SLUG-related partial epithelial-to-mesenchymal transition is a transcriptomic prognosticator of head and neck cancer survival

Schinke, Henrik; Pan, Min; Akyol, Merve; Zhou, Jiefu; Shi, Enxian; Kranz, Gisela; Libl, Darko; Quadt, Tanja; Simon, Florian; Canis, Martin; Baumeister, Philipp und Gires, Olivier (2021): SLUG-related partial epithelial-to-mesenchymal transition is a transcriptomic prognosticator of head and neck cancer survival. In: Molecular Oncology, Bd. 16, Nr. 2: S. 347-367

Abstract

Partial epithelial-to-mesenchymal transition (pEMT) contributes to cellular heterogeneity that is associated with nodal metastases and unfavorable clinical parameters in head and neck squamous cell carcinomas (HNSCCs). We developed a single-cell RNA sequencing signature-based pEMT quantification through cell type-dependent deconvolution of bulk RNA sequencing and microarray data combined with single-sample scoring of molecular phenotypes (Singscoring). Clinical pEMT-Singscores served as molecular classifiers in multivariable Cox proportional hazard models and high scores prognosticated poor overall survival and reduced response to irradiation as independent parameters in large HNSCC cohorts [The Cancer Genome Atlas (TCGA), MD Anderson Cancer Centre (MDACC), Fred Hutchinson Cancer Research Center (FHCRC)]. Differentially expressed genes confirmed enhanced cell motility and reduced oxidative phosphorylation and epithelial differentiation in pEMT(high) patients. In patients and cell lines, the EMT transcription factor SLUG correlated most strongly with pEMT-Singscores and promoted pEMT, enhanced invasion, and resistance to irradiation in vitro. SLUG protein levels in HNSCC predicted disease-free survival, and its peripheral expression at the interphase to the tumor microenvironment was significantly increased in relapsing patients. Hence, pEMT-Singscores represent a novel risk predictor for HNSCC stratification regarding clinical outcome and therapy response that is partly controlled by SLUG.

• Dokumententyp: Zeitschriftenartikel
• Fakultät: Medizin
• Themengebiete: 600 Technik, Medizin, angewandte Wissenschaften > 610 Medizin und Gesundheit
• ISSN: 1574-7891
• Sprache: Englisch