A 13-Gene Signature Prognostic of HPV-Negative OSCC: Discovery and External Validation CLINICAL CANCER RESEARCH Lohavanichbutr, P., Mendez, E., Holsinger, F. C., Rue, T. C., Zhang, Y., Houck, J., Upton, M. P., Futran, N., Schwartz, S. M., Wang, P., Chen, C. 2013; 19 (5): 1197-1203


To identify a prognostic gene signature for patients with human papilloma virus (HPV)-negative oral squamous cell carcinomas (OSCC).Two gene expression datasets were used: a training dataset from the Fred Hutchinson Cancer Research Center (FHCRC, Seattle, WA; n = 97) and a validation dataset from the MD Anderson Cancer Center (MDACC, Houston, TX; n = 71). We applied L1/L2-penalized Cox regression models to the FHCRC data on the 131-gene signature previously identified to be prognostic in patients with OSCCs to identify a prognostic model specific for patients with high-risk HPV-negative OSCCs. The models were tested with the MDACC dataset using a receiver operating characteristic (ROC) analysis.A 13-gene model was identified as the best predictor of HPV-negative OSCC-specific survival in the training dataset. The risk score for each patient in the validation dataset was calculated from this model and dichotomized at the median. The estimated 2-year mortality (± SE) of patients with high-risk scores was 47.1% (± 9.24%) compared with 6.35% (± 4.42) for patients with low-risk scores. ROC analyses showed that the areas under the curve for the age, gender, and treatment modality-adjusted models with risk score [0.78; 95% confidence interval (CI), 0.74-0.86] and risk score plus tumor stage (0.79; 95% CI, 0.75-0.87) were substantially higher than for the model with tumor stage (0.54; 95% CI, 0.48-0.62).We identified and validated a 13-gene signature that is considerably better than tumor stage in predicting survival of patients with HPV-negative OSCCs. Further evaluation of this gene signature as a prognostic marker in other populations of patients with HPV-negative OSCC is warranted.

View details for DOI 10.1158/1078-0432.CCR-12-2647

View details for Web of Science ID 000315740200027

View details for PubMedID 23319825