Abstract

This study investigates the molecular mechanism of FTO m6A demethylase in non-small cell lung cancer (NSCLC) and gefitinib resistance using GEO and TCGA databases. Differentially expressed genes (DEGs) were screened from RNA-seq data sets of serum exosomes of gefitinib-resistant NSCLC patients in the GEO database and the NSCLC data set in the GEPIA2 database. From this analysis, FTO m6A demethylase was found to be significantly upregulated in the serum exosomes of gefitinib-resistant NSCLC patients. To identify downstream genes affected by FTO m6A demethylase, weighted correlation network analysis and differential expression analysis were performed, resulting in the identification of three key downstream genes (FLRT3, PTGIS, and SIRPA). Using these genes, the authors constructed a prognostic risk assessment model. Patients with high-risk scores exhibited a significantly worse prognosis. The model could predict the prognosis of NSCLC with high accuracy measured by AUC values of 0.588, 0.608, and 0.603 at 1, 3, and 5 years respectively. Furthermore, m6A sites were found in FLRT3, PTGIS, and SIRPA genes, and FTO was significantly positively correlated with the expression of these downstream genes. Overall, FTO m6A demethylase promotes gefitinib resistance in NSCLC patients by upregulating downstream FLRT3, PTGIS, and SIRPA expression, with these three downstream genes serving as strong prognostic indicators.

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