Artificial intelligence (AI)-powered immune phenotyping to predict outcomes of immunooncology (IO)-based regimens in hepatocellular carcinoma (HCC).

601 Background: Anti-PD-(L)1 monotherapy or combination with bevacizumab or ipilimumab are approved treatment options in HCC. Nevertheless, not all patients benefit from IO treatment, and discovery of predictive biomarkers for IO outcome has not been fully investigated. Immune phenotype analysis by AI-powered spatial tumor-infiltrating lymphocyte (TIL) analyzer in H&E whole-slide images (WSI), Lunit SCOPE IO, has shown predictive effect across multiple cancer types. Here, we investigated the correlation between immune phenotype (IP) and the real-world outcomes in HCC. Methods: Real-world dataset of 177 patients with HCC were retrospectively collected from CHA Bundang Medical Center. Inflamed score was defined by the proportion of area with high intra-tumoral TIL density per 0.5 mm2-sized grid. IP status was sub-analyzed by PD-L1 combined positive score (CPS) and prognostic factors including Child-Pugh class and Barcelona Clinic Liver Cancer (BCLC) stage. We evaluated the correlation between IP and IO outcome by regimen (atezolizumab+bevacizumab [Atez+Bev], n=100; nivolumab+/-ipilimumab [Niv+/-Ipi], n=77). Results: The majority of patients (75.3%) were Child-Pugh class A (75.3%) and BCLC stage C (86.5%), respectively. Atez+Bev was mostly received as first-line therapy (92.0%), whereas Niv+/-Ipi as second-line or beyond (98.7%). The inflamed score was significantly higher in patients who had lymph node metastasis ( p=0.008), but it was not correlated with other metastatic sites, or any other prognostic factors. Of 177 patients, 105 (59.3%) patients were classified as having a high inflamed score (≥10%) and 72 (40.7%) patients as having lower than 10%. PD-L1 CPS was significantly higher in the sample with high score compared to those with low inflamed score ( p=0.01387). PFS of Niv+/-Ipi were significantly favorable in the patients with high inflamed score (3-m PFS rate; 44.0% vs 3.61%, 12-m PFS rate; 17.8% vs 0%, Hazard ratio [HR] 0.37, 95% confidence interval [CI] 0.22-0.63, p<0.001), while PFS of Atez+Bev were not different according to inflamed score (3-m PFS rate; 67.5% vs 57.3%, 12-m PFS rate; 36.6% vs 31.0%, HR 0.80, 95% CI 0.48-1.32, p=0.400). Conclusions: Inflamed score, the proportion of area with high intra-tumoral TIL infiltration, can be a clinically significant predictor of PFS of Niv+/-Ipi, but it was not relevant for Atez+Bev treatment outcomes.