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B cell signatures and tertiary lymphoid structures contribute to outcome in head and neck squamous cell carcinoma.

ABSTRACT: Current immunotherapy paradigms aim to reinvigorate CD8⁺ T cells, but the contribution of humoral immunity to antitumor immunity remains understudied. Here, we demonstrate that in head and neck squamous cell carcinoma (HNSCC) caused by human papillomavirus infection (HPV⁺), patients have transcriptional signatures of germinal center (GC) tumor infiltrating B cells (TIL-Bs) and spatial organization of immune cells consistent with tertiary lymphoid structures (TLS) with GCs, both of which correlate with favorable outcome. GC TIL-Bs in HPV⁺ HNSCC are characterized by distinct waves of gene expression consistent with dark zone, light zone and a transitional state of GC B cells. Semaphorin 4a expression is enhanced on GC TIL-Bs present in TLS of HPV⁺ HNSCC and during the differentiation of TIL-Bs. Our study suggests that therapeutics to enhance TIL-B responses in HNSCC should be prioritized in future studies to determine if they can complement current T cell mediated immunotherapies.

SUBMITTER: Ruffin AT

PROVIDER: S-EPMC8184766 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:OBJECTIVES:Head and neck squamous cell carcinoma (HNSCC) shows a remarkable heterogeneity between tumors, which may be captured by a variety of quantitative features extracted from diagnostic images, termed radiomics. The aim of this study was to develop and validate MRI-based radiomic prognostic models in oral and oropharyngeal cancer. MATERIALS AND METHODS:Native T1-weighted images of four independent, retrospective (2005-2013), patient cohorts (n = 102, n = 76, n = 89, and n = 56) were used to delineate primary tumors, and to extract 545 quantitative features from. Subsequently, redundancy filtering and factor analysis were performed to handle collinearity in the data. Next, radiomic prognostic models were trained and validated to predict overall survival (OS) and relapse-free survival (RFS). Radiomic features were compared to and combined with prognostic models based on standard clinical parameters. Performance was assessed by integrated area under the curve (iAUC). RESULTS:In oral cancer, the radiomic model showed an iAUC of 0.69 (OS) and 0.70 (RFS) in the validation cohort, whereas the iAUC in the oropharyngeal cancer validation cohort was 0.71 (OS) and 0.74 (RFS). By integration of radiomic and clinical variables, the most accurate models were defined (iAUC oral cavity, 0.72 (OS) and 0.74 (RFS); iAUC oropharynx, 0.81 (OS) and 0.78 (RFS)), and these combined models outperformed prognostic models based on standard clinical variables only (p < 0.001). CONCLUSIONS:MRI radiomics is feasible in HNSCC despite the known variability in MRI vendors and acquisition protocols, and radiomic features added information to prognostic models based on clinical parameters. KEY POINTS:• MRI radiomics can predict overall survival and relapse-free survival in oral and HPV-negative oropharyngeal cancer. • MRI radiomics provides additional prognostic information to known clinical variables, with the best performance of the combined models. • Variation in MRI vendors and acquisition protocols did not influence performance of radiomic prognostic models.

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B cell signatures and tertiary lymphoid structures contribute to outcome in head and neck squamous cell carcinoma.

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