Research ExplorerPublicationsDNA methylation-based classification of sinonasal tumors

DNA methylation-based classification of sinonasal tumors

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DNA methylation-based classification of sinonasal tumors. / 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 T W; Sill, Martin; von Deimling, Andreas; Snuderl, Matija; Müller, Klaus-Robert; Forgó, Erna; Howitt, Brooke E; Mertins, Philipp; Klauschen, Frederick; Capper, David.

In: NAT COMMUN, Vol. 13, No. 1, 7148, 28.11.2022.

Research output: SCORING: Contribution to journal › SCORING: Journal article › Research › peer-review

Harvard

Jurmeister, P, Glöß, S, Roller, R, Leitheiser, M, Schmid, S, Mochmann, LH, Payá Capilla, E, Fritz, R, Dittmayer, C, Friedrich, C, Thieme, A, Keyl, P, Jarosch, A, Schallenberg, S, Bläker, H, Hoffmann, I, Vollbrecht, C, Lehmann, A, Hummel, M, Heim, D, Haji, M, Harter, P, Englert, B, Frank, S, Hench, J, Paulus, W, Hasselblatt, M, Hartmann, W, Dohmen, H, Keber, U, Jank, P, Denkert, C, Stadelmann, C, Bremmer, F, Richter, A, Wefers, A, Ribbat-Idel, J, Perner, S, Idel, C, Chiariotti, L, Della Monica, R, Marinelli, A, Schüller, U, Bockmayr, M, Liu, J, Lund, VJ, Forster, M, Lechner, M, Lorenzo-Guerra, SL, Hermsen, M, Johann, PD, Agaimy, A, Seegerer, P, Koch, A, Heppner, F, Pfister, SM, Jones, DTW, Sill, M, von Deimling, A, Snuderl, M, Müller, K-R, Forgó, E, Howitt, BE, Mertins, P, Klauschen, F & Capper, D 2022, 'DNA methylation-based classification of sinonasal tumors', NAT COMMUN, vol. 13, no. 1, 7148. https://doi.org/10.1038/s41467-022-34815-3

APA

Jurmeister, P., Glöß, S., Roller, R., Leitheiser, M., Schmid, S., Mochmann, L. H., Payá Capilla, E., Fritz, R., Dittmayer, C., Friedrich, C., Thieme, A., Keyl, P., Jarosch, A., Schallenberg, S., Bläker, H., Hoffmann, I., Vollbrecht, C., Lehmann, A., Hummel, M., ... Capper, D. (2022). DNA methylation-based classification of sinonasal tumors. NAT COMMUN, 13(1), [7148]. https://doi.org/10.1038/s41467-022-34815-3

Vancouver

Jurmeister P, Glöß S, Roller R, Leitheiser M, Schmid S, Mochmann LH et al. DNA methylation-based classification of sinonasal tumors. NAT COMMUN. 2022 Nov 28;13(1). 7148. https://doi.org/10.1038/s41467-022-34815-3

Bibtex

@article{301b89615d554d03a8e316d4907b06e5,
title = "DNA methylation-based classification of sinonasal tumors",
abstract = "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.",
keywords = "Humans, DNA Methylation/genetics, Proteomics, Reproducibility of Results, Carcinoma, DNA Helicases/genetics, Nuclear Proteins/genetics, Transcription Factors",
author = "Philipp Jurmeister and Stefanie Gl{\"o}{\ss} and Ren{\'e}e Roller and Maximilian Leitheiser and Simone Schmid and Mochmann, {Liliana H} and {Pay{\'a} Capilla}, Emma and Rebecca Fritz and Carsten Dittmayer and Corinna Friedrich and Anne Thieme and Philipp Keyl and Armin Jarosch and Simon Schallenberg and Hendrik Bl{\"a}ker and Inga Hoffmann and Claudia Vollbrecht and Annika Lehmann and Michael Hummel and Daniel Heim and Mohamed Haji and Patrick Harter and Benjamin Englert and Stephan Frank and J{\"u}rgen Hench and Werner Paulus and Martin Hasselblatt and Wolfgang Hartmann and Hildegard Dohmen and Ursula Keber and Paul Jank and Carsten Denkert and Christine Stadelmann and Felix Bremmer and Annika Richter and Annika Wefers and Julika Ribbat-Idel and Sven Perner and Christian Idel and Lorenzo Chiariotti and {Della Monica}, Rosa and Alfredo Marinelli and Ulrich Sch{\"u}ller and Michael Bockmayr and Jacklyn Liu and Lund, {Valerie J} and Martin Forster and Matt Lechner and Lorenzo-Guerra, {Sara L} and Mario Hermsen and Johann, {Pascal D} and Abbas Agaimy and Philipp Seegerer and Arend Koch and Frank Heppner and Pfister, {Stefan M} and Jones, {David T W} and Martin Sill and {von Deimling}, Andreas and Matija Snuderl and Klaus-Robert M{\"u}ller and Erna Forg{\'o} and Howitt, {Brooke E} and Philipp Mertins and Frederick Klauschen and David Capper",
note = "{\textcopyright} 2022. The Author(s).",
year = "2022",
month = nov,
day = "28",
doi = "10.1038/s41467-022-34815-3",
language = "English",
volume = "13",
journal = "NAT COMMUN",
issn = "2041-1723",
publisher = "NATURE PUBLISHING GROUP",
number = "1",

