Molecular Heterogeneity Analysis and Prognostic Stratification of Driver-Gene mutated NSCLC Based on Concurrent Alteration Profiles

Comprehensive co-alteration profiling reveals distinct molecular subtypes and prognostic stratification in driver-gene-mutated non-small cell lung cancer (NSCLC). In this study, we systematically delineated the co-alteration profiles across eight different driver mutations and their subtypes using next-generation sequencing (NGS) data from 494 NSCLC patients. Unsupervised hierarchical cluster analysis based on high-frequency co-alterations was subsequently performed to identify molecular subtypes in surgical patients with classical EGFR mutations. The cluster analysis stratified patients into four distinct subgroups with significantly different relapse-free survival (RFS). Cluster 1, characterized by TP53 co-alterations, demonstrated the worst RFS in both the entire cohort and Stage Ⅰ subgroup, and emerged as an independent prognostic risk factor in multivariable analysis (Cluster 2 vs. 1: HR = 0.12, p < 0.001; Cluster 3 vs. 1: HR = 0.13, p < 0.001). The prognostic model effectively identified high-risk patients who might benefit from more intensive surveillance or adjuvant therapy. Our study established a co-alteration-based molecular subtyping as a powerful prognostic tool in EGFR-mutant NSCLC, providing critical insights for personalized treatment strategies.