Machine learning analysis of DNA methylation profiles distinguishes primary lung squamous cell carcinomas from head and neck metastases

Author:

Jurmeister Philipp123ORCID,Bockmayr Michael145ORCID,Seegerer Philipp6ORCID,Bockmayr Teresa1,Treue Denise1ORCID,Montavon Grégoire6,Vollbrecht Claudia137ORCID,Arnold Alexander1,Teichmann Daniel8,Bressem Keno9ORCID,Schüller Ulrich4510ORCID,von Laffert Maximilian1,Müller Klaus-Robert61112,Capper David38ORCID,Klauschen Frederick13ORCID

Affiliation:

1. Institute of Pathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, 10117 Berlin, Germany.

2. Charité Comprehensive Cancer Center, 10117 Berlin, Germany.

3. German Cancer Consortium (DKTK), Partner Site Berlin, and German Cancer Research Center (DKFZ), 69210 Heidelberg, Germany.

4. Department of Pediatric Hematology and Oncology, University Medical Center Hamburg-Eppendorf, 20251 Hamburg, Germany.

5. Research Institute Children's Cancer Center Hamburg, 20251 Hamburg, Germany.

6. Machine-Learning Group, Department of Software Engineering and Theoretical Computer Science, Technical University of Berlin, 10623 Berlin, Germany.

7. German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120 Heidelberg, Germany

8. Department of Neuropathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, 10117 Berlin, Germany.

9. Department of Radiology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, 10117 Berlin, Germany.

10. Institute of Neuropathology, University Medical Center Hamburg-Eppendorf, 20251 Hamburg, Germany.

11. Department of Brain and Cognitive Engineering, Korea University, 136-713 Seoul, South Korea.

12. Max-Planck-Institute for Informatics, 66123 Saarbrücken, Germany.

Abstract

A DNA methylation–based classifier facilitates the differentiation of primary lung and metastatic head and neck cancer with diagnostic accuracy.

Funder

German Federal Ministry of Education and Research

European Fund for Regional Development (EFRE) and the Federal State of Berlin

Fördergemeinschaft Kinderkrebszentrum Hamburg

Government of South Korea

Berlin Institute of Health (BIH) Charité Clinician Scientist Program

Publisher

American Association for the Advancement of Science (AAAS)

Subject

General Medicine

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