Development of a multiomics database for personalized prognostic forecasting in head and neck cancer: The Big Data to Decide <scp>EU</scp> Project
Stefano Cavalieri, Loris De Cecco, Ruud H. Brakenhoff, Mara Serena Serafini, Silvana Canevari, Silvia Rossi, Davide Lanfranco, Frank Hoebers, Frederik Wesseling, Simon Keek, Kathrin Scheckenbach, Davide Mattavelli, Thomas K. Hoffmann, Laura Lopez-Perez, Giuseppe Fico, Marco Bologna, Irene H. Nauta, C. René Leemans, Annalisa Trama, Thomas Klausch, Johannes Berkhof, Vasilis Tountopoulos, Ron Shefi, Luca Mainardi, Franco Mercalli, Tito Poli, Lisa Licitra
Abstract
BACKGROUND: 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.