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Objectives The aim of LungBEAM was to determine the value of a novel epidermal growth factor receptor (EGFR) mutation test in blood based on BEAMing technology to predict disease progression in advanced non‐small cell lung cancer (NSCLC) patients treated with first‐ or second‐generation EGFR‐tyrosine kinase inhibitors (EGFR‐TKIs). Another goal was to monitor the dynamics of EGFR mutations, as well as to track EGFR exon 20 p.T790M (p.T790M) resistance during treatment, as critical indicators of therapeutic efficacy and patient survival. Methods Stage IV NSCLC patients with locally confirmed EGFR‐TKI sensitizing mutations (ex19del and/or L858R) in biopsy tissue who were candidates to receive first‐ or second‐generation EGFR‐TKI as first‐line therapy were included. Plasma samples were obtained at baseline and every 4 weeks during treatment until a progression‐free survival (PFS) event or until study completion (72‐week follow‐up). The mutant allele fraction (MAF) was determined for each identified mutation using BEAMing. Results A total of 68 of the 110 (61.8%) patients experienced a PFS event. Twenty‐six patients (23.6%) presented with an emergent p.T790M mutation in plasma at some point during follow‐up, preceding radiologic progression with a median of 76 (interquartile ratio: 54–111) days. Disease progression correlated with the appearance of p.T790M in plasma with a hazard ratio (HR) of 1.94 (95% confidence interval [CI], 1.48–2.54; p, The manuscript is a multicenter, prospective study conducted in the real‐world setting. The study reveals that the detection and quantification (MAF slope) of EGFR mutations in ctDNA using the highly sensitive BEAMing method may assist in optimizing treatment decisions for advanced NSCLC patients.

We molecularly characterized tumors from non‐small cell lung cancer patients, focusing on long‐term responders to immune checkpoint inhibitors and showed that these patients present high tumor mutation burden and low somatic copy number alteration burden. PD‐L1 expression was also enriched in these patients. Finally, we validated our findings by reanalyzing two public datasets., Immunotherapy has transformed advanced non‐small cell lung cancer (NSCLC) treatment strategies and has led to unprecedented long‐lasting responses in some patients. However, the molecular determinants driving these long‐term responses remain elusive. To address this issue, we performed an integrative analysis of genomic and transcriptomic features of long‐term immune checkpoint inhibitors (ICIs)‐associated responders. We assembled a cohort of 47 patients with NSCLC receiving ICIs that was enriched in long‐term responders [>18 months of progression‐free survival (PFS)]. We performed whole‐exome sequencing from tumor samples, estimated the tumor mutational burden (TMB), and inferred the somatic copy number alterations (SCNAs). We also obtained gene transcription data for a subset of patients using Nanostring, which we used to assess the tumor immune infiltration status and PD‐L1 expression. Our results indicate that there is an association between TMB and benefit to ICIs, which is driven by those patients with long‐term response. Additionally, high SCNAs burden is associated with poor response and negatively correlates with the presence of several immune cell types (B cells, natural killers, regulatory T cells or effector CD8 T cells). Also, CD274 (PD‐L1) expression is increased in patients with benefit, mainly in those with long‐term response. In our cohort, combined assessment of TMB and SCNAs burden enabled identification of long‐term responders (considering PFS and overall survival). Notably, the association between TMB, SCNAs burden, and PD‐L1 expression with the outcomes of ICIs treatment was validated in two public datasets of ICI‐treated patients with NSCLC. Thus, our data indicate that TMB is associated with long‐term benefit following ICIs treatment in NSCLC and that TMB, SCNAs burden, and PD‐L1 are complementary determinants of response to ICIs.