Lung cancer is ranked at the first in both incidence and mortality worldwide [
At present, the latest theory shows that tumors are a kind of stem cell disease. Malignant tumors include a small portion of cancer stem cells (CSCs) and act as a pivotal part in the formation and growth of tumors. These CSCs have the ability to multiply, self-renew and differentiate, and express similar molecular markers and gene products [
To deeply understanding the relation between nanog overexpression and prognosis in lung cancer, we performed the present meta-analysis to assess the influence of nanog on survival and clinic-pathological parameters in patients.
The electronic database including PubMed, Cochrane Library, Web of Science, EMBASE database, Chinese CNKI, and the Chinese Wan Fang database was searched (Last update May 2018). Searches contained the terms “nanog or NANOG” (abstract/title) and “cancer or tumor or carcinoma or neoplasm” (abstract/title) and “lung or pulmonary” (abstract/title). All qualified studies were acquired and all references for those selected articles were screened and evaluated. Some review articles were manually retrieved to look for other qualified studies which were then assessed for inclusion by two reviewers (Wei Cheng and Juanjuan yuan). Divergences were resolved by consultation.
The included criteria for eligible studies in our meta-analysis are
The data was extracted from all qualified studies by two authors (Wei Cheng and Juanjuan Yuan). All the extracted data contained first author, publication year, country, number of cases, detect methods of nanog, antibody used, cut-off value of nanog, hazard ratios (HR) and 95% confidence intervals (CIs) (Table
Characteristics of studies included in the meta-analysis.
First author | Patient | Study | Number of patients | Method | Antibody | Cut-off | Follow-up | HR estimation | HR (95% CI) | Survival | Study quality (NOS) |
---|---|---|---|---|---|---|---|---|---|---|---|
Chiou-2010 | China | R | 118 (78/40) | IHC | CST | Position | 80 | Sur-curve | 1.47 (1.01-2.12) | OS | 7 |
Li-2013 | China | R | 309 (94/215) | IHC | CST | 5% | 69.5 | HR | 1.70 (1.25-2.32) | OS | 8 |
Du-2013 | China | R | 123 (98/25) | IHC | CST | Score 8 | 60 | Sur-curve | 5.48 (1.42-21.12) | OS | 7 |
Luo (1)-2013 | China | R | 62 (30/32) | IHC | CST | Position | 60 | HR | 2.11 (1.08-4.11) | OS | 6 |
Luo (2)-2013 | China | R | 106 (26/80) | IHC | CST | 25% | 60 | Sur-curve | 1.23 (0.85-1.79) | OS | 6 |
Mo-2014 | China | R | 50 (36/14) | IHC | CST | Position | No data | No data | No data | No data | 6 |
Sodja -2015 | Slovenia | R | 50 (25/25) | RT-PCR | median | 32.5 | HR | 1.30 (0.70-2.39) | OS, DFS | 6 | |
Park-2016 | Korea | R | 226 (96/130) | IHC | Epitomics | Grade 2 | 125 | HR | 1.70 (1.05–2.76) | OS, DFS | 8 |
Yao-2016 | China | R | 156 (129/27) | IHC | Proteintech | 10% | 25 | HR | 1.86 (1.02-3.36) | OS | 6 |
Chang-2017 | Korea | R | 112 (44/68) | IHC | CST | Position | 65 | HR | 3.00 (1.98–4.54) | OS, DFS | 8 |
Lee-2017 | Korea | R | 110 (55/55) | IHC | CST | Position | 65 | HR | 2.89 (2.18-4.62) | OS, DFS | 7 |
R, retrospective; P, positive; N, negative; IHC, immunohistochemistry; HR, hazard ratios; CI, confidence interval; OS, overall survival; DFS, disease free survival; NOS, Newcastle-Ottawa-Scale.
The studies quality was evaluated by Newcastle-Ottawa-Scale (NOS) criteria [
We divided the original aims into two categories for this meta-analysis. The first aim was to estimate the prognostic value of nanog overexpression on OS and DFS. HRs and 95% CIs were calculated by the survival data extracted from Kaplan-Meier curve with Engauge Digitizer version 4.1 as described before when not directly gained in studies [
619 potential relevant studies were searched from the databases according to the search terms. As shown in Figure
Flow diagram of the study selection in this meta-analysis.
