This study systematically evaluated the predictive power of various immune cell types and established biomarkers by integrating multi-omics data from 11 clinical cohorts comprising 1,232 patients with head and neck squamous cell carcinoma (HNSCC). It found that B cell abundance—whether in tumor tissue or peripheral blood—significantly predicts the efficacy of immune checkpoint inhibitor therapy and patient survival, outperforming existing biomarkers such as tumor mutational burden (TMB) and PD-L1 expression.
Literature Overview
This article, 'Tumor and Blood B Cell Abundance Outperforms Established Immune Checkpoint Blockade Response Prediction Signatures in Head and Neck Cancer,' published in Annals of Oncology: official journal of the European Society for Medical Oncology, reviews and summarizes the critical predictive role of B cells in immune responses to head and neck squamous cell carcinoma (HNSCC). The study integrates a large number of patient samples from multiple independent cohorts, covering different HPV statuses, treatment regimens, and tissue sources, and systematically evaluates the relationship between immune cell abundance in the tumor microenvironment and peripheral blood and the response to immune checkpoint blockade (ICB) therapy using multiple technologies, including transcriptomics, single-cell sequencing, and flow cytometry. The results show that B cell infiltration levels are not only significantly associated with overall survival (OS) and progression-free survival (PFS), but also outperform several existing biomarkers—including PD-L1 expression, tumor mutational burden (TMB), and T cell–related gene signatures—in predicting ICB treatment response. Moreover, a peripheral blood B cell proportion ≥5.5% serves as a non-invasive liquid biopsy indicator with high clinical translational potential. This study provides strong evidence to optimize immunotherapy selection strategies for HNSCC patients.Background Knowledge
Head and neck squamous cell carcinoma (HNSCC) is the sixth most common cancer worldwide. Although immune checkpoint inhibitors (e.g., anti–PD-1 antibodies) have been approved for use in recurrent or metastatic patients, overall response rates remain low and heterogeneous, highlighting the urgent need for more reliable biomarkers to guide treatment decisions. Currently approved biomarkers by the FDA include PD-L1 combined positive score (CPS) and tumor mutational burden (TMB), but multiple clinical studies have shown limited predictive performance in HNSCC. Over the past decade, numerous transcriptome-based immune signatures have been proposed—such as T cell–inflamed gene profile, IFN-γ signaling, and TIDE score—mainly focusing on the role of T cells. However, other immune cell types, including B cells, dendritic cells, and macrophages, have also been shown to participate in anti-tumor immune responses. In particular, B cells have recently been reported in melanoma and sarcoma to promote immunotherapy response through the formation of tertiary lymphoid structures (TLS). In HNSCC, however, the role of B cells remains controversial: some studies suggest that B cell infiltration within the tumor parenchyma correlates with prognosis, while others emphasize the importance of stromal B cells or TLS. Furthermore, whether B cells in peripheral blood can reflect the state of the tumor microenvironment and be used for response prediction has not been systematically assessed. Therefore, a comprehensive, multi-cohort integrated analysis of the predictive value of different immune cell types in HNSCC—especially the role of B cells—holds significant scientific and clinical translational potential. This study addresses this gap by revealing, through large-scale data integration, the prominent role of B cell abundance as a strong predictor of immunotherapy response in HNSCC.
Research Methods and Experiments
The study integrated 11 HNSCC clinical cohorts, totaling 1,232 patient samples, including public cohorts and two newly generated internal cohorts (Cohort10 and Cohort11). The cohorts spanned different HPV statuses, treatment regimens (e.g., anti–PD-1 monotherapy or combination with anti–CTLA-4), tissue sources (tumor and peripheral blood), and data types (bulk RNA-seq, scRNA-seq, flow cytometry, multiplex immunofluorescence imaging). B cell abundance in bulk RNA-seq data was estimated using the Kassandra deconvolution algorithm, calculated as the proportion of target cell types in total cells in scRNA-seq data, and directly measured in peripheral blood mononuclear cells (PBMCs) using flow cytometry. ICB treatment response was classified as responder or non-responder according to RECIST or pathological response criteria. Statistical methods—including Mann-Whitney U test, Cox regression models, ROC curves, and AUC analysis—were used to evaluate the predictive ability of B cell abundance for survival and treatment response, with comparisons to TMB, PD-L1, TLS features, and other T cell–related biomarkers. Additionally, the study analyzed the relationship between IGHM gene expression and treatment response and explored the association between B cell abundance and tumor microenvironment characteristics.Key Conclusions and Perspectives
Research Significance and Prospects
This study systematically reveals the central predictive value of B cells in HNSCC immunotherapy, challenging the traditional T cell–centric model of immunotherapy response and highlighting the potential of B cells as an independent and powerful biomarker. The results indicate that the role of B cells extends beyond TLS formation—overall infiltration levels alone can effectively reflect anti-tumor immune activity.
More importantly, B cell abundance in peripheral blood, as a non-invasive and easily accessible liquid biopsy marker, holds high clinical translational value. It can be detected via routine flow cytometry, providing a practical tool for clinical decision-making and helping to avoid unnecessary immunotherapy and associated toxicities in patients unlikely to respond.
Future studies should further explore the specific functions of B cell subsets (e.g., memory B cells, plasma cells), elucidating the mechanisms by which they promote anti-tumor immunity—such as through antibody-dependent cellular cytotoxicity (ADCC), antigen presentation, or immune complex–mediated complement activation. Additionally, the generalizability of the 5.5% threshold should be validated in larger, prospective, multicenter cohorts, and its potential application in other cancer types should be explored.
Conclusion
This study, through systematic analysis of 11 clinical cohorts involving 1,232 patients with head and neck squamous cell carcinoma, establishes B cell abundance as one of the strongest predictors of response to immune checkpoint inhibitors. Whether in tumor tissue or peripheral blood, B cell infiltration levels significantly outperform PD-L1, TMB, and multiple T cell–related gene signatures in predicting patient survival and treatment response. The study found that peripheral blood B cell levels are highly correlated with tumor B cell infiltration, and when the proportion of B cells in PBMCs exceeds 5.5%, the response rate to ICB therapy increases significantly, with odds ratios exceeding 7.8. This non-invasive biomarker has strong clinical application potential and can be rapidly assessed using routine flow cytometry, providing a practical tool for personalized immunotherapy decisions. Additionally, IGHM expression also demonstrates strong predictive power, underscoring the important role of humoral immunity in anti-tumor responses. This study not only deepens our understanding of the HNSCC immune microenvironment but also provides critical evidence for optimizing patient selection strategies and improving the precision of immunotherapy, potentially accelerating the clinical translation of B cell–related biomarkers.
