176 Spatial and seromic profiling of tumor infiltrating B-cell subtypes and autoantibody production in oral cancers
Bibliographic record
Abstract
Background Immune Checkpoint Inhibitors (ICIs) are approved for the treatment of recurrent/metastatic head and neck squamous cell carcinoma (HNSCC) showing long-term clinical benefit in a small proportion of patients. Excitingly, ICI are now moving to first line therapy. To predict response and improve efficacy of ICIs, detailed insights into the HNSCC tumor immune microenvironment (TiME) is essential. Although cytotoxic CD8 T-cells are considered to be the effectors of immunotherapy approaches, a critical role of tumor-infiltrating B-cells (TIL-B) is gaining attention. Previous research in our group showed that high numbers of TIL-B were associated with improved patient survival in oral HNSCC (OSCC), independent of CD8 T-cell infiltration. 1 A recent meta-analysis identified TIL-B as key prognostic marker in HNSCC outcome and ICI efficacy, outperforming established biomarkers like tumor mutational burden and PD-L1 combined positivity score.2 However, TIL-B phenotypes and their function within the TiME remain unclear. The aim of this study was to characterize B-cell subsets and antibody production spatially within OSCC and to identify OSCC-specific antibody responses in patient plasma samples.Methods Seven- and nine marker panels were designed to perform multiplexed fluorescent immunohistochemistry (mfIHC) on a cohort of OSCC FFPE samples (n=120) to spatially characterize TIL-B phenotypes and IgG/IgA production. To investigate autoantibody production and identify OSCC-specific autoantibody targets, we screened plasma samples of 50 OSCC patients and 25 healthy controls on the HuProt high-density protein array platform.Results Our spatial analyses revealed increased infiltration of naïve and memory B cells, plasmablasts and plasma cells in TIL-B high OSCC. In tumors enriched for plasmablasts, heterogeneous expression of IgG and IgA was observed. Plasmablasts were mostly present at the invasive tumor front, sometimes near tertiary lymphoid structures, but did not infiltrate the tumor fields. Seromic analysis revealed the presence of autoantibodies against tumor-associated antigens such as p53 and the MAGEA cancer/testis antigens, among others. Additionally, we observed an enrichment of autoantibodies directed against squamous cell-specific proteins, indicative of a humoral response in the TiME of OSCC. Top autoantibody hits not previously linked to OSCC, were validated at the protein level in patient tumor tissue and HNSCC-cell lines.Conclusions We identified a subset of OSCC tumors enriched in plasmablast populations, and identified squamous cell-associated autoantibodies. Our data support the apparent important role of B-cells in the TiME of HNSCC. These TIL-B populations and associated autoantibody profiles could serve as biomarkers of immunotherapy response and reveal novel targets for immunotherapy.Ethics Approval This study was conducted in agreement with the Declaration of Helsinki and the medical ethical guidelines in the Code of Conduct for Proper Secondary Use of Human Tissue of the Dutch Federation of Biomedical Scientific Societies. For plasma sample collection written informed consent was obtained. The Institutional Review Board of VUmc approved the use of the material under protocols 2008.071 (A2016.035) and 2021-0511.References Nauta IH, Nijenhuis DNLM, Ganzevles SH, Raaff PI, Kloosterman J, Bloemena E, Brakenhoff RH, Leemans CR, van de Ven R. Richness for tumor-infiltrating B-Cells in the oral cancer tumor microenvironment is a prognostic factor in early-stage disease and improves outcome in advanced-stage disease. Cancers. 2025;17:113 (p1–19).Chang TG, Spathis A, Schäffer AA, Gavrielatou N, Kuo F, Jia D, Mukherjee S, Sievers C, Economopoulou P, Anastasiou M, Moutafi M, Pal LR, Vos J, Lee AS, Lam S, Zhao K, Jiang P, Allen CT, Foukas P, Gomatou G, Altan-Bonnet G, Morris LTG, Psyrri A, Ruppin E. Tumor and blood B-cell abundance ourperforms established immune checkpoint response predisction signatures in head and neck cancer. Ann Oncol. 2024;36:309–320.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".