Heterogeneity was significant among the included studies when assessing relationship between nanog overexpression and OS and DFS for lung cancer (
Pooled analysis for the association between nanog overexpression and OS. (a) Forest plots. (b) Funnel plots. (c) Sensitive analysis. OS, overall survival. HR, hazard ratio; CI, confidence intervals; se, standard error.
Pooled analysis for the association between nanog overexpression and DFS. (a) Forest plots. (b) Funnel plots. (c) Sensitive analysis. DFS, disease-free survival; HR, hazard ratio; CI, confidence intervals; se, standard error.
The relationship between nanog overexpression and clinical variable in lung cancer was estimated in our meta-analysis (Table
The associations between nanog overexpression and clinic-pathological features for lung cancer.
Heterogeneity | |||||||
| |||||||
Clinic-pathological features | No. of studies | No. of patients | Pooled OR (95% CI) | PHet | I2 | P value | Model used |
| |||||||
differentiation | 4 | 588 | 4.17 (2.71-6.43) | 0.795 | 0.0% | ≤0.001 | Fixed |
lymph node metastasis | 4 | 391 | 1.76 (1.06-2.91) | 0.738 | 0.0% | 0.028 | Fixed |
tumor size | 2 | 276 | 1.93 (1.17-3.20) | 0.462 | 0.0% | 0.010 | Fixed |
T stage | 2 | 432 | 0.85 (0.57-1.34) | 0.402 | 0.0% | 0.541 | Fixed |
TNM | 4 | 708 | 1.22 (0.88-1.68) | 0.472 | 0.0% | 0.227 | Fixed |
gender | 7 | 812 | 1.19 (0.87-1.62) | 0.546 | 0.0% | 0.287 | Fixed |
Random, random-effects model; fixed, fixed-effects model; OR, odds ratio; CI, confidence interval; NO, number of sample size.
Pooled analysis for the association between nanog overexpression and clinic-pathological features. (a) Differentiation. (b) Lymph node metastasis. (c) Tumor size. (d) T stage. (e) TNM stage. (f) Gender. OR, odds ratio; CI, confidence interval.
Subgroup analysis was used to explore possible sources of heterogeneity among OS (Table
Subgroup analysis of OS by pathological types, publication year, NOS score, and country.
Subgroup | No. of studies | No. of patients | P value | Pooled HR (95% CI) | PHet | I2 (%) |
---|---|---|---|---|---|---|
Pathological types | ||||||
Adenocarcinoma | 5 | 613 | ≤0.001 | 1.68 (1.34-2.11) | 0.375 | 5.6% |
Squamous cell carcinoma | 2 | 105 | 0.270 | 1.97 (0.59-6.55) | 0.009 | 85.4% |
Small cell carcinoma | 1 | 50 | 0.402 | 1.74 (0.70-2.23) | ||
Publication year | ||||||
2010-2016 | 8 | 1150 | ≤0.001 | 1.56 (1.33-1.83) | 0.819 | 0.0% |
2017 | 2 | 222 | ≤0.001 | 2.94 (2.22-3.88) | 0.896 | 0.0% |
NOS score | ||||||
<7 | 4 | 374 | 0.004 | 1.46 (1.12-1.89) | 0.432 | 0.0% |
≥7 | 6 | 998 | ≤0.001 | 2.01 (1.55-2.60) | 0.038 | 57.6% |
Country | ||||||
China | 6 | 874 | ≤0.001 | 1.57 (1.32-1.87) | 0.671 | 0.0% |
Other | 4 | 498 | ≤0.001 | 2.20 (1.52-3.19) | 0.051 | 61.5% |
OS, overall survival; NO, number of sample size; HR, hazard ratio; CI, confidence interval; NOS, Newcastle-Ottawa-Scale.
Subgroup analysis of DFS by pathological type, publication year, NOS score, and country.
Subgroup | No. of studies | No. of patients | P value | Pooled HR (95% CI) | PHet | I2 (%) |
---|---|---|---|---|---|---|
Pathological type | ||||||
Adenocarcinoma | 2 | 290 | 0.010 | 1.85 (1.16-2.96) | 0.189 | 41.9% |
Squamous cell carcinoma | 1 | 48 | ≤0.001 | 3.76 (1.89-7.49) | ||
Small cell carcinoma | 1 | 50 | 0.085 | 1.26 (0.97-1.64) | ||
Publication year | ||||||
2010-2016 | 2 | 276 | 0.008 | 1.34 (1.08-1.67) | 0.402 | 0.0% |
2017 | 2 | 222 | ≤0.001 | 2.92 (2.00-4.26) | 0.585 | 0.0% |
NOS score | ||||||
≤7 | 1 | 50 | 0.085 | 1.26 (0.97-1.64) | ||
>7 | 3 | 448 | 0.001 | 2.21 (1.36-3.61) | 0.061 | 64.2% |
Country | ||||||
China | 0 | 0 | ||||
Other | 4 | 498 | 0. 006 | 1.86 (1.20-2.90) | 0.004 | 77.2% |
DFS, disease free survival; NO, number of sample size; NOS, Newcastle-Ottawa-Scale; HR, hazard ratio; CI, confidence interval.
