| Literature DB >> 33299862 |
Kui Fan1, Chuan-Long Zhang1, Yuan-Fu Qi2, Xin Dai2, Yoann Birling3, Zhao-Feng Tan2, Fang Cao2.
Abstract
BACKGROUND: The prognosis of non-small-cell lung cancer (NSCLC) has not been significantly improved. In the past several years, research on epigenetics is in full swing. There is a focus on the gene EZH2; however, its role as a predictor of the prognosis of NSCLC is in the debate.Entities:
Mesh:
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Year: 2020 PMID: 33299862 PMCID: PMC7705440 DOI: 10.1155/2020/2380124
Source DB: PubMed Journal: Biomed Res Int Impact factor: 3.411
Figure 1Flow diagram of the study selection process. HR: hazard ratio.
Main characteristics of the eligible studies.
| Study | Country | Method | Antibody Corp | Sample |
|
| Stage | Lung cancer type | Related characteristics |
|---|---|---|---|---|---|---|---|---|---|
| Kikuchi et al. 2010 [ | Japan | IHC | BD Transduction Laboratories, Mississauga, ON, Canada | Issue | 157 | 95 | I–IV | NSCLC (ADC and NADC) | Nonadenocarcinoma histology, moderate and poor differentiation, advanced pathologic tumor classification, and high Ki-67 and cyclin E labeling indices |
| Takawa et al. 2011 [ | Japan | IHC | Leica Microsystems, Wetzlar, Germany | Issue | 292 | 135 | pt1-pt, pN0-pn2, and pm0 | NSCLC | Stage (grade III tumors showed significantly higher EZH2 protein expression than grade I and grade II tumors) |
| Bondgaard et al. 2012 [ | Denmark | IHC | BD Transduction Laboratories, San Jose, CA, USA | Issue | 96 | 27 | I–IV | LENEC | Grade |
| Huqun et al. 2012 [ | China | IHC | Cell Signaling Technology, Danvers, MA | Issue | 106 | 66 | I | NSCLC | Tumor size |
| Chen et al. 2013 [ | Japan | IHC | Cell Signaling Technology, MA, USA | Issue | 42 | 18 | I | NSCLC (22 ADC and 20 SCC) | Male, non-ADC, smoking history, vessel invasion |
| Xu et al. 2014 [ | China | IHC | Cell Signaling Inc., Danvers, MA, USA | Issue | 360 | 204 | IIIB to IV | NSCLC | Higher TNM, poorer differentiation, nodal metastases |
| Geng et al. 2015 [ | China | IHC | Cell signaling | Issue | 195 | 96 | I–IV | NSCLC | Tumor differentiation, lymph node metastasis, size and TNM stage |
| Toyokawa et al. 2017 [ | Japan | IHC | Leica Biosystems, Newcastle-upon-Tyne, UK | Issue | 268 | 117 | I–IV | NSCLC | SUVmax、the presence of vascular invasion and SCC histology |
| Toyokawa et al. 2018 [ | Japan | IHC | Leica Biosystems, Newcastle-upon-Tyne, UK | Issue | 40 | 25 | I–III | SCLC | None |
| Matsubara et al. 2019 [ | Japan | IHC | Takara, Shiga, Japan | Issue | 350 | 182 | I–IV | Adenocarcinoma | Male sex, advanced stage, pleural and lymphovascular invasion, and vimentin expression |
| Behrens et al. 2013 [ | American | IHC | Mouse monoclonal, NCL-L; Novocastra, Leica Niosystem | Issue | I–III | NSCLC (SCC and ADC) | Age, gender, histology, disease stage, size of tumor, smoking status, EGFR mutation, KRAS mutation | ||
| Li et al. 2014 [ | China | PCR | OriGene Technology | Issue | 54 | 28 | I–III | NSCLC | Age, gender, histology, disease stage, size of tumor, smoking status, metastasis, and recurrence |
| Xu et al. 2013 [ | China | IHC | Cell Signaling Inc., Danvers, MA, USA | Issue | 60 | 22 | I–IV | NSCLC | Lymph node metastasis and TNM stages |
IHC: immunohistochemistry; PCR: polymerase chain reaction; NSCLC: non-small-cell lung carcinoma; SCLC: small-cell lung carcinoma; SCC: squamous cell carcinoma; ADC: adenocarcinoma; EGFR: estimated glomerular filtration rate; TNM: tumor node metastasis; N: number.
Summary of HRs and their 95% CI.
| Author | Year | HR | LCI | UCI |
|---|---|---|---|---|
| Kikuchi et al. [ | 2010 | 2.08 | 1.32 | 3.23 |
| Takawa et al. [ | 2011 | 1.482 | 1.051 | 2.091 |
| Bondgaard et al. [ | 2012 | 0.28 | 0.13 | 0.57 |
| Huqun et al. [ | 2012 | 2.8 | 1.19 | 6.59 |
| Chen et al. [ | 2013 | 1.975 | 0.775 | 5.031 |
| Xu et al. [ | 2014 | 4.32 | 2.13 | 8.73 |
| Geng et al. [ | 2015 | 2.39 | 1.66 | 3.46 |
| Toyokawa et al. [ | 2017 | 2.28 | 1.02 | 5.09 |
| Toyokawa et al. [ | 2018 | 0.57 | 0.16 | 2.01 |
| Matsubara et al. [ | 2019 | 2.64 | 1.41 | 4.94 |
| Behrens et al. [ | 2013 | 1.943 | 1.387 | 2.723 |
| Li et al. [ | 2014 | 0.45 | 0.15 | 1.35 |
CI: confidence interval; HR: hazard ratio; LCI: low confidence interval; UCI: upper confidence interval.
