Abstract

Objective:
 The objective of this study is to define novel biomarkers for Prostate Cancer
 (PCa) via in silico analysis that takes PCa-specific miRNAs, finds their
 combinatorial target genes (potential ceRNAs), selects ones containing
 Transcribed Ultra Conserved Region (T-UCR) among them and potentiates their
 relevance with PCa.
 
 Methods:
 Thirty-four miRNAs of which clinical relevances with PCa were proved
 experimentally were exported via miRWalk database.Using the ComiR database, 859
 genes targeted by these 34 miRNAs simultaneously were identified. Genes with
 ComiR score above 0.911 were taken into account. Genes containing T-UCR and
 showing potential ceRNA activity were extracted. Among PCa-associated ceRNAs
 including T-UCR, we identified genes with significant expression differences between
 PCa and normal prostate tissue using the GEPIA database. The statistical
 evaluation of the association of NFAT5 and PTBP2 genes with PCa was performed
 by Spearman correlation test in GEPIA database.
 
 Results:
 PCa-associated ceRNAs cross-matching with genes including T-UCR in their exonic
 regions were NFAT5, CLK3, PTBP2, CPEB4, MIPOL1 and TCF4. We identified genes
 with significant expression differences between PCa and normal prostate tissues
 among PCa-associated ceRNAs including T-UCR. According to this analysis, NFAT5
 and PTBP2 genes were significantly less expressed in PCa than in normal
 prostate tissue while the others didn’t show any significant differential
 expression pattern. NFAT5 and PTBP2 genes were found to be significantly
 associated with PCa (p=0.000012; R=0.72).
 
 Conclusion:
 All in all, this is the study associating NFAT5 and PTBP2 genes with PCa and
 giving them tumor suppressive potential for PCa. Still, larger and more
 comprehensive studies are needed on this issue.

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