Abstract
Background: Immunotherapy has improved the outcomes for some patients with head and neck squamous-cell carcinoma (HNSCC). However, the low and variable response rates observed highlight the need for robust response biomarkers to select patients for treatment. Patients and methods: We assembled and analyzed a large HNSCC dataset, encompassing 11 clinical cohorts including 1232 patient samples, spanning a variety of disease subtypes and immune checkpoint blockade (ICB) treatment types, tissue sources, data modalities, and timing of measurements. We conducted a comprehensive evaluation of the predictive power of various cell types, traditional biomarkers, and emerging predictors in both blood and tumor tissues of HNSCC patients. Results: Tumor B-cell infiltration emerged as a strong and robust predictor of both patient survival and ICB response. It outperformed all other established biomarkers of response to ICB, including the tertiary lymphoid structure signature and numerous T-cell-based signatures. B-cell infiltration was associated with a ‘hot’ antitumor microenvironment that promotes tumor eradication. Furthermore, B-cell levels in peripheral blood mononuclear cells (PBMCs) correlated strongly with tumor B-cell levels and demonstrated high predictive value for ICB response, with high odds ratios (≥7.8) in two independent clinical cohorts. Conclusion: B-cell abundance, whether assessed in PBMCs or tumor tissues, is one of the strongest predictors of ICB response in HNSCC. For translation to patient care, measuring B-cell abundance in PBMCs via cytometry offers a practical and accessible tool for clinical decision making.
Original language | English |
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Pages (from-to) | 309-320 |
Number of pages | 12 |
Journal | Annals of Oncology |
Volume | 36 |
Issue number | 3 |
Early online date | 17 Nov 2024 |
DOIs | |
State | Published - Mar 2025 |
Externally published | Yes |
Bibliographical note
Publisher Copyright:© 2024
Keywords
- B cells
- head and neck cancer
- immunotherapy
- liquid biopsy
- treatment response biomarker
- tumor microenvironment