Differences in the expression profiles of m6A-related genes and the prognostic role in immunotherapy for lung adenocarcinoma patients.

Background: Lung adenocarcinoma (LUAD) is the most common subtype of non-small cell lung cancer (NSCLC) and has high mortality rates. However, practical strategies for guiding clinical therapies for LUAD are still lacking. This study aimed to analyze the expression profiles and mutation features of 20 m6A (N6-methyladenosine) regulators in LUAD patients. It also systematically explored the biological roles of these m6A methylation regulators and their links to tumor immunity in LUAD, ultimately providing a theoretical basis for clinical treatment approaches. Methods: RNA sequencing data for 20 m6A methylation regulators and clinical information for LUAD patients were sourced from the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. The relationship between insulin-like growth factor 2 mRNA binding protein 1 (IGF2BP1) and immune cell infiltration in LUAD was analyzed using CIBERSORT. The "GSVA" R package (version 1.38.2) was employed to perform Gene Set Variation Analysis (GSVA). The protein-protein interaction (PPI) network of these m6A-related genes was built using the STRING database. The Tumor Immune Dysfunction and Exclusion (TIDE) algorithm was applied to predict clinical responses to immune checkpoint inhibitors, while the oncoPredict R package evaluated chemotherapeutic responses. We collected clinical specimens to validate Kaplan-Meier survival analysis and used immunohistochemistry to differentiate between high- and low-expression groups. Results: Sixteen m6A modification regulators showed significant abnormal expression in LUAD tissues. Univariate Cox and Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression analyses revealed that IGF2BP1 was the only independent predictor of LUAD after adjustment for common clinical markers. The mutation rates of m6A modification regulators in LUAD were below 10%. Further studies demonstrated that IGF2BP1 expression was strongly associated with immune infiltration, immune checkpoint expression, the effectiveness of immunotherapy in LUAD patients, and the incidence, progression, metastasis, and treatment resistance of lung adenocarcinoma. Additionally, patients with high IGF2BP1 expression had worse prognoses. We developed a nomogram combining IGF2BP1 expression with five other predictive risk factors. The ROC and calibration curves showed that the nomogram was well-calibrated and effectively distinguished between high- and low-expression LUAD patients. The results from the clinical validation cohort were consistent with these previous analyses. Conclusions: Our findings suggest that the m6A modification influences the tumor microenvironment and that IGF2BP1 acts as an independent predictor of immunotherapy response in LUAD. It may serve as an innovative biomarker for LUAD prognosis and tumor immunity status.