Clinical Research Directory

Immune Biomarker Study for Salivary Gland Carcinoma

Sponsor: University of Erlangen-Nürnberg Medical School

Summary

Salivary gland carcinomas (SGC) are rare tumors. 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 challenging to recruit a high number of patients for individual entities in clinical studies, leading to the pooling of patients with different histological subtypes to achieve sufficient participants. The different histological subtypes of SGC exhibit significant differences in their clinicopathological features, including grading, occurrence, and outcome. SGCs usually are stratified into low-, intermediate-, or high-grade tumors. 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. To integrate IT as a therapeutic option for SGC and to facilitate informed therapeutic decisions based on tumor (immune) biology, predictive and prognostic immunological biomarkers are indispensable. In this prospective study, 500 patients will be enrolled, distributed across three arms. The observational cohort includes patients with malignant salivary gland tumors, whereas patients with benign tumors of a salivary gland are grouped in the control group 1. In the control cohort, two patients do not have a salivary gland tumor but have a planned functional surgery of the nose or ear or a maxillofacial surgery. The local immune status of the tumor tissue and the microbiome will be sampled before treatment. In addition, the systemic immune status from peripheral blood will be analyzed before and after surgery and after the adjuvant and definitive chemoradiotherapy (CRT), if applicable. Clinical baseline characteristics and outcome parameters will additionally be collected. Data mining and modeling approaches will be applied to identify interactions between local and systemic immune parameters and to define predictive and prognostic immune signatures based on the evaluated immune markers.

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