The Head and Neck Tumor Biobank

Head and Neck Squamous Cell Carcinoma

head and neck, HNSCC, orophaynx, hypopharynx, larynx, nasopharynx, oral cavity, prospective study, predictive models for HNSCC, genomic analyses, outcome prediction

The purpose of the biobank is to enable future genomic based research on this Head and Neck Cancer patient population. The investigators will try to identify tumor factors that will predict cancer-related outcome in order to improve the outcome prediction after treatment in a patient-individualized manner.

This is a prospective, non-interventional longitudinal study in patients with HNSCC. Patients will have their normal routine workup including the standard panendoscopy, during which usually multiple biopsies for diagnostic histo-pathology are obtained. Part of one of these biopsies will be stored in the HN Tumor Biobank. There will be no change in the subsequent proposed treatment, which may consist of primary surgery (with or without postoperative (chemo-) radiation) or definitive (chemo-) radiation. The primary and general objective of this project is to develop, validate, and improve predictive models for different endpoints that are relevant for patients after curatively intended treatment of HNSCC. These endpoints include loco-regional tumour control and overall survival. Primary Objective: To build a biobank of tumor tissue from all HNSCC patients for future genomic analyses. Secondary Objective: To improve the outcome prediction, based on both clinical factors and tumour gene expression profiles. Hypothesis: Our general hypothesis is that a more accurate estimation of locoregional control and overall survival can be achieved when prognostic factors are taken into account different from than the currently used 'classical' prognostic factors, such as TNM-stage. The investigators hypothesize that the final outcome of this project will allow us to improve the performance of predictive models for HNSCC. The performance of our prediction models will be quantified by AUC for binary outcome measures and with the c-statistic for survival analysis. The ultimate objective will be to achieve an AUC of at least 0.90. Such a performance will allow us to build a Decision Support System based on these predictive models that provides information to physicians with regard to the probability of loco-regional failure and overall survival in individual patients. Study parameters/endpoints: Because no specific gene-signature has yet been defined that is applicable to a large population of HNSCC patients, no specific endpoint can be named. However, the main study endpoint will be the accuracy of a certain gene-signature that may contribute or rather improve the outcome prediction of patients. Outcome is defined as locoregional control and/or survival. The outcome of the patients is currently recorded in the electronic medical charts of azM and of Maastro Clinic and at the time of analysis, these clinical outcome data will be coupled blinded to the data generated from the tumor-biopsy analysis The goal is to achieve an AUC of at least 0.90. Such a performance will allow us to build a Decision Support System.

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Netherlands