Abstract
Findings on mutations, associated with lung cancer, have led to advancements in mutation-based precision medicine. This study aimed to comprehensively and synthetically analyze mutations in lung cancer, based on the next generation sequencing data of surgically removed lung tumors, and identify the mutation-related factors that can affect clinical outcomes. Targeted sequencing was performed on formalin-fixed paraffin-embedded surgical specimens obtained from 172 patients with lung cancer who underwent surgery in our hospital. The clinical and genomic databases of the hospital were combined to determine correlations between clinical factors and mutation profiles in lung cancer. Multivariate analyses of mutation-related factors that may affect the prognosis were also performed. Based on histology, TP53 was the driver gene in 70.0% of the cases of squamous cell carcinoma. In adenocarcinoma cases, driver mutations were detected in TP53 (26.0%), KRAS (25.0%), and epidermal growth factor receptor (EGFR) (23.1%). According to multivariate analysis, the number of pathogenic mutations (≥3), presence of a TP53 mutation, and TP53 allele fraction >60 were poor prognostic mutational factors. The TP53 allele fraction tended to be high in caudally and dorsally located tumors. Moreover, TP53-mutated lung cancers located in segments 9 and 10 were associated with significantly poorer prognosis than those located in segments 1-8. This study has identified mutation-related factors that affect the postoperative prognosis of lung cancer. To our knowledge, this is the first study to demonstrate that the TP53 mutation profile varies with the site of lung tumor, and that postoperative prognosis varies accordingly.