A microRNA expression signature for the prognosis of oropharyngeal squamous cell carcinoma

Abstract

Background: Oropharyngeal squamous cell carcinoma (SCC) rates have been increasing significantly in recent years, despite a decreasing incidence of head and neck cancer in general. Oropharyngeal SCC has many characteristics that are distinct from other head and neck cancers, and thus it is important to focus specifically on cancers arising in this region, with the goal of improving patient outcomes. One important goal is to identify those patients who are likely to fail standard therapy and who could potentially benefit from alternative or targeted treatments.

Methods: In the current study, the prognostic value of microRNAs (miRNAs) was evaluated in patients with oropharyngeal SCC. miRNAs are small, noncoding RNAs that are master regulators of many important biological processes. In total, 150 oropharyngeal tumors were analyzed using the recently developed quantitative polymerase chain reaction-based method for miRNA expression profiling. In addition, the expression of miRNAs was also compared with human papillomavirus (HPV) transcriptional activities.

Results: The current study identified 6 miRNAs that were found to be significantly associated with cancer survival. A combined expression signature of these miRNAs was prognostic of oropharyngeal SCC, independent of common clinical features or HPV status.

Conclusions: This new miRNA signature was experimentally validated in an independent oropharyngeal SCC cohort. Furthermore, 5 HPV-related miRNAs were identified, which may help to characterize HPV-induced cancers including both oropharyngeal and cervical SCC.

Figure 1

The expression profiles of six prognostic miRNAs in 101 oropharyngeal SCC. The patients were stratified into two groups according to the survival status (deceased or alive). The expression profiles of individual miRNAs were determined in each group, and normalized using a quantile-based scaling method as described previously . The normalized expression data were visualized by further scaling to the value range of 0–1 and grouped into multiple bins with Weka . The p-values were calculated with the Wald test in univariate Cox regression analysis, and further adjusted with permutation tests.

Figure 2

Kaplan-Meier survival analysis to evaluate the miRNA signature using the training cohort. A risk score was calculated based on the final miRNA prediction model and assigned to each patient. Based on the risk score, the patients were stratified into either the low risk group or high risk group. The prognostic value of the miRNA risk scores was evaluated with overall survival (A) and disease-specific survival (B). The p-values were calculated with the log-rank test. (C, D) Leave-one-out cross-validation to evaluate the miRNA modeling strategy. The cross-validated results from all 101 rounds were combined for prognostic evaluation using overall survival (C) and disease-specific survival (D).

Figure 3

Kaplan-Meier survival analysis to evaluate the independence of the miRNA signature from HPV infection. The patients were stratified into two groups based on their HPV status. The miRNA model was applied to HPV+ patients (A) or HPV− patients (B) separately.

Figure 4

Kaplan-Meier survival analysis to evaluate the miRNA signature using the validation cohort for overall survival (A) and disease-specific survival (B).