Purpose: The aim of this study was to identify and independently validate a novel gene signature predicting loco-regional 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 by genes with previously reported association to 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 3 individual genes HILPDA, CD24,TCF3 and one metagene combining the highly correlated genes SERPINE1, INHBA, P4HA2, 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 to clinical parameters alone (ci=0.66) and to 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.
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