| Literature DB >> 33906290 |
Sasidharanpillai Sabeena1, Nagaraja Ravishankar2.
Abstract
AIM: There is growing evidence for the possible use of microRNAs (miRNAs) in cancers as diagnostic as well as prognostic biomarkers in the present era of Personalized Medicine. The objective of the present systematic review and meta-analysis was to assess the prognostic role of microRNAs in uterine cervical cancers.Entities:
Keywords: Cervical cancer; MicroRNA; Overall survival; Prognosis; miRNA
Year: 2021 PMID: 33906290 PMCID: PMC8325113 DOI: 10.31557/APJCP.2021.22.4.999
Source DB: PubMed Journal: Asian Pac J Cancer Prev ISSN: 1513-7368
Figure 1.PRISMA Chart Ddetailing the Study Selection Process. The flow diagram demonstrating the number of studies identified, records screened, full-text articles evaluated for the eligibility, and the studies included in the systematic review and meta-analysis
Main Characteristics of Qualified Studies for Meta-Analysis (n=14)
| Reference (years) | Country | Age (years) | Number (n) | Sample | Histology | Lymph node metastasis | Quality of studies NOS | |||
|---|---|---|---|---|---|---|---|---|---|---|
| squamous | Non-squamous | No | Yes | Good | ||||||
| 1 | Liu 2018 24 | China | Mean 46.3 | 31 | Snap frozen tissue | 31 | 0 | Not available | Not available | Good |
| 2 | Zhou 2018 255 | China | < 65- 76 | 181 | Snap frozen Tissue | 74 | 107 | 114 | 67 | Good |
| 3 | Zhang 2016 27 | China | < 65- 81 | 186 | Snap frozen | 137 | 49 | 82 | 104 | Good |
| 4 | Fang et al 2016 7 | China | <50-63 | 129 | Snap frozen tissue | 86 | 43 | 78 | 51 | Good |
| 5 | Min Luo et al 20152 | China | <50- 35 ≥50-53 | 88 | Snap frozen tissue | 62 | 26 | 42 | 46 | Good |
| 6 | Yin et al 2015 29 | China | <55-37 ≥55- 59 | 96 | Flash frozen tissue | 67 | 29 | 43 | 53 | Good |
| 7 | Wang Q 2015 26 | China | Median 50 | 114 | Snap frozen tissue | 114 | 0 | 43 | 71 | Good |
| 8 | Fan et al 2015 30 | China | Mean 54.4±9.9 | 55 | Snap frozen tissue | 50 | 5 | 26 | 29 | Good |
| 9 | Yang et al 2014 31 | China | < 65- 56 | 133 | Snap frozen tissue | 101 | 32 | 70 | 63 | Good |
| 10 | Shen et al 2013 8 | China | Median 50 | 126 | Frozen tissue | 126 | 0 | 44 | 82 | Good |
| 11 | Jiang 2017 23 | China | Mean 53±9 | 182 | serum | 139 | 43 | 145 | 37 | Good |
| 12 | Sun 2017 22 | China | ≤60-22 | 40 | serum | 10 | 30 | 11 | 29 | Good |
| 13 | Liu 2015 21 | China | <50-64 | 105 | serum | 84 | 21 | 68 | 37 | Good |
| 14 | Q Ma 2014 20 | China | Median 51 | 60 | serum | 60 | 0 | 22 | 38 | Good |
NOS, New castle Ottawa scale
Prognostic Value of Micro RNAs in Uterine Cervical Cancer (n=14)
| Author (year) | Follow up (months) | miRNA | HPV status | HR (95% CI) | 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 | 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 |
Figure 2Forest Plot of the Pooled Hazard Ratio (HR) of microRNAs Expressed in Tissues with Overall Survival among Cervical Cancer Patients. The summary estimates were obtained by the random-effects model. The diamond data specifies pooled HRs. CI –confidence interval
Figure 3Forest Plot of the Pooled Hazard Ratio (HR) of microRNAs Expressed in Serum Samples of Cervical Cancer Cases with Overall Survival. The summary estimates were obtained by the random-effects model. The diamond data specifies pooled HRs. CI –confidence interval
Result of Egger's Test of Forest Plot Regarding the Pooled Hazard Ratio (HR) of microRNAs Expressed in Tissues of Cervical Cancer Cases
| Coefficient | Estimate (95%CI) | P-value |
|---|---|---|
| Slope | -0.2905 (-1.4353, 0.8544) | 0.575 |
| Bias | 2.7114 (-3.0859, 8.5087) | 0.312 |
Results of Egger’s Test of Forest Plot Regarding the Pooled Hazard Ratio (HR) of microRNAs Expressed in Serum Samples of Cervical Cancer Cases
| Coefficient | Estimate (95%CI) | P-value |
|---|---|---|
| Slope | 2.2598 (-4.2961, 8.8157) | 0.276 |
| Bias | -5.8059 (-29.6182, 18.0063) | 0.404 |