Abstract 6277: A time-series mouse model identifies an early post-treatment effective liquid biomarker of ICB response in human head and neck cancer

Abstract Background & Approach: Immune checkpoint blockade (ICB) therapy has shown promise for head and neck squamous cell carcinoma (HNSCC); however, response rates remain limited, with only a subset of patients exhibiting significant clinical benefits. Identifying non-invasive liquid biomarkers to predict ICB response is crucial for optimizing patient selection and treatment strategies. In this study, we generate and analyze time-series RNA and T-cell receptor (TCR) sequencing data from blood in a murine HNSCC model treated with anti-PD-1 therapy to identify potential liquid biomarkers predictive of ICB response Results: Our analysis reveals significant differences in the clonal expansion and temporal dynamics of effector T cells (Teff) and B cells between responders and non-responders, indicating distinct immune profiles associated with therapeutic outcomes. Notably, these immunological changes are most prominent at early post-treatment timepoints, suggesting that this period is optimal for assessing ICB efficacy and for the potential identification of predictive biomarkers. Importantly, the Teff and B cell transcriptomic gene signatures identified at these early post-treatment timepoints predict ICB treatment responses in HNSCC patient cohorts without the need for additional training, underscoring their potential clinical utility. Further time-series ligand-receptor interaction analyses uncover potential immune cell communication pathways that may mediate ICB outcomes, offering insights into mechanisms underlying ICB resistance. Conclusions: Our findings highlight the importance of early post-treatment timepoints for assessing ICB response and suggest blood-based Teff and B cell signatures as effective biomarkers for predicting ICB treatment outcomes in HNSCC patients. This study provides a potential framework for translating findings from murine models to human clinical practice, facilitating the development of personalized immunotherapeutic strategies. Citation Format: Binbin Wang, Robert Saddawi-konefka, Lauren M. Clubb, Shiqi Tang, Di Wu, Sumit Mukherjee, Sahil Sahni, Saugato Rahman Dhruba, Kun Wang, J. Silvio Gutkind, Eytan Ruppin. A time-series mouse model identifies an early post-treatment effective liquid biomarker of ICB response in human head and neck cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 6277.