Lung cancer is the leading cause of cancer-related death worldwide and has a high incidence rate. N-Acetyltransferase 2 (NAT2) is a polymorphic xenobiotic enzyme, which can catalyze N-acetylation and O-acetylation of various carcinogens such as aromatic, heterocyclic amines and hydrazines. At present, many studies have explored the effects of NAT2 polymorphism on lung cancer, but we found inconsistent results. We researched 18 published studies, involving 4,016 patients and 5,469 controls, to more accurately assess the effects of NAT2 polymorphism on lung cancer risk and to investigate whether smoking is associated. We used STATA software to analyze the extracted data and used STATA for subgroup analysis, sensitivity analysis, and to perform publication bias tests. To determine the correlation, we used the crude odds ratio (ORs) with 95% confidence interval (CIs). Our study was prospectively registered in PROSPERO (CRD42020159737). The odds ratio was 1.53 (95% CI: 1.21–1.95, I² = 45.2%, P=0.104) for the NAT2 slow + intermediate phenotype versus rapid phenotype. The results suggested that people with NAT2 non-rapid (slow + intermediate) phenotype have a significantly increased risk of lung cancer. In addition, NAT2 rapid phenotype was significantly associated with reduced risk of lung cancer, compared with slow phenotype or intermediate phenotype (slow phenotype vs. rapid phenotype: OR: 1.61, 95% CI: 1.07–2.42, I²= 50%, P= 0.075; intermediate phenotype vs. rapid phenotype: OR: 1.47, 95% CI: 1.15–1.88, I²= 40.3%, P= 0.137).

Purpose: Non-small cell lung cancer (NSCLC) is the leading cause of cancer-related deaths worldwide. The mechanisms underlying NSCLC initiation and progression require further investigation. The purpose of this study was to investigate the role of ADP ribosylation factor-like GTPase 14 (ARL14) related to the progression of NSCLC. Patients and Methods: We analyzed the correlation between clinical characteristics and ARL14 expression using data from The Cancer Genome Atlas (TCGA). Kaplan–Meier analysis was conducted to evaluate the prognostic value of ARL14 in NSCLC. Functions of ARL14 were identified by enrichment analysis. The relationship between ARL14 expression and immune cell infiltration was also studied. Furthermore, ARL14 expression was examined using immunohistochemistry, and its clinical significance was analyzed in 120 patients with NSCLC. Results: Our study revealed that the expression level of ARL14 in patients with NSCLC was higher than that in normal tissues. Using TCGA data, higher ARL14 expression in lung adenocarcinoma was associated with residual tumor (P = 0.017), while it was associated with age (P = 0.003) and N stage (P = 0.009) in lung squamous cell carcinoma. Similar results were obtained from 120 patients with NSCLC. High ARL14 expression was associated with poor overall survival and progression-free survival in NSCLC. Multivariate analysis revealed that ARL14 was an independent risk factor for patients with NSCLC. Functional enrichment analysis indicated that ARL14 was related to the occurrence and development of tumors. Conclusion: Increased ARL14 expression was considerably correlated with poor survival in NSCLC, and it might be a promising prognostic biomarker for NSCLC.

Rationale: Idiopathic pulmonary fibrosis (IPF) is one of the most aggressive forms of idiopathic interstitial pneumonia. Some miRNAs may be associated with IPF and may affect the occurrence and development of IPF in various pathways. Many miRNAs and genes that may be involved in the development of IPF have been discovered using chip and high throughput technologies.

Background: Nonsmall cell lung cancer (NSCLC) ranks first among global cancer-related deaths. Despite the emergence of various immunological and targeted therapies, immune tolerance remains a barrier to treatment. Methods: It has been found that this obstacle can be overcome by targeting autophagy-related genes (ATGs). ATGs were screened by coexpression analysis and the genes related to the prognosis of lung cancer were screened using Kaplan–Meier (K–M) survival analysis, univariate Cox regression and multivariate Cox regression. The prognostic risk model of ATGs was constructed and verified using K–M survival analysis and receiver operating characteristic (ROC) curve analysis. Results: The prognostic risk model of ATGs was constructed. Gene set enrichment analysis (GSEA) showed that the function and pathway of ATG enrichment were closely related to immune cell function. CIBERSORT, LM22 matrix and Pearson correlation analysis showed that risk signals were significantly correlated with immune cell infiltration and immune checkpoint genes. Conclusions: We identified and independently verified the ATG (AL691432.2, MMP2-AS1, AC124067.2, CRNDE, ABALON, AL161431.1, NKILA) in NSCLC patients and found that immune regulation in the tumor microenvironment is closely related to this gene.