Prediction of treatment response within HPV-positive oropharyngeal squamous cell carcinoma (OPSCC) remains crude. We aimed to develop and validate a pre-treatment proteomic signature that identifies the high-risk subset of HPV-positive OPSCC. This model would improve both individual prognostication as well as recruitment of clinically appropriate patients for de-escalation trial inclusion.
This retrospective case-control study included 124 patients with locally advanced HPV-positive OPSCC treated with definitive radiotherapy +/- systemic therapy at the Princess Alexandra Hospital (PAH, Brisbane, Australia) between 2007 and 2019. Ethical approval was obtained through the Metro South Human Research Ethics Committee at the PAH. Primary tumour biopsy specimens were analysed using data-independent acquisition mass spectrometry. Disease free survival (DFS) was the primary end-point and combined residual and recurrent disease occurring within the 5-year follow-up period. A proteomic signature associated DFS was identified from the top 50 proteins in univariate cox, as the set of proteins that formed the optimal combination to achieve a multivariate cox model with the lowest Akaike Information Criterion.
A 21-protein signature was identified through this analysis. When applied to the training cohort, computed risk score categorised patients into low, intermediate and high risk of recurrence (P<0.0001). The top 10 proteins from the 21-protein signature out-performed clinicopathological variables in prediction of DFS for the training cohort (Hazard ratio (HR) 30.76, p<0.001, c-index 0.843). This proteomic signature was validated using the heterogeneous head and neck cancer TCGA cohort for overall survival (n=502, HR 1.7, p=0.0002).
This 21-protein signature represents the first proteomics-based risk stratification model for HPV-positive OPSCC. Refining pre-treatment prognostication, through application of this protein signature, has the potential to benefit both the individual patient and future de-escalation trials.