Improving stratification in HPV-negative head and neck squamous cell carcinoma (HNSCC) using emerging immune-based biomarkers

There is increasing awareness of the role of the tumor immune microenvironment (TIME) in the development and response to treatment in multiple types of cancer (1). In head and neck squamous cell carcinoma (HNSCC), the TIME is a heterogeneous mix of stromal cells (including endothelial cells and cancer-associated fibroblasts), immune cells and tumor cells (1). The fibroblasts and tumor cells recruit endothelial cells using growth factors, such as vascular endothelial growth factor (VEGF), epithelial growth factor (EGF), cytokines and chemokines, to stimulate neovascularisation leading to a supply of oxygen and nutrients to the tumor (2,3). This TIME in turn can lead to the support and survival of cancer stem cells (4). Head and neck tumors are highly infiltrated by immune cells, including tumor-infiltrating lymphocytes (TILs) and myeloid cells (macrophages, neutrophils, dendritic cells), although the composition varies according to anatomic subsite and etiologic agent [smoking, human papillomavirus (HPV)] (5). High levels of TILs in HNSCC have been shown to have better outcomes (6,7), with HPV-positive tumors exhibiting higher levels of TILs (8).

Tertiary lymphoid structures (TLS), which are lymphoid structures (comprised of CD20⁺ B cells surrounded by CD3⁺ T cells) that develop in ectopic non-lymphoid tissues that are subjected to chronic infections/inflammation and cancers, have also been shown to have beneficial effects in cancer outcomes and response to immunotherapy (9,10). There are several proposed mechanisms for these observations, including anti-tumor antibodies produced by intra-tumoral B-cells and B-cell-mediated antigen presentation that facilitates T-cell priming (11). Immune-based classifications, such as the Immunoscore in colorectal cancer, are increasingly used for prognostication and have also demonstrated superior classification and prognostication when compared to traditional staging systems (12). The potential importance of TLS and intra-tumoral B cells has been suggested by findings that B cell infiltration, even more than T cell infiltration, predicts HNSCC tumor response to immunotherapy (13).

Emerging evidence supports a causal role for TLS in augmenting anti-tumor immunity. Wang et al. showed that TLS in HNSCC facilitates recruitment and activation of CD8⁺ T cells through CXCL13- and CCL21-dependent pathways (14). This mechanism may have prognostic importance: Li et al. found that mature TLS in HNSCC is enriched with germinal center B-cells, stem-like CD8⁺ cells, and progenitor exhausted CD4⁺ follicular helper T-cells, conferring the most favorable survival outcomes (11).

To explore the prognostic aspects of TLS in greater detail, a recent study by Xu et al. sought to provide an immune-based classification for HPV-negative HNSCC using TLS and TIL levels (15).

Using transcriptomic data from The Cancer Genome Atlas (TCGA) and published datasets from Foy et al. and Wichmann et al. (16,17), the authors identified five immune phenotypes and demonstrated that the TLS-enriched subtype confers markedly superior survival and immunotherapy response among HPV-negative patients, but no significant differences in HPV-positive patients (15). This transcriptomics-based stratification framework serves a similar function to the Immunoscore, a measure of TILs using CD3⁺ and CD8⁺ immunohistochemical (IHC) staining, distinguishing biologically distinct subgroups that are not captured in traditional staging.

In this study, TLS positivity was superior to tumor-node-metastasis (TNM) staging in stratifying prognosis, but also extended to predicting response to immunotherapy. In their combined dataset of 137 immunotherapy-treated patients, TLS-positive tumors achieved an objective response rate of 42.9%, compared with roughly 10% in TLS-negative cases, a striking differential given that overall response rates to programmed cell death protein 1 (PD-1) inhibitors in HPV-negative HNSCC, often considered immunologically cold, are low (15,18).

From a translational standpoint, TLS stratification could reshape clinical practice and trial design by offering an additional biomarker for patients that are likely to derive the most benefit from checkpoint inhibition, much like programmed cell death ligand 1 (PD-L1) combined positive score (CPS) or tumor mutational burden (TMB). TLS quantification can also help guide intensity modulation: TLS-positive tumors could warrant immunotherapy-first approaches, while TLS-negative patients might benefit more from cytotoxic chemotherapy-based approaches—this question will need to be addressed in prospective clinical studies. Recent data have suggested that high expression of TLSs in resected tumor tissues was associated with a higher response to immunotherapy and better survival outcomes across different tumor types (19). However, in the neoadjuvant context, poor concordance between biopsy and surgical specimens in TLS assessment may limit the use of such an approach (20). For this reason, gene expression signatures may provide the most practical biopsy-based approach for TLS assessment, with several studies describing TLS gene signatures with strong predictive values for prognosis and immunotherapy response in HNSCC (21-23).

As with the Immunoscore, widespread adoption will depend on assay standardization. There is currently no consensus on TLS maturity and density, spatial localization (intra- versus peritumoral), or scoring thresholds (9). Inter-observer variability is untested, and validation across ethnically and geographically diverse populations is needed, especially as the cohort of the study by Xu et al. was drawn entirely from a Chinese institution (15).

Nevertheless, the data from the study by Xu et al. demonstrate that prognostication in HPV-negative head and neck SCC can be improved by the addition of immune-based stratification and help predict response to checkpoint inhibition (15). Future pathology reports may routinely incorporate immune-based predictors, such as the TLS status, akin to CPS score to inform adjuvant and immunotherapy decisions. Nevertheless, caution is warranted: TLS remains an evolving biomarker, and generalizability and inter-observer consistency are important to demonstrate. In the interest of developing pathology-based biomarkers suitable for widespread and reproducible implementation, the incremental predictive power added by TLS over simpler, correlated measures such as B-cell abundance should be investigated. Validation in multi-institutional, ethnically diverse, prospectively collected cohorts will be essential, as will demonstration of inter-laboratory concordance and analytical robustness.

Acknowledgments

None.

Footnote

Provenance and Peer Review: This article was commissioned by the editorial office, Translational Cancer Research. The article has undergone external peer review.

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Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1-2633/coif). The authors have no conflicts of interest to declare.

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