A hypergeometric test of and showed a target genes predicted from targetscan (http:www.targetscan.org) and 109

A hypergeometric test of and showed a target genes predicted from targetscan (http:www.targetscan.org) and 109 identified 378 miR150 statistical significance of pvalue 0.006 (Figure 3A).Ubiquitin Inhibitors Reagents leioyomarelated genes from previously published papers [3,148]. Consequently, a total of 7 genesTP53, CTNNB1, HMGA2, PIK3CB, CCND2, GSK3B, and p27Kip1 (CDKN1B), were common to both groups and showed a statistical significance of pvalue 0.006 (Figure 3A). Using the high confident hyperlink of STRING ten.five, the predicted target genes of miR150 constituted a comparatively largescale subnetwork (Figure 3B). In gene prioritization applying the STRING network, the target genes of miR150 have been able to predict leiomyoma genes sufficiently and showed a high AUC prediction power (AUC0.7994) (Figure 3C). Amongst the predicted target genes, p27Kip1 (CDKN1B) was selected for further validation.Int. J. Mol. Sci. 2019, 20,five ofACBFigure 3. (A) Gene set analysis: predicted target genes of miR150 contain 7 in the 109 previously known leiomyoma related genes.predicted target genes of miR150 contain 7 of thetarget genes of Figure three. (A) Gene set analysis: (B) In the STRING network model, the predicted 109 previously miR150 leiomyoma modules of enough size. STRING p27Kip1 , the predictedpredicted target miR150 recognized are forming related genes. (B) Within the Akt and network model, the target genes for genes of within this study, forming modules of sufficient size. Akt and p27Kip1, the predicted target genes for miRmiR150 are was shown in yellow. (C) In gene prioritization working with the STRING network, the target genes ofthis study, was shown in yellow. (C) Ingenes sufficiently and showed aSTRING network, the 150 in miR150 were capable to predict leiomyoma gene prioritization applying the high AUC prediction power (AUC0.7994). target genes of miR150 were able to predict leiomyoma genes sufficiently and showed a high AUCprediction power (AUC0.7994).Int. J. Mol. Sci. 2019, 20,six ofUsing the high confident hyperlink of STRING ten.five, the predicted target genes of miR150 constituted a somewhat largescale subnetwork (Figure 3B). In gene prioritization applying the STRING network, the target genes of miR150 were in a position to predict leiomyoma genes sufficiently and showed a higher AUC prediction energy (AUC0.7994) (Figure 3C). Among the predicted target genes, p27Kip1 (CDKN1B) was chosen for additional validation.two.4. p27Kip1 mRNA Expression Levels Reduce in Leiomyoma two.four. p27Kip1 mRNA Expression Levels Reduce in Leiomyoma To confirm the network analysis outcomes, relative expression of p27Kip1 (CDKN1B), a predicted To confirm the network analysis outcomes, relative expression of p27Kip1 (CDKN1B), a predicted target gene of miR150, in uterine leiomyomas and matched myometrium was assessed making use of qRTtarget gene of miR150, in uterine leiomyomas and matched myometrium was assessed utilizing qRTPCR PCR (Figure 4). p27Kip1 mRNA expression levels decreased 0.23 times in leiomyoma tissues compared (Figure four). p27Kip1 mRNA expression levels decreased 0.23 times in leiomyoma tissues compared to to myometrial Herbimycin A Biological Activity tissue (p 0.01). myometrial tissue (p 0.01).Figure 4. Expression of p27Kip1 mRNA was decreased 0.23 occasions in leiomyoma tissues (n = 7) compared Figure 4. Expression of p27Kip1 mRNA was decreased 0.23 times in leiomyoma tissues (n = 7) realtime to myometrial tissue (n = 7) in line with qRTPCR analysis (p 0.01). qRTPCR, quantitativecompared to myometrial tissue (n = 7) according polymerase chain reaction. ( p 0.01)to qRTPCR evaluation (p 0.