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DNA methylation-based classification of sinonasal tumors

Title: DNA methylation-based classification of sinonasal tumors
Authors: Jurmeister, Philipp; Glöß, Stefanie; Roller, Renée; Leitheiser, Maximilian; Schmid, Simone; Mochmann, Liliana H; Payá Capilla, Emma; Fritz, Rebecca; Dittmayer, Carsten; Friedrich, Corinna; Thieme, Anne; Keyl, Philipp; Jarosch, Armin; Schallenberg, Simon; Bläker, Hendrik; Hoffmann, Inga; Vollbrecht, Claudia; Lehmann, Annika; Hummel, Michael; Heim, Daniel; Haji, Mohamed; Harter, Patrick; Englert, Benjamin; Frank, Stephan; Hench, Jürgen; Paulus, Werner; Hasselblatt, Martin; Hartmann, Wolfgang; Dohmen, Hildegard; Keber, Ursula; Jank, Paul; Denkert, Carsten; Stadelmann, Christine; Bremmer, Felix; Richter, Annika; Wefers, Annika; Ribbat-Idel, Julika; Perner, Sven; Idel, Christian; Chiariotti, Lorenzo; Della Monica, Rosa; Marinelli, Alfredo; Schüller, Ulrich; Bockmayr, Michael; Liu, Jacklyn; Lund, Valerie J; Forster, Martin; Lechner, Matt; Lorenzo-Guerra, Sara L; Hermsen, Mario; Johann, Pascal D; Agaimy, Abbas; Seegerer, Philipp; Koch, Arend; Heppner, Frank; Pfister, Stefan M; Jones, David TW; Sill, Martin; von Deimling, Andreas; Snuderl, Matija; Müller, Klaus-Robert; Forgó, Erna; Howitt, Brooke E; Mertins, Philipp; Klauschen, Frederick; Capper, David
Source: Nature Communications , 13 (1) , Article 7148. (2022)
Publisher Information: Springer Science and Business Media LLC
Publication Year: 2022
Collection: University College London: UCL Discovery
Subject Terms: DNA methylation; Head and neck cancer; Machine learning; Proteomics
Description: The diagnosis of sinonasal tumors is challenging due to a heterogeneous spectrum of various differential diagnoses as well as poorly defined, disputed entities such as sinonasal undifferentiated carcinomas (SNUCs). In this study, we apply a machine learning algorithm based on DNA methylation patterns to classify sinonasal tumors with clinical-grade reliability. We further show that sinonasal tumors with SNUC morphology are not as undifferentiated as their current terminology suggests but rather reassigned to four distinct molecular classes defined by epigenetic, mutational and proteomic profiles. This includes two classes with neuroendocrine differentiation, characterized by IDH2 or SMARCA4/ARID1A mutations with an overall favorable clinical course, one class composed of highly aggressive SMARCB1-deficient carcinomas and another class with tumors that represent potentially previously misclassified adenoid cystic carcinomas. Our findings can aid in improving the diagnostic classification of sinonasal tumors and could help to change the current perception of SNUCs.
Document Type: article in journal/newspaper
File Description: application/pdf
Language: English
Relation: https://discovery.ucl.ac.uk/id/eprint/10161000/
Availability: https://discovery.ucl.ac.uk/id/eprint/10161000/1/s41467-022-34815-3.pdf; https://discovery.ucl.ac.uk/id/eprint/10161000/
Rights: open
Accession Number: edsbas.A27DF6CB
Database: BASE