Real world genomic profiling in non-small cell lung cancer reveals regional variations with clinical implications
Abstract
Routine targeted genomic profiling in non-small cell lung cancer (NSCLC) is primarily used to identify actionable alterations but may provide more information for clinical decision making. In this study routine genomic profiling data were used to examine the mutational landscape of lung cancer and its relationship to patient characteristics. We analyzed Archer VariantPlex 67-gene sequencing data from 528 patients diagnosed with lung cancer in the North Swedish Health Care Region between 2011 and 2021 and linked the genomic results to registry-derived clinical and demographic data. Mutation frequencies, positional architectures, subgroup enrichments, and survival associations were compared within the regional cohort and against an external reference cohort assembled from cBioPortal. After quality filtering, 1,415 somatic variants across 60 genes were identified, with a mean of 2.68 mutations per tumor, indicating substantial heterogeneity in mutational profiles. TP53 and KRAS formed a conserved mutational backbone across cohorts, whereas EGFR was less frequent and MET, APC, ATM, and CDKN2A were enriched in North Sweden relative to the external reference cohort. Major hotspot architectures were broadly preserved, although MET showed the clearest positional divergence. Mutation patterns varied by age, sex, smoking status, and disease stage. EGFR defined the most coherent clinical subtype, being enriched in females, never-smokers, younger patients, and earlier-stage disease, whereas KRAS, STK11, and TP53 were associated with smoking. EGFR was the strongest favorable prognostic marker, but stage strongly influenced the interpretation of many survival differences, indicating that gene-level prognostic signals are closely shaped by clinical context. Routine genomic profiling in NSCLC provides clinically relevant information beyond actionable driver detection when interpreted together with stage, smoking history, age, sex, and regional molecular context. These findings support a more context-aware interpretation of routine molecular diagnostics in thoracic oncology.