}

RIS

TY - JOUR

T1 - DNA methylation-based classification of sinonasal tumors

AU - Jurmeister, Philipp

AU - Glöß, Stefanie

AU - Roller, Renée

AU - Leitheiser, Maximilian

AU - Schmid, Simone

AU - Mochmann, Liliana H

AU - Payá Capilla, Emma

AU - Fritz, Rebecca

AU - Dittmayer, Carsten

AU - Friedrich, Corinna

AU - Thieme, Anne

AU - Keyl, Philipp

AU - Jarosch, Armin

AU - Schallenberg, Simon

AU - Bläker, Hendrik

AU - Hoffmann, Inga

AU - Vollbrecht, Claudia

AU - Lehmann, Annika

AU - Hummel, Michael

AU - Heim, Daniel

AU - Haji, Mohamed

AU - Harter, Patrick

AU - Englert, Benjamin

AU - Frank, Stephan

AU - Hench, Jürgen

AU - Paulus, Werner

AU - Hasselblatt, Martin

AU - Hartmann, Wolfgang

AU - Dohmen, Hildegard

AU - Keber, Ursula

AU - Jank, Paul

AU - Denkert, Carsten

AU - Stadelmann, Christine

AU - Bremmer, Felix

AU - Richter, Annika

AU - Wefers, Annika

AU - Ribbat-Idel, Julika

AU - Perner, Sven

AU - Idel, Christian

AU - Chiariotti, Lorenzo

AU - Della Monica, Rosa

AU - Marinelli, Alfredo

AU - Schüller, Ulrich

AU - Bockmayr, Michael

AU - Liu, Jacklyn

AU - Lund, Valerie J

AU - Forster, Martin

AU - Lechner, Matt

AU - Lorenzo-Guerra, Sara L

AU - Hermsen, Mario

AU - Johann, Pascal D

AU - Agaimy, Abbas

AU - Seegerer, Philipp

AU - Koch, Arend

AU - Heppner, Frank

AU - Pfister, Stefan M

AU - Jones, David T W

AU - Sill, Martin

AU - von Deimling, Andreas

AU - Snuderl, Matija

AU - Müller, Klaus-Robert

AU - Forgó, Erna

AU - Howitt, Brooke E

AU - Mertins, Philipp

AU - Klauschen, Frederick

AU - Capper, David

N1 - © 2022. The Author(s).

PY - 2022/11/28

Y1 - 2022/11/28

N2 - 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.

AB - 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.

KW - Humans

KW - DNA Methylation/genetics

KW - Proteomics

KW - Reproducibility of Results

KW - Carcinoma

KW - DNA Helicases/genetics

KW - Nuclear Proteins/genetics

KW - Transcription Factors

U2 - 10.1038/s41467-022-34815-3

DO - 10.1038/s41467-022-34815-3

M3 - SCORING: Journal article

C2 - 36443295

VL - 13

JO - NAT COMMUN

JF - NAT COMMUN

SN - 2041-1723

IS - 1

M1 - 7148

ER -