Begg’s funnel plot and Egger’s test were performed to evaluate the publication bias for OS and DFS in lung cancer patients in included studies. As shown in Figures
In order to appraise the effect of single study on the pooled HRs in OS and DFS because of significant heterogeneity, we carried out sensitivity analysis by estimating the average HRs in the absence of each study. The results demonstrated that our meta-analysis was statistically reliable (Figures
Lung cancer is a malignant tumor with high morbidity and mortality. Although there are many treatment strategies for lung cancer, the therapeutic effectiveness is still not satisfactory. It is emergency for us to explore the new mechanism of metastasis and recurrence and look for related prognostic markers and targets of therapeutic interventions to improve the prognosis for lung cancer.
More and more studies have showed that there is a small count of cells with self-renewal and differentiation in tumors. Their characteristics are similar to normal stem cells. We call them CSCs. Increased CSCs are often associated with tumor progression, relapse, and drug resistance [
Our outcomes showed that nanog overexpression have been involved with poor OS and DFS in lung cancer. For clinic-pathological features involved in lung cancer, we found that nanog overexpression was associated with differentiation, lymph node metastasis, and tumor size. The reasons for this may be that nanog can promote invasion, metastasis, and cell proliferation in lung cancer. Our results also demonstrated that no obvious relation was found between nanog overexpression and T stage, TNM stage, and gender. Because of obvious heterogeneity in OS and DFS, we carried out subgroup analysis based on pathological types, publication year, NOS score, and country. Our subgroup results showed that publication year might be considered as a source of heterogeneity. There was no significant heterogeneity in both publication year subgroup (2010-2016) and publication year subgroup (2017) for OS and DFS. Our results indicated that nanog overexpression led to poor OS and DFS in two subgroups. Du to absence heterogeneity for OS and DFS in adenocarcinoma subgroup based on pathological types, our outcome also demonstrated that there was a decreased OS and DFS for lung adenocarcinoma patients with high nanog expression compared with low nanog expression. We performed sensitivity analyses by evaluating the average HRs in the absence of each study. The results indicated that our meta-analysis was statistically reliable. And currently, the heterogeneity cannot be well elaborated and still requires some high quality studies with large sample. In short, our results suggested that nanog overexpression may indicate poor OS and DFS and susceptibility to poor differentiation and undifferentiation, lymph node metastasis, and tumor size (≥3cm). So, it is possible for us to improve OS and DFS for patients with lung cancer by targeting nanog therapy in future. We can also consider determining treatment strategies according to nanog expression level.
Publication bias is an important limitation in meta-analysis, because some studies with negative results are more difficult to be accepted for publication. Thus we should encourage some researchers to publish their studies including some negative results. Our results demonstrated that no significant evidence of publication bias was found in our included studies.
There are still so many other limitations in our study. First of all, prognosis data extracted from survival curves might be less reliable than reported directly in studies. Second, the antibody used, IHC cell-scoring method, and the cut-off value were not defined similarly in partial studies. Third, the heterogeneity of the OS and DFS is significant, although we performed subgroup analysis and sensitivity analyses. These factors may contribute to potential publication bias. Our sensitivity analyses indicated that the results were stable and the heterogeneity did not influence the analysis results.
To summarize, our results demonstrated that nanog overexpression, a hazard factor of differentiation, lymph node metastasis, and tumor size, may contribute to poor OS and DFS for lung cancer. Nanog might be a bad prognostic marker for lung cancer.
Overall survival
Disease-free survival
Hazard ratios
Odds ratios
Confidence intervals
Cancer stem cells
Immunohistochemistry
Reverse transcription polymerase chain reaction
Newcastle-Ottawa-Scale.
The funders had not taken part in study design, collection, and analysis of data, decision of publication, and preparation of the manuscript.
The authors declare that they have no conflicts of interest.
This work was supported by National Natural Science Foundation of China (Research Grant no. 81673743).