| Literature DB >> 31632145 |
Qingming Xiang1, Zhenxian Xiang2, Rongzhang Dou2, Bin Xiong2.
Abstract
An increasing number of studies revealed that microRNA-22 as a biomarker may play a significant role in the cancer patients' prognosis, but the accurate prognosis value of microRNA-22 remains somewhat controversial. Thus, we comprehensively searched the database and performed this study to explicate the accurate value of microRNA-22 in the cancer patients' prognosis. This meta-analysis revealed that elevated expression of microRNA-22 correlated with good overall survival (OS) and disease-free survival (DFS)/progression-free survival (PFS)/recurrence-free survival (RFS) in cancers, while no significant association was found in metastasis-free survival (MFS)/distant metastasis-free survival (DMFS). Through the subgroup analysis for OS and DFS/PFS/RFS, we found that elevated expression of miR-22 significantly correlated with good prognosis in most subgroups, while it predicted a worse prognosis in nasopharyngeal carcinoma subgroup. And besides that, elevated expression of miR-22 was negatively correlated with TNM stage, lymph node metastasis, distant metastasis and recurrence, while no significant association was found between microRNA-22 expression and T stage, tumor differentiation, and lymphatic invasion. Our meta-analysis demonstrated that elevated expression of microRNA-22 predicted a good OS and DFS/PFS/RFS in cancer patients; meanwhile, its high expression also means earlier TNM stage, and lower likelihoods of lymph node metastasis, of distant metastasis and of recurrence. If we regularly monitor miR-22 expression in cancer patients, it might be useful for us to predict cancer prognosis in future clinical applications.Entities:
Keywords: biomarker; cancer; clinicopathological; hsa-miR-22; meta-analysis; prognosis
Year: 2019 PMID: 31632145 PMCID: PMC6790216 DOI: 10.2147/CMAR.S185124
Source DB: PubMed Journal: Cancer Manag Res ISSN: 1179-1322 Impact factor: 3.989
Figure 1Flowchart of the study selection process.
Main characteristics of 26 studies after screening
| Study ID | Origin of | Tissue | Disease | Specimen | Number | Stage | miR-22 assay | Cutoff | Survival analysis | HR (95% CI) | Follow-up time (months) | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Wan 2014 | China | Fresh | EOC | Tissue | 109 | I-IV | qRT-PCR | Median value | OS/PFS | Reported | 0.007/0.005 | 60 |
| Delfino 2013 | TCGA | – | EOC | Tissue | 418/249 | I-IV | qRT-PCR | NR | OS/RFS | Reported | <0.0001 | 160 |
| Li 2013 | China | FTT | EOC | Tissue | 45 | I-IV | qRT-PCR | Mean values | OS/PFS | SC | 0.550/0.175 | 80/160 |
| Zhou 2013 | China | FTT | HCC | Tissue | 192 | I-IV | qRT-PCR | Median value | OS | SC | 0.046 | 80 |
| Zhang 2010 | China | – | HCC | Tissue | 160 | I-IV | qRT-PCR | Median value | DFS | SC | 0.025 | 48 |
| Chen 2016 | TCGA | FTT | HCC | Tissue | 372 | I-IV | qRT-PCR | Mean value | OS | Reported | 0.0109 | 120 |
| Zhang 2012 | China | FFPE | CRC | Tissue | 86 | I-IV | qRT-PCR | Median value | OS | Reported | 0.042 | 68 |
| Slattery 2015 | American | FTT | CRC | Tissue | 1141 | I-IV | qRT-PCR | Mean value | OS (Co/Re) | Reported | >0.05 | 120 |
| Xia 2017 | China | – | CRC | Tissue | 110 | I-IV | qRT-PCR | log2 (miR-22)>0 | RFS | Reported | 0.0018 | 82 |
| Zuo 2015 | China | Fresh | GC | Tissue | 61 | I-IV | qRT-PCR | Mean value | OS | SC | 0.038 | 40 |
| Tang 2015 | China | FFPE | GC | Tissue | 89 | I-IV | ISH | Expression score | – | – | – | – |
| Wang.2013 | China | FTT | GC | Tissue | 98 | I-IV | qRT-PCR | Median value | OS | Reported | 0.04 | 60 |
| Patel 2011 | GEO | Fresh | BC | Tissue | 1809 | NR | qRT-PCR | Mean value | OS/RFS/MFS | Reported | 0.82/0.0047/0.06 | 170 |
| Chen 2015 | China | FTT | BC | Tissue | 122 | I-IV | qRT-PCR | Median value | OS/DFS | Reported/SC | 0.006/0.003 | 120 |
