Development of a Multiomics Database for Personalized Prognostic Forecasting in Head and Neck Cancer: The Big Data to Decide EU Project

AutorCavalieri, Stefano; Cecco, L. de; Brakenhoff, R.H.; Serafini, M.S.; Canevari, S.; Rossi, S.; Lanfranco, D.; Hoebers, F.J.P.; Wesseling, F.W.R.; Keek, S.; Scheckenbach, K.; Mattavelli, D.; Hoffmann, T.; López Pérez, L.; Fico, G.; Bologna, M.; Nauta, I.; Leemans, C.R.; Trama, A.; Klausch, T.; Berkhof, J.H.; Tountopoulos, V.; Shefi, R.; Mainardi, L.; Mercalli, F.; Poli, T.; Licitra, L.; Wesarg, S.
ArtJournal Article
AbstraktBackground Despite advances in treatments, 30% to 50% of stage III-IV head and neck squamous cell carcinoma (HNSCC) patients relapse within 2 years after treatment. The Big Data to Decide (BD2Decide) project aimed to build a database for prognostic prediction modeling. Methods Stage III-IV HNSCC patients with locoregionally advanced HNSCC treated with curative intent (1537) were included. Whole transcriptomics and radiomics analyses were performed using pretreatment tumor samples and computed tomography/magnetic resonance imaging scans, respectively. Results The entire cohort was composed of 71% male (1097)and 29% female (440): oral cavity (429, 28%), oropharynx (624, 41%), larynx (314, 20%), and hypopharynx (170, 11%); median follow-up 50.5 months. Transcriptomics and imaging data were available for 1284 (83%) and 1239 (80%) cases, respectively; 1047 (68%) patients shared both. Conclusions This annotated database represents the HNSCC largest available repository and will enable to develop/validate a decision support system integrating multiscale data to explore through classical and machine learning models their prognostic role.