Definition of predictive and prognostic immune biomarkers for salivary gland cancer from the intratumoural and systemic immune status: detailed protocol of the prospective, observatory ImmoGlandula study.

introductionSalivary gland carcinomas (SGC) are rare tumours. The term SGC is not more than an umbrella for a variety of histogenetically, morphologically and biologically distinct entities. Accordingly, SGCs have not been sufficiently investigated to date. Their rarity makes it difficult to reach high patient numbers for individual entities in clinical studies, leading to pooling patients with different histological subtypes to attain sufficient participants. The different histological subtypes of SGC differ significantly in their clinicopathological features, such as their grading, their occurrence and their outcome. SGCs are usually stratified into low-grade, intermediate-grade or high-grade tumours. In most kinds of SGC, specific targetable molecular markers are lacking. The inclusion of immunotherapy (IT), however, might improve the outcome of patients suffering from high-grade SGCs. In order to integrate IT as a therapeutic option for SGC and to facilitate therapeutic decisions based on tumour (immune) biology, predictive and prognostic immunological biomarkers are indispensable. METHODS AND ANALYSIS: In this prospective study, 500 patients will be enrolled, who are distributed in three arms. The observational cohort includes patients with malignant salivary gland tumours, whereas patients with benign tumours of a salivary gland are grouped in the control group 1. In the control cohort, 2 patients do not have a salivary gland tumour but have a planned functional surgery of the nose or ear or a maxillofacial surgery. The local immune status from the tumour tissue and the microbiome will be sampled before treatment. In addition, the systemic immune status from peripheral blood will be analysed before and after surgery and after the adjuvant and definitive chemoradiotherapy, if applicable. Clinical baseline characteristics and outcome parameters will additionally be collected. Data mining and modelling approaches will finally be applied to identify interactions of local and systemic immune parameters and to define predictive and prognostic immune signatures based on the evaluated immune markers. ETHICS AND DISSEMINATION: Approval from the institutional review board of the Friedrich-Alexander-Universität Erlangen-Nürnberg was granted in September 2023 (application number 23-292-B). The results will be disseminated to the scientific audience and the general public via presentations at conferences and publication in peer-reviewed journals. TRIAL REGISTRATION NUMBER: NCT06047236.