Quality assessment based on the Newcastle-Ottawa scale.
| Study | Year | Selection | Comparability | Outcome | Total score |
|---|---|---|---|---|---|
| Kikuchi et al. [ | 2010 | 4 | 2 | 2 | 8 |
| Takawa et al. [ | 2011 | 3 | 2 | 2 | 7 |
| Bondgaard et al. [ | 2012 | 4 | 1 | 2 | 7 |
| Huqun et al. [ | 2012 | 3 | 2 | 2 | 7 |
| Chen et al. [ | 2013 | 3 | 1 | 3 | 7 |
| Xu et al. [ | 2013 | 4 | 2 | 3 | 9 |
| Behrens et al. [ | 2013 | 4 | 2 | 2 | 8 |
| Xu et al. [ | 2014 | 4 | 1 | 2 | 7 |
| Li et al. [ | 2014 | 3 | 1 | 2 | 6 |
| Geng et al. [ | 2015 | 3 | 2 | 2 | 7 |
| Toyokawa et al. [ | 2017 | 3 | 2 | 2 | 7 |
| Toyokawa et al. [ | 2018 | 3 | 2 | 2 | 7 |
| Matsubara et al. [ | 2019 | 3 | 2 | 2 | 7 |
Figure 2Forest plot of overall survival analysis and disease-free survival analysis. (a) Meta-analysis of EZH2 expression and overall survival. (b) Meta-analysis of EZH2 expression and overall survival in different stages of lung cancer.
Figure 3Kaplan-Meier survival curves for lung cancer patients, stratified by EZH2 expression levels: (a) lung cancer, (b) lung adenocarcinoma, and (c) lung squamous cell carcinoma.
Figure 4TCGA data analysis. (a) Comparison of EZH2 expression between normal tissue and tumor tissue. (b) Comparison of EZH2 expression between stages of patients with lung cancer.
Figure 5TCGA data analysis. (a) Overall correlation between EZH2 and BRAF in adenocarcinoma and squamous cell carcinoma. (b) Correlation between EZH2 and BRAF in adenocarcinoma. (c) Correlation between EZH2 and BRAF in squamous cell carcinoma. (d) Overall correlation between EZH2 and EGFR in adenocarcinoma and squamous cell carcinoma. (e) Correlation between EZH2 and EGFR in adenocarcinoma. (f) Correlation between EZH2 and EGFR in squamous cell carcinoma. (g) Overall correlation between EZH2 and KRAS in adenocarcinoma and squamous cell carcinoma. (h) Correlation between EZH2 and KRAS in adenocarcinoma. (i) Correlation between EZH2 and KRAS in squamous cell carcinoma. (j) Overall correlation between EZH2 and smoking in adenocarcinoma and squamous cell carcinoma. (k) Correlation between EZH2 and smoking in adenocarcinoma. (l) Correlation between EZH2 and smoking in squamous cell carcinoma. Lung cancer: adenocarcinoma of lung and squamous cell lung carcinoma; LUAD: adenocarcinoma of lung; LUSC: squamous cell lung carcinoma; r: coefficient of correlation.
Figure 6Result of sensitivity analyses by omitting one study in each turn.
Begg's test.
| Begg's test |
|---|
| adj.Kendall′s score ( |
| Std.Dev.of score = 14.58 |
| Number of studies = 12 |
|
|
| Pr > ∣ |
|
|
| Pr > ∣ |
adj.: adjusted; Std. Dev.: standard deviation.
Figure 7Funnel plot of EZH2 and overall survival.
Egger's test.
| Egger's test | ||||||
|---|---|---|---|---|---|---|
| Std_Eff | Coef. | Std. err. |
|
| (95% Conf. interval) | |
| Slope | 0.930 | 0.401 | 2.320 | 0.043 | 0.036 | 1.824 |
| Bias | -1.331 | 1.464 | -0.910 | 0.385 | -4.592 | 1.93 |
Correlation between EZH2 and smoking in six studies.
| Study | OR | EZH2 high | EZH2 low | ||
|---|---|---|---|---|---|
| Yes | No | Yes | No | ||
| Kikuchi et al. 2010 [ | 8.69 | 74 | 11 | 24 | 31 |
| Takawa et al. 2011 [ | 3.64 | 114 | 21 | 94 | 63 |
| Chen et al. 2013 [ | 4.90 | 14 | 4 | 10 | 14 |
| Geng et al. 2015 [ | 1.02 | 50 | 46 | 51 | 48 |
| Toyokawa et al. 2018 [ | 5.50 | 22 | 1 | 12 | 3 |
| Li et al. 2014 [ | 0.23 | 10 | 12 | 25 | 7 |