| Yoshimoto 2011 | Japan | – | BC | Tissue | 171 | I-IV | qRT-PCR | Mean value | OS | Reported | 0.67 | 150 |
| Song 2013 | American | FTT | BC | Tissue | 108 | I-IV | qRT-PCR | NR | RFS | Reported | 0.022 | 84 |
| Fan 2016 | China | FTT | RCC | Tissue | 68 | I-IV | qRT-PCR | Mean value | – | – | – | – |
| Zhang 2016 | China | FTT | RCC | Tissue | 50 | I-IV | qRT-PCR | Median value | – | – | – | – |
| Wang 2015 | China | - | OST | Tissue | 52 | I-IV | qRT-PCR | Median value | OS/DFS | Reported | 0.004/0.002 | 60 |
| Song 2013 | American | FTT | MDS | Tissue | 107 | I-IV | ISH | Expression score | OS | SC | <0.0005 | 75 |
| Wang X C 2013 | China | – | ESCC | Tissue | 100 | I-IV | qRT-PCR | Mean value | OS | SC | 0.237 | 80 |
| Liu 2014 | China | – | NPC | Serum | 512 | I-IV | qRT-PCR | Median risk score | OS/DMFS(T,V) | Reported | <0.01 | 132 |
| Li 2014 | China | FTT | glioma | Tissue | 72 | I-IV | qRT-PCR | Mean value | OS | SC | <0.05 | 42 |
| Lionetti 2013 | American | – | pPCL | Tissue | 18 | I-IV | qRT-PCR | NR | PFS | SC | 0.001 | 32 |
| Du 2017 | China | FTT | Bla Ca | Urine | 240 | I-IV | qRT-PCR | Median value | RFS | Reported | 0.024 | 80 |
| Zou 2017 | China | FTT | BC | Tissue | 72 | I-IV | qRT-PCR | Mean | – | – | – | – |
Abbreviations: miR-22, microRNA-22; T, training set; V, validation set; NR, not reported; Co, colon set; Re, rectal set; “-”, not mentioned; q-RCR, quantitative real-time polymerase chain reaction; ISH, in situ hybridization; SC, survival curve; OS, overall survival; PFS, progression-free survival; DFS, disease-free survival; RFS, recurrence free survival; MFS, metastasis-free survival; DMFS, distant metastasis-free survival; TCGA, The Cancer Genome Atlas; GEO, gene expression omnibus; BC, breast cancer; EOC, epithelial ovarian cancer; CRC colorectal carcinoma; HCC, hepatocellular carcinoma; NPC, nasopharyngeal carcinoma; GC, gastric cancer; OST, osteosarcoma; MDS, myelodysplastic syndrome; ESCC, esophageal squamous cell carcinoma; pPCL, primary plasma cell leukemia; Bla Ca, bladder cancer; RCC, renal cell carcinoma.
Figure 2Forest plot of miR-22 expression and overall survival in various cancers.
Meta-analysis of overall and subgroup analysis for miR-22 expression and OS in cancers
| Categories | Studies | HR (95% CI) | Model | Heterogeneity | |
|---|---|---|---|---|---|
| 19 | 0.76 (0.62–0.92) | Random | 78.4 | 0.000 | |
| HCC | 2 | 0.40 (0.26–0.62) | Fixed | 0 | 0.511 |
| CRC | 3 | 0.92 (0.83–1.03) | Fixed | 49.6 | 0.137 |
| NPC | 2 | 1.90 (1.37–2.63) | Fixed | 0 | 0.776 |
| EOC | 3 | 0.42 (0.20–0.86) | Random | 64.7 | 0.059 |
| GC | 2 | 0.90 (0.24–3.39) | Random | 68.5 | 0.075 |
| BC | 3 | 0.81 (0.54–1.22) | Random | 66 | 0.053 |
| Tissue | 17 | 0.67 (0.55–0.81) | Random | 75.5 | 0.000 |
| Serum | 2 | 1.90 (1.37–2.63) | Random | 0 | 0.776 |
| Digestive system | 8 | 0.74 (0.58–0.95) | Random | 65.9 | 0.005 |
| Reproduction system | 6 | 0.55 (0.33–0.93) | Random | 84.5 | 0.000 |
| Adenocarcinoma | 11 | 0.75 (0.61–0.92) | Random | 74.9 | 0.000 |
| Squamous cell carcinoma | 3 | 1.52 (0.97–2.37) | Random | 62.3 | 0.022 |
| Tumor of mesenchymal tissue | 2 | 0.70 (0.10–4.99) | Random | 80.8 | 0.071 |
| Asian | 13 | 0.73 (0.52–1.01) | Random | 77.6 | 0.000 |
| Caucasian | 3 | 0.94 (0.84–1.05) | Fixed | 0 | 0.414 |
| q-PCR | 18 | 0.74 (0.61–0.91) | Random | 79.3 | 0.000 |
| ISH | 1 | 2.01 (0.51–7.95) | Random | – | – |
| Fresh tissue | 4 | 1.31 (0.68–2.52) | Random | 76.7 | 0.005 |
| Unclear method (-) | 4 | 0.58 (0.28–1.16) | Random | 79.5 | 0.002 |
| FTT | 9 | 0.88 (0.76–1.01) | Random | 53.7 | 0.027 |
| FFPE | 2 | 0.32 (0.18–0.56) | Fixed | 0 | 0.634 |
Abbreviations: miR-22, microRNA-22; “-”, not mentioned; ISH, in situ hybridization; OS, overall survival; BC, breast cancer; EOC, epithelial ovarian cancer; CRC colorectal carcinoma; HCC, hepatocellular carcinoma; NPC, nasopharyngeal carcinoma; GC, gastric cancer.
