Immunotherapy Response and Survival Outcome by Immunophenotypic Signature in Non–Small Cell Lung Cancer

PURPOSE: Current predictive biomarkers for immune checkpoint inhibitor (ICI)-based therapy in patients with lung adenocarcinoma (LUAD) or lung squamous cell carcinoma (LUSC), such as PD-L1 protein expression or tumor mutation burden, are still suboptimal. We aim to explore immunophenotypic factors as potential biomarkers in this patient population. METHODS: Clinical, genomic, and transcriptomic data from five patient cohorts, consisting of three publicly available data and two retrospective cohorts, were included. Immune tumor microenvironment (TME) subtype and tertiary lymphoid structure (TLS) signature were evaluated using RNA expression data, and deconvolutional cellular decomposition of tumor samples was performed using the Kassandra algorithm. Survival analysis was performed using a log-rank test and multivariate Cox regression. All statistical analyses were performed using Python version 3.10. RESULTS: mutations did not affect the response rates but were associated with poorer OS and PFS. CONCLUSION: Dynamic and active immune recruitment, indicated by immune-hot TME and high TLS score, was predictive of ICI benefit in patients with LUAD. Further prospective studies are warranted to expand to other treatment combinations with PD-(L)1 inhibitors.