Table 2.
Prognostic Value of Micro RNAs in Uterine Cervical Cancer (n=14)
| Author (year) | Follow up (months) | miRNA | HPV status | HR (95% CI) Multivariate analysis |
Potential targets | Expression Associates with poor prognosis | ||
|---|---|---|---|---|---|---|---|---|
| (+) | (-) | |||||||
| 1 | Liu 2018 24 | 24 | miRNA- 361-3p | --- | ---- | 0.377 (0.233-0.608) | SOST, MTA1, TFRC,YAP1 | Low |
| 2 | Zhou 2018 25 | 60 | miRNA-1254 | 127 | 54 | 2.889 (1.452-6.886) | N4BP3 | Low |
| 3 | Zhang 2016 27 | 70 | miRNA-664 | 132 | 54 | 4.21 (2.36-17.32) | c-Kit | Low |
| 4 | Fang et al 2016 7 | 60 | miRNA-155 | 79 | 50 | 2.32 (1.259-4.276) | LKB1 SMAD2, CCND, |
High |
| 5 | Min Luo et al 201528 | 74 (mean) | miRNA-26b | 39 | 49 | 2.107(1.744-3.211) | JAG1 | Low |
| 6 | Yin et al 2015 29 | 60 | miRNA-503 | 44 | 52 | 2.327(1.922-3.436) | CCND1 | Low |
| 7 | Wang Q 2015 26 | 47 (median) | miRNA-145 | 70 | 44 | 0.63 (0.54–0.83) | IRS-1, HLTF | Low |
| 8 | Fan et al 2015 30 | 42 | MiRNA-125a | --- | ----- | 0.691(0.418-1.141) | STAT 3 | Low |
| 9 | Yang et al 2014 31 | 60 | miRNA-126 | 97 | 36 | 3.97(2.01-20.22) | ZEB 1 | Low |
| 10 | Shen et al 2013 8 | Median 51.9 | miRNA-224 | 78 | 48 | 1.59(1.12-2.26) | PTX3 | High |
| 11 | Jiang 2017 23 | 60 | miRNA-101 | - | - | 2.820 (1.473–3.925) | COX-2 | Low |
| 12 | Sun 2017 22 | 60 | miRNA-425-5p | - | - | 1.957 (1.224-2.843) | AIFM1 | High |
| 13 | Liu 2015 21 | 80 | miRNA-196a | 92 | 13 | 3.51 (1.961–6.874) | HOXC8 | High |
| 14 | Q Ma 2014 20 | 60 | miRNA-205 | 54 | 6 | 0.33 (0.14-0.76) | CYR61 and CTGF | High |