J Natl Cancer Inst. 2022 Apr 11;114(4):609-617. doi: 10.1093/jnci/djab215.
BACKGROUND: HPV-associated oropharyngeal squamous cell carcinoma (OPCSCC) has excellent control rates compared to non-virally associated OPSCC. Multiple trials are actively testing whether de-escalation of treatment intensity for these patients can maintain oncologic equipoise while reducing treatment related toxicity. We have developed OP-TIL, a biomarker that characterizes the spatial interplay between tumor-infiltrating lymphocytes (TILs) and surrounding cells in histology images. Herein, we sought to test whether OP-TIL can segregate stage I HPV-associated OPSCC patients into low-risk and high-risk groups and aid in patient selection for de-escalation clinical trials.
METHODS: Association between OP-TIL and patient outcome was explored on whole slide H&E images from 439 stage I HPV-associated OPSCC patients across six institutional cohorts. One institutional cohort (n = 94) was used to identify the most prognostic features and train a Cox regression model to predict risk of recurrence and death. Survival analysis was used to validate the algorithm as a biomarker of recurrence/death in the remaining five cohorts (n = 345). All statistical tests were 2-sided.
RESULTS: OP-TIL separated stage I HPV-associated OPSCC patients with ≤30 pack-year smoking history into low-risk (2-year disease-free survival [DFS] = 94.2%; 5-year DFS= 88.4%) and high-risk (2-year DFS = 82.5%; 5-year DFS = 74.2%) groups (hazard ratio = 2.56, 95% confidence interval = 1.52-4.32, P < .001), even after adjusting for age, smoking status, T and N-classification, and treatment modality on multivariate analysis for DFS (hazard ratio = 2.27, 95% confidence interval = 1.32-3.94, P = .003).
CONCLUSIONS: OP-TIL can identify stage I HPV-associated OPSCC patients likely to be poor candidates for treatment de-escalation. Following validation on previously completed multi-institutional clinical trials, OP-TIL has the potential to be a biomarker, beyond clinical stage and HPV status, that can be used clinically to optimize patient selection for de-escalation.
PubMed ID: 34850048
Article Size: 1.9 MB