Background Immune checkpoint inhibitors (ICIs) provide significant survival benefits in non-small cell lung cancer (NSCLC). Nevertheless, while some patients obtain a prolonged benefit, a non-negligible fraction of patients experiences an ultrarapid disease progression. Identifying specific molecular backgrounds predicting opposite outcomes is instrumental to optimize the use of these agents in clinical practice. Methods We carried out an observational study with prospective design envisioning targeted next-generation sequencing (NGS) with an approved assay in 55 patients with metastatic NSCLC (Rome cohort), of whom 35 were treated with ICIs. Data from three clinically comparable datasets were collected and combined into a metadataset containing 779 patients. The datasets were related to the Memorial Sloan Kettering Cancer Center (MSKCC) cohort (tissue-based NGS) and the randomized phase II and III POPLAR and OAK trials (blood-based NGS). Results In patients treated with ICIs in the Rome cohort, co-occurring mutations in NOTCH1-3 and homologous repair (HR) genes were associated with durable clinical benefit. Using the MSKCC/POPLAR/OAK metadaset, we confirmed the relationship between the NOTCH mut/HR mut signature and longer progression-free survival (PFS) in ICI-treated patients (multivariate Cox: HR 0.51, 95% CI 0.34 to 0.76, p=0.001). The NOTCH mut/HR mut genomic predictor was also associated with longer survival (log-rank p=0.008), despite patients whose tumors carried the NOTCH mut/HR mut signature had higher metastatic burden as compared with their negative counterpart. Finally, we observed that this genomic predictor was also associated with longer survival in patients with other tumor types treated with ICIs (n=1311, log-rank p=0.002). Conclusions Co-occurring mutations in the NOTCH and HR pathways are associated with increased efficacy of immunotherapy in advanced NSCLC. This genomic predictor deserves further investigation to fully assess its potential in informing therapeutic decisions.
- lung neoplasms
- tumor biomarkers