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    Development and validation of a 6-gene signature for the prognosis of loco-regional control in patients with HPV-negative locally advanced HNSCC treated by postoperative radio(chemo)therapy.
        
        Radiother. Oncol. 171, 91-100 (2022)
    
    
    
				PURPOSE: The aim of this study was to develop and validate a novel gene signature from full-transcriptome data using machine-learning approaches to predict loco-regional control (LRC) of patients with human papilloma virus (HPV)-negative locally advanced head and neck squamous cell carcinoma (HNSCC), who received postoperative radio(chemo)therapy (PORT-C). MATERIALS AND METHODS: Gene expression analysis was performed using Affymetrix GeneChip Human Transcriptome Array 2.0 on a multicentre retrospective training cohort of 128 patients and an independent validation cohort of 114 patients from the German Cancer Consortium - Radiation Oncology Group (DKTK-ROG). Genes were filtered based on differential gene expression analyses and Cox regression. The identified gene signature was combined with clinical parameters and with previously identified genes related to stem cells and hypoxia. Technical validation was performed using nanoString technology. RESULTS: We identified a 6-gene signature consisting of four individual genes CAV1, GPX8, IGLV3-25, TGFBI, and one metagene combining the highly correlated genes INHBA and SERPINE1. This signature was prognostic for LRC on the training data (ci=0.84) and in validation (ci=0.63) with a significant patient stratification into two risk groups (p=0.005). Combining the 6-gene signature with the clinical parameters T stage and tumour localisation as well as the stem-cell marker CD44 and the 15-gene hypoxia-associated signature improved the validation performance (ci=0.69, p=0.001). CONCLUSION: We have developed and validated a novel prognostic 6-gene signature for LRC of HNSCC patients with HPV-negative tumours treated by PORT-C. After successful prospective validation the signature can be part of clinical trials on the individualization of radiotherapy.
			
			
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        Publikationstyp
        Artikel: Journalartikel
    
 
    
        Dokumenttyp
        Wissenschaftlicher Artikel
    
 
     
    
    
        Schlagwörter
        Cancer Stem Cells ; Gene Signature ; Head And Neck Squamous Cell Carcinoma ; Hypoxia ; Machine Learning ; Postoperative Radiotherapy
    
 
     
    
    
        Sprache
        englisch
    
 
    
        Veröffentlichungsjahr
        2022
    
 
     
    
        HGF-Berichtsjahr
        2022
    
 
    
    
        ISSN (print) / ISBN
        0167-8140
    
 
    
        e-ISSN
        1879-0887
    
 
     
     
     
	     
	 
	 
    
        Zeitschrift
        Radiotherapy and Oncology
    
 
		
    
        Quellenangaben
        
	    Band: 171,  
	    
	    Seiten: 91-100 
	    
	    
	
    
 
  
         
        
            Verlag
            Elsevier
        
 
         
	
         
         
         
         
         
	
         
         
         
    
         
         
         
         
         
         
         
    
        Begutachtungsstatus
        Peer reviewed
    
 
     
    
        POF Topic(s)
        30504 - Mechanisms of Genetic and Environmental Influences on Health and Disease
30203 - Molecular Targets and Therapies
 
    30203 - Molecular Targets and Therapies
        Forschungsfeld(er)
        Radiation Sciences
    
 
    
        PSP-Element(e)
        G-521800-001
G-501300-001
 
    G-501300-001
        Förderungen
        Nationales Centrum für Tumorerkrankungen Heidelberg
Universidad Católica de Córdoba
TNTB
Normal and Tumor Tissue Bank
National Center for Tumor Diseases
 
     	
    
    Universidad Católica de Córdoba
TNTB
Normal and Tumor Tissue Bank
National Center for Tumor Diseases
        Scopus ID
        85129269859
    
    
        PubMed ID
        35429503
    
    
        Erfassungsdatum
        2022-07-29