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. Objective. To clarify if the expression level of EZH2 can influence the prognosis of NSCLC and explain its prognostic value. Methods. We have systematically searched PubMed, Web of Science, and Cochrane library, screened relevant articles, and conducted a meta-analysis on the expression level of EZH2 in NSCLC. We collected the hazard ratio (HR) and the 95% confidence interval (CI) and used STATA 12.0 to calculate the combined result of EZH2 overall survival. In addition, we conducted subgroup analyses, a sensitivity analysis, and a funnel plot to test the reliability of the results. We further validated these meta-analysis results using the Kaplan-Meier plotter database and The Cancer Genome Atlas (TCGA) database. In addition, we have investigated the correlation between EZH2 expression and EGFR expression, KRAS expression, BRAF expression, and smoking in TCGA database to further explore the mechanism behind the influence of high EZH2 expression on lung cancer prognosis. Results. 13 studies including 2180 participants were included in the meta-analysis. We found that high expression of EZH2 indicates a poor prognosis of NSCLC ( HR = 1.65 and 95% CI 1.16-2.35; p ≤ 0.001 ). Subgroup analyses showed high heterogeneity in stages I-IV ( I 2 = 85.1 % and p ≤ 0.001 ) and stages I-III ( I 2 = 66.9 % and p = 0.029 ) but not in stage I ( I 2 = 0.00 % and p = 0.589 ). In the Kaplan-Meier plotter database, there was a high expression in 963 cases and low expression in 964 cases ( HR = 1.31 and 95% CI 1.15-1.48; p < 0.05 ). Further analysis found that the high expression of EZH2 was statistically significant in lung adenocarcinoma ( HR = 1.27 and 95% CI 1.01−1.6; p = 0.045 ), but not in lung squamous cell carcinoma ( HR = 1.03 and 95% CI 0.81−1.3; p = 0.820 ). The results of the TCGA database showed that the expression of EZH2 in normal tissues was lower than that in lung cancer tissues ( p < 0.05 ). Smoking was associated with high expression of EZH2 ( p < 0.001 ). EZH2 was also highly expressed in lung cancers with positive KRAS expression, and the correlation was positive in lung adenocarcinoma ( r = 0.3129 and p < 0.001 ). The correlation was also positive in lung squamous cell carcinoma ( r = 0.3567 and p < 0.001 ). EZH2 expression was positively correlated with BRAF expression ( r = 0.2397 and p < 0.001 ), especially in lung squamous cell carcinoma ( r = 0.3662 and p < 0.001 ). In lung squamous cell carcinoma, a positive yet weak correlation was observed between EZH2 expression and EGFR expression ( r = 0.1122 and p < 0.001 ). Conclusions. The high expression of EZH2 indicates a poor prognosis of NSCLC, which may be related to tumor stage or cancer type. EZH2 may be an independent prognostic factor for NSCLC. EZH2 high expression or its synergistic action with KRAS and BRAF mutations affects the prognosis of non-small-cell lung cancer.

Background: Systemic inflammation is a key factor in tumor growth. The Glasgow Prognostic Score (GPS) has a certain value in predicting the prognosis of lung cancer. However, these results still do not have a unified direction.Methods: A systematic review and meta-analysis were performed to investigate the relationship between GPS and the prognosis of patients with non-small cell lung cancer (NSCLC). We set patients as follows: GPS = 0 vs. GPS = 1 or 2, GPS = 0 vs. GPS = 1, GPS = 0 vs. GPS = 2. We collected the hazard ratio (HR) and the 95% confidence interval (CI).Results: A total of 21 studies were included, involving 7333 patients. We observed a significant correlation with GPS and poor OS in NSCLC patients (HRGPS=0 vs. GPS=1 or 2 = 1.62, 95% CI: 1.27–2.07, p ≤ .001; HRGPS=0 vs GPS=1 = 2.14, 95% CI:1.31–3.49, p ≤ .001; HRGPS=0 vs. GPS=2 = 2.64, 95% CI: 1.45–4.82, p ≤ .001). Moreover, we made a subgroup analysis of surgery and stage. The results showed that when divided into GPS = 0 group and GPS = 1 or 2 group, the effect of high GPS on OS was more obvious in surgery (HR = 1.79, 95% CI: 1.08–2.97, p = .024). When GPS was divided into two groups (GPS = 0 and GPS = 1 or 2), the III-IV stage, higher GPS is associated with poor OS (HR = 1.73, 95% CI: 1.43–2.09, p ≤ .001). In the comparison of GPS = 0 and GPS = 1 group (HR = 1.56, 95% CI: 1.05–2.31, p = .026) and the grouping of GPS = 0 and GPS = 2(HR = 2.23, 95% CI: 1.17–4.26, p = .015), we came to the same conclusion.Conclusion: For patients with NSCLC, higher GPS is associated with poor prognosis, and GPS may be a reliable prognostic indicator. The decrease of GPS after pretreatment may be an effective way to improve the prognosis of NSCLC.

