microRNA-mRNA interaction identification in Wilms tumor using principal component analysis based unsupervised feature extraction

Wilms tumor is one of lethal child renal cancers, for which no known disease causing mechanisms exist. In this paper, we tried to identify possible disease causing microRNA(miRNA)-mRNA pairs (interactions) by analyzing (partially matched) miRNA/mRNA gene expression profiles with the recently proposed principal component analysis based unsupervised feature extraction. It successfully identified multiple miRNA-mRNA pairs whose biological natures are convincing. Correlation coefficients between miRNA and mRNA expression in matched parts of profiles turned out to be significantly negative. Constructed miRNA-mRNA network will be a key to understand Wilms tumor causing mechanisms.

[1]  R. Ain,et al.  MicroRNA-141-3p and miR-200a-3p regulate insulin-like growth factor 2 during mouse placental development , 2015, Molecular and Cellular Endocrinology.

[2]  Mitsuo Iwadate,et al.  Bioinformatic Screening of Autoimmune Disease Genes and Protein Structure Prediction with FAMS for Drug Discovery , 2013, Protein and peptide letters.

[3]  H. Ben‐Hur,et al.  Expression of Stem Cell Markers in the Human Fetal Kidney , 2009, PloS one.

[4]  Mitsuo Iwadate,et al.  TINAGL1 and B3GALNT1 are potential therapy target genes to suppress metastasis in non-small cell lung cancer , 2014, BMC Genomics.

[5]  Yoshiki Murakami,et al.  Principal Component Analysis Based Feature Extraction Approach to Identify Circulating microRNA Biomarkers , 2013, PloS one.

[6]  Peter J. Smith,et al.  Expression and mutation analysis of the Wilms' tumor 1 gene in human neural tumors , 2002, International journal of cancer.

[7]  P. Jones,et al.  Collagen synthesis by short-term explants of pediatric tumors. , 1985, Cancer research.

[8]  G. Kale,et al.  Management of bilateral Wilms tumor over three decades: The perspective of a single center. , 2015, Journal of pediatric urology.

[9]  Yoshiki Murakami,et al.  Heuristic principal component analysis based unsupervised feature extraction and its application to bioinformatics , 2014 .

[10]  Yoshiki Murakami,et al.  Universal disease biomarker: can a fixed set of blood microRNAs diagnose multiple diseases? , 2014, BMC Research Notes.

[11]  Murielle M. Akpa,et al.  Wilms Tumor Suppressor, WT1, Cooperates with MicroRNA-26a and MicroRNA-101 to Suppress Translation of the Polycomb Protein, EZH2, in Mesenchymal Stem Cells* , 2015, The Journal of Biological Chemistry.

[12]  Guantao Zheng,et al.  Coordinated action of histone modification and microRNA regulations in human genome. , 2015, Gene.

[13]  Sean R. Davis,et al.  GEOquery: a bridge between the Gene Expression Omnibus (GEO) and BioConductor , 2007, Bioinform..

[14]  Sergey Popov,et al.  miRNA Profiles as a Predictor of Chemoresponsiveness in Wilms’ Tumor Blastema , 2013, PloS one.

[15]  Y-h. Taguchi,et al.  Heuristic principal component analysis-based unsupervised feature extraction and its application to gene expression analysis of amyotrophic lateral sclerosis data sets , 2015, 2015 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB).

[16]  C. Sander,et al.  Analysis of microRNA-target interactions across diverse cancer types , 2013, Nature Structural &Molecular Biology.

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

[18]  Toshiki Yoshimine,et al.  Overexpression of the Wilms' tumor gene WT1 in primary astrocytic tumors , 2004, Cancer science.

[19]  Richard A. Moore,et al.  Recurrent DGCR8, DROSHA, and SIX homeodomain mutations in favorable histology Wilms tumors. , 2015, Cancer cell.

[20]  Eckart Meese,et al.  Mutations in the SIX1/2 pathway and the DROSHA/DGCR8 miRNA microprocessor complex underlie high-risk blastemal type Wilms tumors. , 2015, Cancer cell.

[21]  Y-h. Taguchi,et al.  Integrative Analysis of Gene Expression and Promoter Methylation during Reprogramming of a Non-Small-Cell Lung Cancer Cell Line Using Principal Component Analysis-Based Unsupervised Feature Extraction , 2014, ICIC.

