Table 2.
Putative microRNA-mRNA regulatory module defined by microRNA down-regulation and mRNA up-regulationa
| Putative miR-mRNA regulatory module | Bioinformatics Predictionc | Correlation (TCGA dataset)d | Correlation (HNSCC cell line)e | |||
|---|---|---|---|---|---|---|
| miR (down)b | mRNA (up)b | Pearson r | p value | Pearson r | p value | |
| hsa-miR-375 | COL4A6 | 5 | −0.3145 | 0.13511 | 0.2432 | |
| hsa-miR-375 | COL5A1 | 5 | −0.3659 | 0.079472 | −0.2159 | 0.4585 |
| hsa-miR-125b | COL5A1 | 5 | −0.437 | 0.03274 | −0.0325 | 0.9122 |
| hsa-miR-375 | COL5A2 | 5 | −0.3708 | 0.075136 | −0.231 | 0.426861 |
| hsa-miR-375 | CXCL1 | 4 | −0.0864 | 0.689479 | 0.7146 | |
| hsa-miR-125b | CXCL13 | 6 | −0.3346 | 0.110688 | −0.1736 | 0.552828 |
| hsa-miR-375 | DFNA5 | 4 | −0.4936 | 0.014374 | −0.0855 | 0.771344 |
| hsa-miR-100 | FSTL4 | 3 | −0.0923 | 0.668975 | −0.1796 | 0.538966 |
| hsa-miR-99a | FSTL4 | 3 | −0.1413 | 0.511067 | −0.1847 | 0.527303 |
| hsa-miR-125b | HMGA2 | 5 | −0.4628 | 0.023036 | −0.0557 | 0.849995 |
| hsa-miR-375 | IFI44L | 4 | −0.1937 | 0.366226 | 0.42 | |
| hsa-miR-125b | IGFBP3 | 4 | −0.3656 | 0.079472 | −0.2774 | 0.336959 |
| hsa-miR-125b | LAMC2 | 5 | −0.6952 | 0.000164 | 0.3459 | |
| hsa-miR-375 | LAMC2 | 3 | −0.4309 | 0.035971 | 0.4508 | |
| hsa-miR-375 | ODC1 | 3 | −0.2375 | 0.264826 | −0.1239 | 0.673024 |
aThe putative microRNA-mRNA regulatory module (MRM) was constructed based on microRNA and mRNA expression profiles of OTSCC, as we previously reported in [16] and [15], respectively
bDifferential expression of microRNAs and mRNAs was validated using dataset on 12 OTSCC and paired normal tissue samples that was extracted from TCGA. Genes that show statistically significant differential expression were identified with bold font
cThe candidate targets of a microRNA were predicted using a collection of 12 bioinformatics tools, including DIANAmT, miRanda, microCosm, miRDB, miRWalk, RNAhybrid, PicTar (4-way), PicTar (5-way), PITA, RNA22, TargetScan5, and TargetScanHuman 6.2. The number of bioinformatics tools (out of a total of 12 tools tested here) that predict a gene to be a microRNA target was presented. The gene/microRNA pairs predicted by at least 3 tools were listed in the table
dCorrelations of microRNA and mRNA levels were assessed using dataset on 12 paired OTSCC and normal controls that was extracted from TCGA Data Portal. Inverted correlation (negative Pearson r value) is expected for a MRM, and p value was calculated
eCorrelations of microRNA and mRNA levels were assessed by quantitative real-time PCR based on 13 HNSCC cell line. Inverted correlation (negative Pearson r value) is expected for a MRM, and p value was calculated