, Rami
    Naume, Bjorn
    Perala, Merja
    Kallioniemi, Olli
    Kristensen, Vessela N.
    Yakhini, Zohar
    Borresen-Dale, Anne-Lise
    [J]. PLOS ONE, 2011, 6 (02):
  • [9] MiR-106b expression determines the proliferation paradox of TGF-β in breast cancer cells
    Gong, C.
    Qu, S.
    Liu, B.
    Pan, S.
    Jiao, Y.
    Nie, Y.
    Su, F.
    Liu, Q.
    Song, E.
    [J]. ONCOGENE, 2015, 34 (01) : 84 - 93
  • [10] MicroRNA miR-491-5p Targeting both TP53 and Bcl-XL Induces Cell Apoptosis in SW1990 Pancreatic Cancer Cells through Mitochondria Mediated Pathway
    Guo, Rong
    Wang, Yi
    Shi, Wei-Ye
    Liu, Bin
    Hou, Sheng-Qi
    Liu, Li
    [J]. MOLECULES, 2012, 17 (12): : 14733 - 14747