Ontology highlight
ABSTRACT:
SUBMITTER: Alcala N
PROVIDER: S-EPMC6702229 | biostudies-literature | 2019 Aug
REPOSITORIES: biostudies-literature
Alcala N N Leblay N N Gabriel A A G AAG Gabriel A A G AAG Mangiante L L Hervas D D Giffon T T Sertier A S AS Ferrari A A Derks J J Ghantous A A Delhomme T M TM Chabrier A A Cuenin C C Abedi-Ardekani B B Boland A A Olaso R R Meyer V V Altmuller J J Le Calvez-Kelm F F Durand G G Voegele C C Boyault S S Moonen L L Lemaitre N N Lorimier P P Toffart A C AC Soltermann A A Clement J H JH Saenger J J Field J K JK Brevet M M Blanc-Fournier C C Galateau-Salle F F Le Stang N N Russell P A PA Wright G G Sozzi G G Pastorino U U Lacomme S S Vignaud J M JM Hofman V V Hofman P P Brustugun O T OT Lund-Iversen M M Thomas de Montpreville V V Muscarella L A LA Graziano P P Popper H H Stojsic J J Deleuze J F JF Herceg Z Z Viari A A Nuernberg P P Pelosi G G Dingemans A M C AMC Milione M M Roz L L Brcic L L Volante M M Papotti M G MG Caux C C Sandoval J J Hernandez-Vargas H H Brambilla E E Speel E J M EJM Girard N N Lantuejoul S S McKay J D JD Foll M M Fernandez-Cuesta L L
Nature communications 20190820 1
The worldwide incidence of pulmonary carcinoids is increasing, but little is known about their molecular characteristics. Through machine learning and multi-omics factor analysis, we compare and contrast the genomic profiles of 116 pulmonary carcinoids (including 35 atypical), 75 large-cell neuroendocrine carcinomas (LCNEC), and 66 small-cell lung cancers. Here we report that the integrative analyses on 257 lung neuroendocrine neoplasms stratify atypical carcinoids into two prognostic groups wit ...[more]