[22]  Y-h. Taguchi,et al.  Identification of More Feasible MicroRNA–mRNA Interactions within Multiple Cancers Using Principal Component Analysis Based Unsupervised Feature Extraction , 2016, International journal of molecular sciences.

[23]  Charles A Powell,et al.  Gene expression in Wilms' tumor mimics the earliest committed stage in the metanephric mesenchymal-epithelial transition. , 2002, The American journal of pathology.

[24]  W. Broaddus,et al.  Wilms tumor 1 expression in malignant gliomas and correlation of +KTS isoforms with p53 status. , 2007, Journal of neurosurgery.

[25]  K. Iwaisako,et al.  Comprehensive analysis of transcriptome and metabolome analysis in Intrahepatic Cholangiocarcinoma and Hepatocellular Carcinoma , 2015, Scientific Reports.

[26]  Hao Zhu,et al.  Lin28 sustains early renal progenitors and induces Wilms tumor , 2014, Genes & development.

[27]  Avi Ma'ayan,et al.  Enrichr: interactive and collaborative HTML5 gene list enrichment analysis tool , 2013, BMC Bioinformatics.

[28]  Yoshiki Murakami,et al.  Comparison of Hepatocellular Carcinoma miRNA Expression Profiling as Evaluated by Next Generation Sequencing and Microarray , 2014, PloS one.

[29]  Y-h. Taguchi,et al.  Heuristic principal component analysis based unsupervised feature extraction and its application to bioinformatics (情報論的学習理論と機械学習 情報論的学習理論ワークショップ) , 2014 .

[30]  Y. Benjamini,et al.  Controlling the false discovery rate: a practical and powerful approach to multiple testing , 1995 .

[31]  Y-h. Taguchi,et al.  Principal component analysis for bacterial proteomic analysis , 2011, 2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW).

[32]  Kathy Pritchard-Jones,et al.  The yin and yang of kidney development and Wilms’ tumors , 2015, Genes & development.

[33]  Y-h. Taguchi,et al.  Identification of aberrant gene expression associated with aberrant promoter methylation in primordial germ cells between E13 and E16 rat F3 generation vinclozolin lineage , 2015, BMC Bioinformatics.

[34]  Y-h. Taguchi,et al.  SFRP1 is a possible candidate for epigenetic therapy in non-small cell lung cancer , 2016, BMC Medical Genomics.

[35]  Y-H Taguchi,et al.  Apparent microRNA-Target-specific Histone Modification in Mammalian Spermatogenesis , 2015, Evolutionary bioinformatics online.

[36]  Y-h. Taguchi,et al.  Principal component analysis based unsupervised feature extraction applied to budding yeast temporally periodic gene expression , 2016, BioData Mining.

[37]  Jordan Anaya,et al.  OncoLnc: linking TCGA survival data to mRNAs, miRNAs, and lncRNAs , 2016, PeerJ Comput. Sci..

[38]  Y-h. Taguchi,et al.  Genes associated with genotype-specific DNA methylation in squamous cell carcinoma as candidate drug targets , 2014, BMC Systems Biology.

[39]  Y-h. Taguchi,et al.  Principal component analysis-based unsupervised feature extraction applied to in silico drug discovery for posttraumatic stress disorder-mediated heart disease , 2015, BMC Bioinformatics.

[40]  Rong Zheng,et al.  Tumor Suppressor Menin Represses Paired Box Gene 2 Expression via Wilms Tumor Suppressor Protein-Polycomb Group Complex* , 2011, The Journal of Biological Chemistry.

[41]  Arnon Nagler,et al.  Inhibition of Wilms tumor xenograft progression by halofuginone is accompanied by activation of WT-1 gene expression. , 2005, The Journal of urology.

[42]  Christina Backes,et al.  Combining miRNA and mRNA Expression Profiles in Wilms Tumor Subtypes , 2016, International journal of molecular sciences.

[43]  Yoshiki Murakami,et al.  Comprehensive miRNA Expression Analysis in Peripheral Blood Can Diagnose Liver Disease , 2012, PloS one.

[44]  Esther Rheinbay,et al.  Wilms tumor chromatin profiles highlight stem cell properties and a renal developmental network. , 2010, Cell stem cell.

[45]  Fang Tian,et al.  The development of Wilms tumor: from WT1 and microRNA to animal models. , 2014, Biochimica et biophysica acta.