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  • br As mentioned in the previous paragraphs experimental


    As mentioned in the previous paragraphs, experimental analysis
    Fig. 3. The ROC curve analysis for the comparison of the diagnostic efficiency of combined and single ncRNA markers.
    reported that deregulated levels of MEG3 and H19 could function as a “molecular sponge” for their related miRNAs and thereby modulates the inhibitory effects of that on the expression of target genes. Therefore, to further investigation, we have determined the GC-related target genes of studied miRNAs which is regulated by two or three distinct miRNAs. Our in silico analysis (Fig. 5) revealed that miR-148a and miR-181a had common targets including TGIF2, BCL2, SPRY2, SMAD2, KLF6 and STAT3 which observed to be deregulated in GC. For example, deregulation of TGIF2 is associated with the development and progression of some human tumors like GC (Hu et al., 2015). Zhang et al. demonstrated that overexpression of STAT3 is associated with poor survival outcome in GC patients (Zhang et al., 2017). In addition, our network analysis showed that ZEB2 and PTEN are targeted by miR-
    Table 3
    Association of ncRNAs expression levels and clinicopathologic parameters. 
    181a- and miR-141. The ZEB2 expression is associated with the clin-icopathological parameters of GC and also could promote GC cell mi-gration and invasion (Dai et al., 2012). It has been shown that func-tional inactivation of PTEN had linked to the development, progression and prognosis of GC (Xu et al., 2014). Finally our in silico analysis re-vealed that miR-181a, miR-141 and miR-675 had one shared target named RUNX1. This transcription factor positively regulates the ErbB2/ HER2 signaling pathway through modulating SOS1 expression in GC ME2906 (Mitsuda et al., 2018). Li et al. (2016) revealed that RUNX1 is down-regulated in GC tissues compared to adjacent non-tumor.
    Our ROC analysis revealed that a combination of H19, MEG3 and miR-675-5p able to discriminate controls and GC subjects with 88.87% sensitivity and 85% specificity. It has been demonstrated that due to the
    Parameter n ncRNAs gene expression
    Low High
    Low High
    Low High
    Low High Low High
    Low High
    Gender 62
    P value
    Smoking 62
    P value
    P value
    Lymph-node metastasis 40
    P value
    TNM stage 46
    I and II
    III and IV
    P value
    P value
    P values was computed by χ2 tests. Bold values are statistically significant. P < 0.05.
    Fig. 4. KEGG pathways enrichment analysis of genes regulated by miR-675, miR-148a, miR-181a and miR-141. Each column represents one miRNA and each row reveals one pathway. Darker colors represent lower significance values, and higher interaction of each miRNA with a specific molecular pathway.
    Fig. 5. MEG3 and H19 lncRNAs inter-active miRNAs. Deregulated level of MEG3 functioned as a “molecular sponge” for miR-181a, miR-148a and miR-141 and thereby modulates the inhibitory effects of these miRNAs on the expression of target genes involved in GC-related pathways. In addition, H19 lncRNA generates miR-675, as well as acts as a sponge for miR-141, thus indirectly regulate gene expres-sion. Orange and blue nodes represent genes that targeted by three and two miRNAs, respectively. (For interpreta-tion of the references to colour in this figure legend, the reader is referred to the web version of this article.)
    possible overlap in miRNA targets, the use of a combination of several miRNAs provided a powerful diagnostic tool compared with using a single marker (Ajit, 2012). Zhu et al. (2014) reported that a panel of five miRNAs may serve as a potential biomarker in detecting early stage GC.