HERD: A multi-centre prospective cohort study to facilitate early detection of relapse in radically treated, high risk head and neck squamous cell carcinoma.

Abstract

TPS6128 Background: Head and Neck Squamous Cell Carcinoma (HNSCC) is the 7th most common cancer worldwide with more than 660,000 cases diagnosed annually. Many patients present with locally advanced disease, which despite aggressive multi-modality treatment remains associated with poor survival. Approximately 50% of patients relapse within 2 years, mostly occurring in the first year after treatment. Biomarkers predicting relapse are lacking and there remains no consensus on surveillance, with strategies differing according to local guidelines and recurrence too often detected when not amenable to salvage surgery (estimated to improve survival outcomes in relapsed HNSCC by up to 73%). We hypothesize that risk of relapse relies on a dynamic interplay between the immune profile, tumor microenvironment (TME; elucidated by radiology and tissue-based laboratory imaging), genomic background and clinicopathological characteristics. Our primary objectives are to develop and validate a multi-analyte based risk prediction tool and risk-stratified follow up strategy to enhance detection of early relapse and improve survival. Methods: This multi-center study is prospectively collectingsamples across multiple platforms including imaging, blood, saliva, stool, urine, and tissue from patients with newly diagnosed high risk locally advanced HPV-negative HNSCC planned for radical treatment (either surgery or (chemo)radiotherapy). We aim to recruit 200 patients in 2 stages, including discovery and validation cohorts. Three mechanistic (hypothesis-driven) meta-covariates and five working platform meta-covariates will be analysed to test recurrence prediction. Each meta-covariate represents an integrated risk score from covariate subsets. The 3 hypotheses are H1) combining magnetic resonance parameters of hypoxia and stromal composition with TME changes; H2) capturing the interactions between genomic mutations, immune cells and exosomes within the TME H3) understanding the relationship between micro-organisms and TME. The technical platforms include exosomal analyses, multi-parametric MRI including novel elastography (MRE) and quantitative magnetic susceptibility mapping (QSM) techniques, comprehensive circulating tumour and cell-free DNA analyses to aid detection of minimally residual disease, tissue immune profiling, somatic mutation testing and microbiome analysis. Regression Analysis will be performed by machine-learning with advanced mathematical and Bayesian statistical modelling. Accrual began in October 2023. Clinical trial information: NCT05097625 .