Newer-generation tyrosine kinase inhibitors (TKIs) have shown increasing efficacy in cancers driven by specific mutations, with epidermal growth factor receptor (EGFR) alterations remaining the most common actionable targets in non-small cell lung cancer (NSCLC). Treatment decisions are currently guided by tissue sampling and genetic testing, which are limited by procedural risks, patient tolerance, tumour heterogeneity and mutation evolution. Because co-mutations involving EGFR and other targetable genes can diminish treatment response, identifying exclusive EGFR mutation, defined by the absence of other actionable alterations, represents a clinically favourable scenario for first-line EGFR-TKI therapy. We developed a CT-based radiomics signature, EGFR-RPV, to predict exclusive EGFR mutational status using NSCLC patients (n = 304) from a multi-centre cohort with paired imaging and genomics data, and validated performance in an independent testing set (n = 51), alongside transcriptomics enrichment analysis. EGFR-RPV predicted exclusive EGFR mutation with accuracies of 0.77 (95% CI 0.66–0.88) and 0.71 (95% CI 0.54–0.89) in internal and external testing, respectively, and stratified patient prognosis (hazard ratio 2.15, 95% CI 1.50–3.08). FAM190A and CBMO1 were enriched in exclusive EGFR-positive cases, consistent with their roles in cell division regulation and vitamin A biosynthesis, respectively. EGFR-RPV thus offers a non-invasive approach to identify exclusive EGFR mutations, with a potential role in guiding first-line EGFR-TKI use.
Chen et al. (Fri,) studied this question.