Objective To analyze the expression of DNA damage repair related genes form TCGA and GEO databases and establish a clinical prognosis prediction model in lung adenocarcinoma. Methods The RNA sequencing and clinical information data of lung adenocarcinoma were downloaded from the TCGA database, and differential analysis of DNA damage repair genes was performed between cancer and normal tissues. Cox proportional risk model and Lasso regression were used to construct the prediction model of DNA repair related genes, and the external model was verified by GSE30219. Metascape and GSEA were used to analyze the relevant mechanisms. Results Total of 74 DNA damage repair related genes were screened out from RNA sequencing data of 515 cases of lung adenocarcinoma and 59 cases of normal lung tissues. Based on Cox and Lasso regression analysis, a risk prediction model composing of PLK1, NEIL3 and EXO1 was constructed, and the risk scoring formula was riskscore = PLK1*0.011259 + NEIL3*0.022537 + EXO1*0.015379. In the TCGA dataset and external validation set of GSE30219, the overall survival of the high-risk group was significantly lower than that of the low-risk group (P < 0.01). The results of mechanism analysis showed that the poor prognosis of high risk group patients was related to mTOR, Myc, G2M and E2F pathways. Conclusion The risk model composed of PLK1, NEIL3 and EXO1 is established in this study, which can accurately predict the prognosis of patients with lung adenocarcinoma.

Background: Mesothelioma is one of the most malignant tumors, which makes the identification of mesothelioma biomarkers extremely important. To investigate the prognostic value of enhancer homolog 2 (EZH2) mRNA expression in mesothelioma patients and its immune infiltration analysis. Methods: Gene expression and clinical information, enrichment analysis, and immune infiltration analysis obtained based on the Cancer Genome Atlas (TCGA) were performed, and additional bioinformatics analysis was performed. Clinical information and gene expression were obtained from 86 patients with mesothelioma based on the Cancer Genome Atlas TCGA database. Survival analysis, GSEA enrichment analysis, and immune infiltration analysis of EZH2 expression were performed by using R (version 3.6.3) (statistical analysis and visualization). Using the TIMER database (Fig. https://cistrome.shinyapps.io/timer/ ), the correlation between EZH2 expression and immune cell infiltration in mesothelioma was analyzed. Results: We collated the data obtained from the TCGA database and performed univariate and multivariate analysis of general data including age, gender, stage, pathological type, and whether they had received radiotherapy, and the results showed that high expression of EZH2 was associated with poor prognosis in mesothelioma patients. The prognosis was worse in the High group (HR=2.75, 95% CI: 1.68-4.52, P＜0.010). Moreover, ROC curves showed that EZH2 expression predicted 1-year survival with an AUC of 0.740, 2-year survival with an AUC of 0.756, and 3-year survival with an AUC of 0.692, suggesting that EZH2 expression has a good predictive effect on prognosis. KEGG pathway analysis showed that there were five pathways with the strongest positive correlation with EZH2 expression: Cell cycle, DNA replication, Cell adhesion molecules cams, Primary immuno deficiency, Tsate transduction, and five pathways with the strongest negative correlation with EZH2 expression: Glycolysis gluconeogenesis , Drug metabolism, cytochrome P450, retinol metabolism, fatty acid metabolism ribosom. We analyzed the correlation between EZH2 expression and the level of immune infiltration in mesothelioma tissues. The results indicate that EZH2 expression plays an important role in immune infiltration. At high EZH2 expression, the number of NK cells, Mast cells and Th17 cells was reduced. Mesothelioma patients with high EZH2 expression differ from mesothelioma patients with low EZH2 expression in their tumor immune microenvironment. Conclusion: EZH2, as a new prognostic biomarker for mesothelioma, is helpful to elucidate how changes in the immune environment promote the development of mesothelioma. Further analysis, EZH2 may be used as a biological test to predict the prognosis of mesothelioma.

Mesothelioma lies one of the most malignant tumors, in which the identification of the corresponding biomarkers is extremely critical. This study aims to investigate the prognostic value of enhancer homolog 2 (EZH2) mRNA expression in mesothelioma patients accompanied with its immune infiltration analysis. Gene expression, clinical information and enrichment analysis were obtained based on the Cancer Genome Atlas (TCGA), the immune infiltration analysis and bioinformatics analysis were performed. Clinical information and gene expression were obtained from 86 patients with mesothelioma based on TCGA database. Survival analysis, GSEA enrichment analysis, and immune infiltration analysis of EZH2 expression were carried out using R (version 3.6.3) (statistical analysis and visualization). The correlation of EZH2 expression with immune cell infiltration in mesothelioma was analyzed according to the TIMER database (Fig. https://cistrome.shinyapps.io/timer/). A univariate and multivariate analysis of general data obtained from the TCGA database was performed, involving age, gender, stage, pathological type, and whether they had received radiotherapy, the results indicated the association of high expression of EZH2 with poor prognosis in mesothelioma patients, with the worse prognosis in the High group (HR = 2.75, 95% CI 1.68–4.52, P < 0.010). Moreover, ROC curves showed that EZH2 expression predicted 1-year survival with an AUC of 0.740, 2-year survival with an AUC of 0.756, and 3-year survival with an AUC of 0.692, suggesting a robust predictive effect of EZH2 expression on prognosis. KEGG pathway analysis indicated five pathways showing the strongest positive correlation with EZH2 expression: cell cycle, DNA replication, Cell adhesion molecules cams, Primary immuno deficiency, Tsate transduction, and five pathways showing the strongest negative correlation with EZH2 expression: Glycolysis gluconeogenesis, Drug metabolism, cytochrome P450, retinol metabolism, fatty acid metabolism ribosome. We investigated the correlation between EZH2 expression and the level of immune infiltration in mesothelioma tissues. The results indicated that EZH2 expression played a critical role in immune infiltration, of which the high expression was correlated with the reduced number of NK cells, Mast cells, and Th17 cells. Moreover, mesothelioma patients with high EZH2 expression differ from those with low EZH2 expression in their tumor immune microenvironment. EZH2, as a new prognostic biomarker for mesothelioma, contributes to elucidating how changes in the immune environment promote the development of mesothelioma. Further analysis, EZH2 may serve as a biological test to predict the prognosis of mesothelioma.