Relationship between postoperative gene mutation and prognosis in chinese patients with lung cancer: a long-term follow-up retrospective cohort study

Lung cancer is the malignant tumor with the highest morbidity and mortality worldwide, and radical surgery is the treatment of choice for early lung cancer, but postoperative recurrence remains a major challenge. The aim of this study was to systematically delineate the gene mutation profile in a Chinese lung cancer population through a large sample of real-world data and to assess the predictive value of critical gene mutations for postoperative DFS. We retrospectively enrolled 1674 patients with stage I-IIIA lung cancer who underwent curative surgical resection, and all patients underwent NGS testing. Clinicopathological data, treatment information, and DFS data were collected to draw gene mutation profiles in the overall population and its subgroups and Kaplan-Meier, Cox univariate/multivariate analysis, and co-mutation analysis were used to assess the correlation between gene mutations and DFS. A total of 144 relevant mutated genes were detected and gene mutations were mapped, with EGFR (61.2%) and TP53 (31.9%) having the highest mutation frequencies. Univariate analysis showed that DFS was significantly shorter in patients with TP53, KRAS, MET, ROS1, and CDKN2A mutations, and ERBB2 mutations were associated with longer DFS. Multivariate analysis confirmed TP53 mutation, ERBB2 mutation, T/N stage and pleural invasion as independent prognostic factors. Patients with TP53 and MET co-mutations had the poorest prognosis and significantly worse DFS than those with single or double wild-type mutations, and this result was consistent in the progressive subgroup. We confirmed that mutations in TP53, ERBB2 and other genes can be used as independent predictors of postoperative DFS in a large sample of Chinese lung cancer population, and co-mutations in TP53 and MET genes further amplify the risk of recurrence. The results provide a reliable molecular basis for postoperative risk stratification and individualized adjuvant therapy of lung cancer.