NSD1- and NSD2-damaging mutations define a subset of laryngeal tumors with favorable prognosis

Suraj Peri (), Evgeny Izumchenko, Adrian D. Schubert, Michael J. Slifker, Karen Ruth, Ilya G. Serebriiskii, Theresa Guo, Barbara A. Burtness, Ranee Mehra, Eric A. Ross, David Sidransky and Erica A. Golemis ()
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Suraj Peri: Fox Chase Cancer Center
Evgeny Izumchenko: Johns Hopkins University School of Medicine
Adrian D. Schubert: Johns Hopkins University School of Medicine
Michael J. Slifker: Fox Chase Cancer Center
Karen Ruth: Fox Chase Cancer Center
Ilya G. Serebriiskii: Fox Chase Cancer Center
Theresa Guo: Johns Hopkins University School of Medicine
Barbara A. Burtness: Yale Cancer Center, Yale School of Medicine, Yale University
Ranee Mehra: Johns Hopkins University School of Medicine
Eric A. Ross: Fox Chase Cancer Center
David Sidransky: Johns Hopkins University School of Medicine
Erica A. Golemis: Fox Chase Cancer Center

Nature Communications, 2017, vol. 8, issue 1, 1-10

Abstract: Abstract Squamous cell carcinomas of the head and neck (SCCHN) affect anatomical sites including the oral cavity, nasal cavity, pharynx, and larynx. Laryngeal cancers are characterized by high recurrence and poor overall survival, and currently lack robust molecular prognostic biomarkers for treatment stratification. Using an algorithm for integrative clustering that simultaneously assesses gene expression, somatic mutation, copy number variation, and methylation, we for the first time identify laryngeal cancer subtypes with distinct prognostic outcomes, and differing from the non-prognostic laryngeal subclasses reported by The Cancer Genome Atlas (TCGA). Although most common laryngeal gene mutations are found in both subclasses, better prognosis is strongly associated with damaging mutations of the methyltransferases NSD1 and NSD2, with findings confirmed in an independent validation cohort consisting of 63 laryngeal cancer patients. Intriguingly, NSD1/2 mutations are not prognostic for nonlaryngeal SCCHN. These results provide an immediately useful clinical metric for patient stratification and prognostication.

Date: 2017
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DOI: 10.1038/s41467-017-01877-7

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