Rôle de l'infiltrat immun dans la réponse au traitement dans les cancers des voies aéro-digestives supérieures

Résumé fourni par la source

Despite the availability of multiple therapeutic options, advanced-stage head and neck squamous cell carcinoma (HNSCC) are associated with poor prognosis and high recurrence rates. In this context, there is an increasing need to identify novel prognostic and predictive biomarkers to better categorize patients, particularly those who could benefit from immunotherapy. The tumor immune microenvironment (TIME) plays a key role in shaping treatment response and clinical outcomes. This objective of this work was to characterize the TIME in HNSCC, especially in recurrent cases, using a multimodal approach that combined histology, immunohistochemistry (IHC), digital image analysis, transcriptomics, and spatial proteomics.First, we developed a custom deep learning algorithm for the quantification of immune cells on IHC-stained slides. We then compared its performance with that of existing image analysis tools (QuPath and HALO®). The algorithm effectively segmented DAB signals regardless of staining type or cell type and yielded results correlated with manual counts and existing software. High densities of CD3+, CD8+, FOXP3+ T cells and CD20+ B cells were associated with improved prognosis, while CD163+ M2-like macrophages had no significant impact. However, the algorithm's performance on an external cohort was limited, highlighting the need for retraining and validation to ensure broader applicability.In the second part of the project, we analyzed a monocentric cohort of 84 patients with oropharyngeal squamous cell carcinoma who were treated with radiotherapy. Using IHC and targeted transcriptomics (nCounter® PanCancer Immune Profiling Panel), we examined immune infiltrates and gene expression profiles associated with recurrence and progression-free survival. Tumors from non-recurrent cases were enriched in CD3+, CD8+, FOXP3+ T cells, CD20+ B cells, CD57+ NK cells, and DC-LAMP+ dendritic cells. Recurrent tumors, on the other hand, showed higher levels of MPO+ neutrophils. A multivariate analysis confirmed that high densities of CD3+, CD8+, CD20+, and FOXP3+ cells were independently associated with better outcomes.Transcriptomic analysis revealed a 14-gene signature associated with recurrence and survival, which was validated on an independent cohort. Six of these genes (MAGEA1, MAGEA4, IL8, SPA17, TREM1, and CXCL5) were linked to poor prognosis. Some of these genes, notably IL8, TREM1, and CXCL5, are involved in neutrophil recruitment and activation. This finding supports a pro-tumoral role for neutrophils. The remaining eight genes (C7, C8G, IDO1, CCR6, CX3CR1, FLT3, PAX5, and IL21R) were associated with favorable outcomes, suggesting involvement in immune activation or tumor suppression.Finally, we initiated the PembroRad project, a multicenter study that integrates spatial proteomics (GeoMx® DSP), bulk RNA sequencing, and mutational analysis. This approach enables precise spatial mapping of immune markers within tumor and stromal compartments, providing more informative insights than bulk quantification alone. Spatial biomarkers, based on the localization or proximity of immune and tumor cells, may offer improved predictive power for treatment response, especially in the context of immunotherapy.Overall, this work underscores the complexity and clinical relevance of the TIME in HNSCC. The integrative strategies developed here -including digital pathology, transcriptomics, and artificial intelligence- contribute to identifying robust immune signatures and opening new avenues toward personalized immunotherapy.

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