Artificial intelligence-guided analysis of the tumor microenvironment predicts response to pembrolizumab in rare tumors.

BACKGROUND: Pathologic tumor response and changes in the tumor microenvironment (TME) predict outcomes to immune checkpoint inhibitors, but are understudied in rare tumors. We investigated whether artificial intelligence (AI)-powered analyses of pretreatment and on-treatment biopsies may inform treatment outcomes to pembrolizumab. METHODS: We evaluated 256 baseline and 248 on-treatment biopsies from 84 patients with rare tumors (10 cohorts) in a phase II pembrolizumab trial. Intratumoral tumor-infiltrating lymphocyte (iTIL) density and tumor content (TC) were assessed on H&E-stained slides using a deep learning-based analyzer (Lunit SCOPE IO). Baseline iTIL and changes in iTIL and TC were correlated with progression-free survival (PFS) and overall survival (OS). Multiplex immunofluorescence was performed in 27 paired samples to assess TME changes. RESULTS: In the high-iTIL tumor group, a baseline iTIL of ≥60 cells/mm2 was associated with favorable PFS (HR 0.49, 95% CI 0.25 to 0.99, p=0.046) and higher CD8+ and CD8+PD-1+ and lower FoxP3+CD8+PD-1+ T-cell density. However, this association with PFS was not seen in the overall cohort (HR 0.62, 95% CI 0.37 to 1.06, p=0.082). In paired biopsies, on-treatment increase in iTIL showed a trend toward improved PFS (HR 0.64, 95% CI 0.40 to 1.06, p=0.084) and was significantly associated with improved OS (HR 0.55, 95% CI 0.35 to 1.01, p=0.037). This increase was also associated with reduced spatial distance between CD8+ immune and tumor cells. Decreased TC during treatment was significantly associated with prolonged PFS and OS (PFS: HR 0.51, p=0.019; OS: HR 0.54, p=0.042). The combination of increased iTIL and decreased TC was significantly associated with better PFS (HR 0.36, p=0.009) and OS (HR 0.36, p=0.029). CONCLUSION: AI-powered assessment of the TME before and during treatment may help inform treatment outcomes to pembrolizumab in patients with rare tumors. TRIAL REGISTRATION NUMBER: NCT02721732.