Chen, Chu, Lohavanichbutr, Pawadee, Zhang, Yuzheng, Houck, John R., Upton, Melissa P., Abedi-Ardekani, Behnoush, Agudo, Antonio, Ahrens, Wolfgang, Alemany, Laia, Anantharaman, Devasena, Conway, David I., Futran, Neal D., Holcatova, Ivana, Günther, Kathrin, Hansen, Bo T., Healy, Claire M., Itani, Doha, Kjaerheim, Kristina, Monroe, Marcus M., Thomson, Peter J., Witt, Benjamin L., Nakoneshny, Steven, Peterson, Lisa A., Schwartz, Stephen M., Zarins, Katie R., Hashibe, Mia, Brennan, Paul, Rozek, Laura S., Wolf, Gregory, Dort, Joseph C., and Wang, Pei (2020) Prediction of survival of HPV16-negative, p16-negative oral cavity cancer patients using a 13-gene signature: A multicenter study using FFPE samples. Oral Oncology, 100. 104487.

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Abstract

Objectives: To test the performance of an oral cancer prognostic 13-gene signature for the prediction of survival of patients diagnosed with HPV-negative and p16-negative oral cavity cancer.

Materials and Methods: Diagnostic formalin-fixed paraffin-embedded oral cavity cancer tumor samples were obtained from the Fred Hutchinson Cancer Research Center/University of Washington, University of Calgary, University of Michigan, University of Utah, and seven ARCAGE study centers coordinated by the International Agency of Research on Cancer. RNA from 638 Human Papillomavirus (HPV)-negative and p16-negative samples was analyzed for the 13 genes using a NanoString assay. Ridge-penalized Cox regressions were applied to samples randomly split into discovery and validation sets to build models and evaluate the performance of the 13-gene signature in predicting 2-year oral cavity cancer-specific survival overall and separately for patients with early and late stage disease.

Results: Among AJCC stage I/II patients, including the 13-gene signature in the model resulted in substantial improvement in the prediction of 2-year oral cavity cancer-specific survival. For models containing age and sex with and without the 13-gene signature score, the areas under the Receiver Operating Characteristic Curve (AUC) and partial AUC were 0.700 vs. 0.537 (p < 0.001), and 0.046 vs. 0.018 (p < 0.001), respectively. Improvement in predicting prognosis for AJCC stage III/IV disease also was observed, but to a lesser extent. Conclusions: If confirmed using tumor samples from a larger number of early stage oral cavity cancer patients, the 13-gene signature may inform personalized treatment of early stage HPV-negative and p16-negative oral cavity cancer patients.

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