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Schmidt, Stefan; Linge, Annett; Zwanenburg, Alex; Leger, Stefan; Lohaus, Fabian; Krenn, Constanze; Appold, Steffen; Gudziol, Volker; Nowak, Alexander; Neubeck, Claere von; Tinhofer, Inge; Budach, Volker; Sak, Ali; Stuschke, Martin; Balermpas, Panagiotis; Roedel, Claus; Bunea, Hatice; Grosu, Anca-Ligia; Abdollahi, Amir; Debus, Jürgen; Ganswindt, Ute; Belka, Claus; Pigorsch, Steffi; Combs, Stephanie E.; Moennich, David; Zips, Daniel; Baretton, Gustavo B.; Buchholz, Frank; Baumann, Michael; Krause, Mechthild and Löck, Steffen (2018): Development and Validation of a Gene Signature for Patients with Head and Neck Carcinomas Treated by Postoperative Radio(chemo)therapy. In: Clinical Cancer Research, Vol. 24, No. 6: pp. 1364-1374

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Purpose: The aim of this study was to identify and independently validate a novel gene signature predicting locoregional tumor control (LRC) for treatment individualization of patients with locally advanced HPV-negative head and neck squamous cell carcinomas (HNSCC) who are treated with postoperative radio(chemo)therapy (PORT-C). Experimental Design: Gene expression analyses were performed using NanoString technology on a multicenter training cohort of 130 patients and an independent validation cohort of 121 patients. The analyzed gene set was composed of genes with a previously reported association with radio(chemo)sensitivity or resistance to radio(chemo)therapy. Gene selection and model building were performed comparing several machine-learning algorithms. Results: We identified a 7-gene signature consisting of the three individual genes HILPDA, CD24, TCF3, and one metagene combining the highly correlated genes SERPINE1, INHBA, P4HA2, and ACTN1. The 7-gene signature was used, in combination with clinical parameters, to fit a multivariable Cox model to the training data (concordance index, ci = 0.82), which was successfully validated (ci = 0.71). The signature showed improved performance compared with clinical parameters alone (ci = 0.66) and with a previously published model including hypoxia-associated genes and cancer stem cell markers (ci = 0.65). It was used to stratify patients into groups with low and high risk of recurrence, leading to significant differences in LRC in training and validation (P < 0.001). Conclusions: We have identified and validated the first hypothesis-based gene signature for HPV-negative HNSCC treated by PORT-C including genes related to several radiobiological aspects. A prospective validation is planned in an ongoing prospective clinical trial before potential application in clinical trials for patient stratification. 2018 AACR.

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