Screening biomarkers of prostate cancer by integrating microRNA and mRNA microarrays.

OBJECTIVE In this study, we screened microRNA (miRNA) target genes of prostate cancer by integrating miRNA and mRNA expression profiles after target prediction and performed function enrichment analysis for selected candidate genes. METHODS The miRNA expression profile (GSE36802) and mRNA expression profile (GSE36801) were downloaded from the Gene Expression Omnibus database. We processed data and identified the differentially expressed miRNAs and mRNAs with R packages. Verified targets of miRNAs were identified through miRecods and miRTarBase. Then, software of Search Tool for the Retrieval of Interacting Genes was used to construct the interaction network of target genes. Finally, we performed function enrichment analysis for genes in the interaction network with the Functional Classification Tool. RESULTS A total of 22 upregulated and 8 downregulated miRNAs were detected in this study, of which, hsa-mir-31 was the most overexpressed miRNA in prostate cancer. Both ITGA5 and RDX, two target genes of hsa-mir-31, were found to be differentially expressed from mRNA profiles by overexpressing hsa-mir-31. The cell adhesion molecule was found to be the most significant pathway enriched by ITGA5 and RDX. CONCLUSION Overexpression of hsa-mir-31 can be a significant marker to distinguish cancer tissues from benign tissues. The targets such as ITGA5 and RDX regulated by hsa-mir-31 are candidate genes of prostate cancer, which provide new treatment strategies for its gene therapy.

[1]  Russ B. Altman,et al.  Missing value estimation methods for DNA microarrays , 2001, Bioinform..

[2]  Brad T. Sherman,et al.  Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists , 2008, Nucleic acids research.

[3]  D. Allison,et al.  Microarray data analysis: from disarray to consolidation and consensus , 2006, Nature Reviews Genetics.

[4]  Limin Chen,et al.  Tripchlorolide induces cell death in lung cancer cells by autophagy , 2011, International journal of oncology.

[5]  O. Cussenot,et al.  Co-ordinated changes in expression of cell adhesion molecules in prostate cancer. , 1997, European journal of cancer.

[6]  Zhaoyi Wang,et al.  miR-17-5p targets the p300/CBP-associated factor and modulates androgen receptor transcriptional activity in cultured prostate cancer cells , 2012, BMC Cancer.

[7]  Edith A Perez,et al.  MicroRNA signatures: clinical biomarkers for the diagnosis and treatment of breast cancer. , 2011, Trends in molecular medicine.

[8]  Taylor Murray,et al.  Cancer statistics, 2000 , 2000, CA: a cancer journal for clinicians.

[9]  W. Jiang,et al.  Cell-cell adhesion molecules and signaling intermediates and their role in the invasive potential of prostate cancer cells. , 2000, The Journal of urology.

[10]  Wei Fan,et al.  miRNA-mRNA Correlation-Network Modules in Human Prostate Cancer and the Differences between Primary and Metastatic Tumor Subtypes , 2012, PloS one.

[11]  Chi-Ying F. Huang,et al.  miRTarBase: a database curates experimentally validated microRNA–target interactions , 2010, Nucleic Acids Res..

[12]  Gordon K. Smyth,et al.  limmaGUI: A graphical user interface for linear modeling of microarray data , 2004, Bioinform..

[13]  Giovanni Vanni Frajese,et al.  miR-221 and miR-222 Expression Affects the Proliferation Potential of Human Prostate Carcinoma Cell Lines by Targeting p27Kip1* , 2007, Journal of Biological Chemistry.

[14]  Taylor Murray,et al.  Cancer statistics, 1999 , 1999, CA: a cancer journal for clinicians.

[15]  D. Altieri Survivin, cancer networks and pathway-directed drug discovery , 2008, Nature Reviews Cancer.

[16]  Alex E. Lash,et al.  Gene Expression Omnibus: NCBI gene expression and hybridization array data repository , 2002, Nucleic Acids Res..

[17]  C. Creighton,et al.  Widespread deregulation of microRNA expression in human prostate cancer , 2008, Oncogene.

[18]  Xu Chen,et al.  Up-regulated microRNA-143 in cancer stem cells differentiation promotes prostate cancer cells metastasis by modulating FNDC3B expression , 2013, BMC Cancer.

[19]  Shuang Huang,et al.  Ratio of miR-196s to HOXC8 messenger RNA correlates with breast cancer cell migration and metastasis. , 2010, Cancer research.

[20]  H. Hirano,et al.  Identification of miR-30d as a novel prognostic maker of prostate cancer , 2012, Oncotarget.

[21]  Yasunori Fujita,et al.  Effects of miR-34a on cell growth and chemoresistance in prostate cancer PC3 cells. , 2008, Biochemical and biophysical research communications.

[22]  S. L. Wong,et al.  A Map of the Interactome Network of the Metazoan C. elegans , 2004, Science.

[23]  Vincent De Guire,et al.  An E2F/miR-20a Autoregulatory Feedback Loop* , 2007, Journal of Biological Chemistry.

[24]  Hsiang-Yuan Yeh,et al.  Biomarker Identification for Prostate Cancer and Lymph Node Metastasis from Microarray Data and Protein Interaction Network Using Gene Prioritization Method , 2012, TheScientificWorldJournal.

[25]  Damian Szklarczyk,et al.  The STRING database in 2011: functional interaction networks of proteins, globally integrated and scored , 2010, Nucleic Acids Res..

[26]  João Ricardo Sato,et al.  Evaluating different methods of microarray data normalization , 2006, BMC Bioinformatics.

[27]  H. Dvorak,et al.  The L6 protein TM4SF1 is critical for endothelial cell function and tumor angiogenesis. , 2009, Cancer research.

[28]  Tongbin Li,et al.  miRecords: an integrated resource for microRNA–target interactions , 2008, Nucleic Acids Res..

[29]  W. Budd,et al.  microRNA Dysregulation in Prostate Cancer: Network Analysis Reveals Preferential Regulation of Highly Connected Nodes , 2012, Chemistry & biodiversity.

[30]  P. Gunaratne,et al.  Molecular profiling uncovers a p53-associated role for microRNA-31 in inhibiting the proliferation of serous ovarian carcinomas and other cancers. , 2010, Cancer research.

[31]  R. Hiatt,et al.  Alcohol consumption, smoking, and other risk factors and prostate cancer in a large health plan cohort in California (United States) , 2005, Cancer Causes & Control.

[32]  Seon-Young Kim,et al.  Gene-set approach for expression pattern analysis , 2008, Briefings Bioinform..

[33]  Gary D. Bader,et al.  Detecting microRNAs of high influence on protein functional interaction networks: a prostate cancer case study , 2012, BMC Systems Biology.

[34]  R. Shiekhattar,et al.  MicroRNA biogenesis and cancer. , 2005, Cancer research.

[35]  D. Ye,et al.  Livin expression may be regulated by miR-198 in human prostate cancer cell lines. , 2013, European journal of cancer.