Development and validation of a gene signature for patients with head and neck carcinomas treated by postoperative radio(chemo)therapy

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 head and neck squamous cell carcinomas (HNSCC) who are treated with postoperative radio(chemo)therapy (PORT-C). Gene expression analyses were performed using nanoString technology on a multicenter training cohort of 195 patients and an independent validation cohort of 142 patients. The analyzed gene set was composed hypothesis-driven and included genes with previously reported association to radio(chemo)sensitivity or resistance to radio(chemo)therapy. Gene selection and model building were performed within a specifically developed statistical framework comparing several machine-learning algorithms. This procedure identified a 7-gene signature for HPV16 DNA negative tumors consisting of the genes: SERPINE1, INHBA, P4HA2, ACTN1, HILPDA, CD24 and TCF3. The 7-gene signature was used to fit a multivariable Cox model to the training data (concordance index, ci=0.84), which was successfully validated (ci=0.71). Thus, the signature showed improved performance compared to a clinical model (ci=0.66) and to a previously published model including hypoxia-associated genes and cancer stem cell markers (ci=0.65). Furthermore, the signature was used to stratify patients into groups with low and high risk of recurrence. Significant differences in LRC between these groups were found in training and validation (p<0.001). A prospective validation is planned in an ongoing prospective clinical trial of the DKTK-ROG before potential application in clinical trials for patient stratification.