Genetic Alterations in the SERPIN Gene Family as Predictors of Immune Checkpoint Therapy Efficacy in Melanoma and Non‐Small Cell Lung Cancer

Identifying reliable biomarkers for immune checkpoint therapy response remains a critical challenge in immuno‐oncology. While tumor mutation burden (TMB) effectively predicts treatment outcomes, its clinical implementation is hindered by cost and complexity. This work aimed to investigate the association between genetic alterations in the serine protease inhibitor (SERPIN) gene family and the efficacy of immune checkpoint inhibitor (ICI) therapy in patients with melanoma or non‐small cell lung cancer (NSCLC), and to evaluate the potential of these genetic alterations as a predictive biomarker compared with TMB.

This study analyzed mutation data and clinical information from five cohorts comprising 797 patients with melanoma and NSCLC who underwent whole‐exome sequencing before ICI treatment, supplemented by data from The Cancer Genome Atlas. We examined gene alterations across 36 protein‐coding SERPIN genes and analyzed their correlations with overall survival, clinical responses, TMB, neoantigen levels, and immune cell infiltration. Integration of data from The Cancer Genome Atlas with single‐cell transcriptomics using Scissor computational analysis was performed to characterize T‐cell populations associated with SERPIN gene alterations.

SERPIN gene alterations were associated with a longer overall survival and improved clinical responses to ICI therapy in both melanoma and NSCLC cohorts. These alterations correlated with higher TMB, increased neoantigen levels, and a more favorable tumor immune microenvironment characterized by enhanced presence of antitumor immune cells. Single‐cell analysis indicated that SERPIN gene alterations were linked to T‐cell populations with greater antitumor activity. The predictive performance of SERPIN alterations for overall survival was comparable to that of TMB.

Genetic alterations in the SERPIN gene family are associated with improved outcomes in ICI therapy and may serve as a cost‐effective predictive biomarker, offering a potential alternative to TMB for stratifying patients likely to benefit from immunotherapy.