Purpose. The purpose of this study was to evaluate the efficacy and safety of a nanodrug delivery regimen compared with conventional drug administration for the treatment of lung cancer. Materials and Methods. Studies were retrieved through PubMed, Web of Science, and ScienceDirect. Primary and secondary outcome measures, including overall response rate (ORR), progression-free survival (PFS), overall survival (OS), and adverse events, were extracted from the retrieved literature and systematically evaluated. Results. Six trials, including 4806 advanced non-small-cell lung cancer patients, were included in this study. Compared with conventional drug administration in the treatment of lung cancer, the nanodrug delivery regimen improved the ORR (risk ratio = 1.43, 95% confidence interval (CI) = 1.25–1.63, p ≤ 0.001 ), prolonged PFS (hazard ratio (HR) = 0.83, 95% CI = 0.76–0.92, p ≤ 0.001 ), and obtained superior OS (HR = 0.91, 95% CI = 0.83–0.99, p ≤ 0.001 ). Regarding safety, the incidence of neutropenia, alopecia, sensory neuropathy, myalgia, and arthralgia was lower in the nanoadministration group, but the risk of thrombocytopenia, anaemia, and nausea was increased. Conclusion. Nanodrug administration is safe and effective in patients with non-small-cell lung cancer to some extent.

Background: Non-small 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.