Artificial intelligence‐powered spatial analysis of tumor‐infiltrating lymphocytes as a predictive biomarker for axitinib in adenoid cystic carcinoma

Abstract

BackgroundThis study analyzed the predictive value of artificial intelligence (AI)‐powered tumor‐infiltrating lymphocyte (TIL) analysis in recurrent or metastatic (R/M) adenoid cystic carcinoma (ACC) treated with axitinib.MethodsPatients from a multicenter, prospective phase II trial evaluating axitinib efficacy in R/M ACC were included in this study. H&E whole‐side images of archival tumor tissues were analyzed by Lunit SCOPE IO, an AI‐powered spatial TIL analyzer.ResultsTwenty‐seven patients were included in the analysis. The best response was stable disease, and the median progression‐free survival (PFS) was 11.1 months (95% CI, 9.2–13.7 months). Median TIL densities in the cancer and surrounding stroma were 25.8/mm2 (IQR, 8.3–73.0) and 180.4/mm2 (IQR, 69.6–342.8), respectively. Patients with stromal TIL density >342.5/mm2 exhibited longer PFS (p = 0.012).ConclusionsCancer and stromal area TIL infiltration were generally low in R/M ACC. Higher stromal TIL infiltration was associated with a longer PFS with axitinib treatment.