Development of a multiomics database for personalized prognostic forecasting in head and neck cancer: The Big Data to Decide EU Project. Academic Article uri icon

Overview

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.

authors

  • Cavalieri, Stefano
  • De Cecco, Loris
  • Brakenhoff, Ruud H
  • Serafini, Mara Serena
  • Canevari, Silvana
  • Rossi, Silvia
  • Lanfranco, Davide
  • Hoebers, Frank J P
  • Wesseling, Frederik W R
  • Keek, Simon
  • Scheckenbach, Kathrin
  • Mattavelli, Davide
  • Hoffmann, Thomas
  • López Pérez, Laura
  • Fico, Giuseppe
  • Bologna, Marco
  • Nauta, Irene
  • Leemans, C René
  • Trama, Annalisa
  • Klausch, Thomas
  • Berkhof, Johannes Hans
  • Tountopoulos, Vasilis
  • Shefi, Ron
  • Mainardi, Luca
  • Mercalli, Franco
  • Poli, Tito
  • Licitra, Lisa

publication date

  • October 27, 2020

Research

keywords

  • Big Data
  • Head and Neck Neoplasms

Identity

PubMed Central ID

  • PMC7820974

Scopus Document Identifier

  • 85093969687

Digital Object Identifier (DOI)

  • 10.1002/hed.26515

PubMed ID

  • 33107152

Additional Document Info

volume

  • 43

issue

  • 2