| Literature DB >> 29228743 |
Gang Liu1, Disheng Xiong2, Junjie Zeng1, Guoxing Xu1,2, Rui Xiao2, Borong Chen1, Zhengjie Huang1,2.
Abstract
Recently, the oncogenic role of DEK has been recognized in several cancer types. However, its prognostic role in human solid tumor remains unclear. Thus, the present meta-analysis, based on 14 published studies (2208 patients) searched from PubMed, Web of Science, and EMBASE databases, assessed the prognostic value of DEK in human solid tumors. Furthermore, the pooled hazard ratio (HR) for overall survival (OS) was evaluated with fixed-effects models. A subgroup analysis was also performed according to the patients' ethnicities and tumor types. Data from these published studies were extracted, and the results showed that the overexpression of DEK was significantly associated with poor OS in human solid tumors. The combined hazards ratio was (HR = 1.83; 95% CI, 1.64-2.05, P < 0.00001) for OS (univariable analysis) with a fixed-effects model without any significant heterogeneity (P = 0.71, I2 = 0%). The combined HR was (HR = 1.70; 95% CI, 1.48-1.96, P < 0.00001) for OS (multivariable analysis) with a fixed-effects model, and no significant heterogeneity was observed (P = 0.36, I2 = 9%). Therefore, the overexpression of DEK was correlated with poor survival in human solid tumors, which suggests that the expression status of DEK is a valuable biomarker for the prediction of prognosis and serves as a novel therapeutic target in human solid tumors.Entities:
Keywords: DEK; meta-analysis; solid tumors
Year: 2017 PMID: 29228743 PMCID: PMC5716783 DOI: 10.18632/oncotarget.19684
Source DB: PubMed Journal: Oncotarget ISSN: 1949-2553
Figure 1Flow diagram shows search strategy
The characteristics of the included studies
| References | Country | Type of cancer | Patient No. | Male / Female | TNM staging | Detect method (Cut-off) | Increased DEK (%) | Fellow-up (months) | Survival analysis | HR (95%CI) | HR (Obtain) |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Shibata T, et al. (2010) | Japan | LC | 79 | NR | NR | IHC (NR) | 35 (44.3%) | 120 | OS (U) | 1.87 (1.10–3.19) | Curve |
| Lin LJ, et al. (2013) | China | HCC | 178 | 116/62 | I–IV | IHC (> 5%) | 86 (48.3%) | 60 | OS (U) | 1.94 (1.45–2.60) | Direct |
| Lin L, et al. (2013) | China | CRC | 99 | 87/22 | I–III | IHC (>25%) | 53 (53.5%) | 60 | OS (U) | 1.54 (1.06–2.25) | Direct |
| Lin D et al. (2014) | Canada | NEPC | 160 | NR | I–IV | IHC (Score > 1) | 5 (3.1%) | 120 | DFS (U) | 16.98 (3.59–80.38) | Direct |
| Martinez UJ, et al. (2014) | Spain | CRC | 67 | 47/20 | NR | IHC (NR) | 21 (31.3%) | 120 | OS (U) | 2.83 (1.24–6.46) | Direct |
| Piao J, et al. (2014) | China | GC | 172 | 102/70 | I–IV | IHC (> 25%) | 114 (70.3%) | 84 | OS (U) | 1.58 (1.15–2.17) | Direct |
| Wang X, et al. (2014) | China | LC | 130 | 72/58 | I–III | IHC (> 25%) | 58 (44.6%) | 60 | OS (U) | 1.63 (1.15–2.31) | Direct |
| Yi HC, et al. (2015) | China | HCC | 55 | 43/12 | I–IV | IHC (> 25%) | 26 (47.2) | 60 | OS (U) | 2.27 (1.47–3.51) | Direct |
| Ying G, et al. (2015) | China | BC | 628 | NR | I–III | IHC (NR) | 389 (61.9%) | 60 | OS (U) | 2.70 (1.49–4.88) | Curve |
| Ou Y, et al. (2016) | China | GC | 192 | 148/44 | I–IV | IHC (> 50%) | 84 (43.8%) | 60 | OS (U) | 1.77 (1.16–2.71) | Direct |
| Riveiro FE, et al. (2016) | Spain | Melanoma | 99 | 47/52 | NR | IHC (> 25%) | 42 (42.4%) | 120 | OS (U) | 2.28 (1.31–3.97) | Direct |
| Liu X, et al. (2016) | China | LC | 196 | 109/87 | I–IV | IHC (> 5%) | 130 (66.3%) | 96 | OS (U) | 1.53 (1.13–2.07) | Direct |
| Yu L, et al. (2016) | China | HCC | 66 | NR | NR | PCR | 33 (50%) | 60 | OS (U) | 1.96 (1.24–3.10) | Curve |
| Sun J, et al. (2017) | China | PDAC | 87 | 48/39 | I–IV | IHC (> 50%) | 46 (52.9) | 30 | OS (U) | 2.28 (1.45–3.58) | Direct |
BC: Breast Cancer; CI: Confidence interval; CRC: Colorectal Cancer; DFS: Disease-free survival; GC: Gastric cancer; HCC: Hepatocellular Carcinoma; HR: Hazard ratio; IHC: Immunohistochemistry; LC: Lung Cancer; M: Multivariable analysis; NEPC: Neuroendocrine prostate cancer; NR: Not Reported; OS: Overall survival; PDAC: Pancreatic ductal adenocarcinoma; U:Univariable analysis.
