PDF file - 57K, Table S1. Integrated Prediction Error (5 years range of integration). To estimate the prediction error we used the .632+ estimate of the integrated Brier score. For OS the cumulative prediction error decreased from 0.192 for the model with clinical factors to 0.182 using additional HPV marker combination and to 0.183 using additional CxCa-like viral RNA patterns. On the contrary, no improvement in prediction accuracy was observed for PFS by adding single HPV markers or marker combinations to clinical factors.
ARTICLE ABSTRACT
Oropharyngeal squamous cell carcinomas (OPSCC) that are associated with human papilloma virus (HPV) infection carry a more favorable prognosis than those that are HPV-negative. However, it remains unclear which biomarker(s) can reliably determine which OPSCC specimens are truly driven by HPV infection. In this study, we analyzed 199 fresh-frozen OPSCC specimens for HPV DNA, viral load, RNA expression patterns typical for cervical carcinomas (CxCaRNA+), and the HPV-targeted tumor suppressor protein p16INK4a as markers for HPV infection. In this set of specimens, there was a 49% prevalence of DNA for the cancer-associated HPV type 16 (HPV+). However, there was only a 16% prevalence of high viral load and only a 20% prevalence of CxCaRNA+, a marker of HPV16 carcinogenic activity. Among the CxCaRNA+ tumors, 78% of the specimens exhibited overexpression of p16INK4a, which also occurred in 14% of the HPV-negative tumors. Using a multivariate survival analysis with HPV negativity as the reference group, CxCaRNA+ as a single marker conferred the lowest risk of death [HR = 0.28, 95% confidence interval (CI), 0.13–0.61] from oropharyngeal cancer, closely followed by high viral load (HR = 0.32, 95% CI, 0.14–0.73). In contrast, a weaker inverse association was found for OPSCC that were HPV+ and p16INK4a high (HR = 0.55, 95% CI, 0.29–1.08). In summary, our findings argued that viral load or RNA pattern analysis is better suited than p16INK4a expression to identify HPV16-driven tumors in OPSCC patient populations. Cancer Res; 72(19); 4993–5003. ©2012 AACR.