Figure 3Forest plot of subgroup analysis for OS: (A) subgroup analysis for the anatomy system of cancer (digestive system and reproduction system); (B) subgroup analysis for the main pathological type of cancer; (C) subgroup analysis for different sample type (tissue or serum); (D) subgroup analysis for different assay method for miR-22 expression (q-PCR and ISH).
Figure 4Forest plot of miR-22 expression and disease progress: (A) subgroup analysis for PFS/DFS/RFS and MFS/DMFS; (B) subgroup analysis for different indicator type (PFS, DFS, RFS); (C) subgroup analysis for PFS/DFS/RFS in EOC subgroup.
Meta-analysis of overall and subgroup analysis for miR-22 expression and disease progress in cancers
| Categories | Studies | HR (95% CI) | Model | Heterogeneity | |
|---|---|---|---|---|---|
| 11 | 0.57 (0.37–0.87) | Random | 79.1 | 0 | |
| 3 | 1.57 (0.67–3.68) | Random | 90.3 | 0 | |
| PFS | 3 | 0.45 (0.19–1.08) | Random | 62 | 0.072 |
| RFS | 5 | 0.86 (0.39–1.88) | Random | 86 | 0.000 |
| DFS | 3 | 0.40 (0.21–0.76) | Random | 54.8 | 0.11 |
| NPC | 2 | 2.35 (1.59–3.47) | Fixed | 0 | 0.749 |
| BC | 3 | 0.86 (0.30–2.47) | Random | 82.6 | 0.003 |
| EOC | 3 | 0.28 (0.17–0.44) | Fixed | 0 | 0.016 |
| Asian | 9 | 0.69 (0.36–1.31) | Random | 87.0 | 0.000 |
| Caucasian | 2 | 2.09 (0.46–9.48) | Random | 63.8 | 0.097 |
Abbreviations: miR-22, microRNA-22; OS, overall survival; PFS, progression-free survival; DFS, disease-free survival; RFS, recurrence-free survival; MFS, metastasis-free survival; EOC, epithelial ovarian cancer; NPC, nasopharyngeal carcinoma; DMFS, distant metastasis-free survival.
Figure 5Forest plot of miR-22 expression and clinicopathological features. (A) subgroup analysis for miR-22 expression and TNM stage; (B) subgroup analysis for miR-22 high expression and lymph node metastasis; (C) subgroup analysis for miR-22 high expression and distant metastasis; (D) subgroup analysis for miR-22 high expression and recurrence.
Figure 6Sensitivity analysis and publication bias analysis under a specific model. (A), sensitivity analysis for overall survival; (B) sensitivity analysis for disease progress (PFS/RFS/DFS); (C) funnel plot of publication bias for OS; (D) funnel plot of publication bias for disease progress (PFS/RFS/DFS).
Meta-analysis of miR-22 high expression and clinicopathological features
| Categories | Studies | RR (95% CI) | Model | Heterogeneity | |
|---|---|---|---|---|---|
| TNM stage | 9 | 0.48 (0.34–0.67) | Random | 72.9 | 0.000 |
| Lymph node metastasis | 9 | 0.55 (0.40–0.77) | Random | 72.1 | 0.000 |
| T stage | 5 | 0.87 (0.70–1.07) | Fixed | 37.2 | 0.173 |
| Distant metastasis | 6 | 0.28 (0.18–0.43) | Fixed | 0 | 0.960 |
| Tumor differentiation | 5 | 0.99 (0.85–1.15) | Fixed | 49.0 | 0.0970 |
| Recurrence | 3 | 0.51 (0.32–0.80) | Fixed | 44 | 0.167 |
| Lymphatic invasion | 3 | 0.86 (0.70–1.05) | Fixed | 33.5 | 0.222 |