Figure 2Meta-analysis of the association between DEK and OS (univariable analysis)
Figure 3Meta-analysis of the association between DEK and OS (multivariable analysis)
Pooled HR for OS according to subgroup analysis
| References | No. of patients | No. of studies | Fixed-effect model | Heterogeneity | ||
|---|---|---|---|---|---|---|
| HR (95% CI) | I2 (%) | |||||
| | 2048 | 13 | 1.83 (1.64–2.05) | < 0.00001 | 0% | 0.71 |
| | 1097 | 9 | 1.70 (1.48–1.96) | < 0.00001 | 9% | 0.36 |
| | 916 | 8 | 1.87 (1.62–2.15) | < 0.00001 | 0% | 0.69 |
| | 1096 | 5 | 1.77 (1.47–2.13) | < 0.00001 | 0% | 0.42 |
| | 672 | 6 | 1.83 (1.52–2.19) | < 0.00001 | 18% | 0.30 |
| | 389 | 3 | 1.53 (1.23–1.97) | < 0.00001 | 0% | 0.53 |
| | 1704 | 11 | 1.80 (1.60–2.02) | < 0.00001 | 0% | 0.72 |
| | 166 | 2 | 2.24 (1.54–3.86) | < 0.00001 | 0% | 0.67 |
| | 931 | 7 | 1.67 (1.44–1.93) | < 0.00001 | 22% | 0.26 |
| | 166 | 2 | 2.15 (1.32–3.51) | < 0.00001 | 0% | 0.75 |
Quality assessment of eligible studies with Newcastle-Ottawa Scale
| References | Year | Selection | Comparability | Outcome | NOS |
|---|---|---|---|---|---|
| Shibata T, et al. | 2010 | ⋆⋆⋆ | ⋆ | ⋆⋆ | 6 |
| Lin LJ, et al. | 2013 | ⋆⋆⋆ | ⋆⋆ | ⋆⋆ | 7 |
| Lin L, et al. | 2013 | ⋆⋆⋆ | ⋆⋆ | ⋆⋆⋆ | 8 |
| Lin D, et al. | 2014 | ⋆⋆⋆ | ⋆ | ⋆⋆ | 6 |
| Martinez UJ, et al. | 2014 | ⋆⋆⋆ | ⋆⋆ | ⋆⋆ | 7 |
| Piao J, et al. | 2014 | ⋆⋆⋆ | ⋆⋆ | ⋆⋆⋆ | 8 |
| Wang X, et al. | 2014 | ⋆⋆⋆ | ⋆⋆ | ⋆⋆⋆ | 8 |
| Yi HC, et al. | 2015 | ⋆⋆⋆ | ⋆⋆ | ⋆⋆⋆ | 8 |
| Ying G, et al. | 2015 | ⋆⋆⋆ | ⋆ | ⋆⋆ | 6 |
| Ou Y, et al. | 2016 | ⋆⋆⋆ | ⋆⋆ | ⋆⋆⋆ | 8 |
| Riveiro FE, et al. | 2016 | ⋆⋆⋆ | ⋆⋆ | ⋆⋆⋆ | 8 |
| Liu X, et al. | 2016 | ⋆⋆⋆ | ⋆⋆ | ⋆⋆⋆ | 8 |
| Yu L, et al. | 2016 | ⋆⋆⋆ | ⋆ | ⋆⋆ | 6 |
| Sun J, et al. | 2017 | ⋆⋆⋆ | ⋆⋆ | ⋆⋆⋆ | 8 |
Figure 4Summary of Begg's funnel plots of publication bias for OS in all patients (A) univariable analysis; (B) multivariable analysis.