PURPOSE Biomarkers on the basis of tumor-infiltrating lymphocytes (TIL) are potentially valuable in predicting the effectiveness of immune checkpoint inhibitors (ICI). However, clinical application remains challenging because of methodologic limitations and laborious process involved in spatial analysis of TIL distribution in whole-slide images (WSI). METHODS We have developed an artificial intelligence (AI)–powered WSI analyzer of TIL in the tumor microenvironment that can define three immune phenotypes (IPs): inflamed, immune-excluded, and immune-desert. These IPs were correlated with tumor response to ICI and survival in two independent cohorts of patients with advanced non–small-cell lung cancer (NSCLC). RESULTS Inflamed IP correlated with enrichment in local immune cytolytic activity, higher response rate, and prolonged progression-free survival compared with patients with immune-excluded or immune-desert phenotypes. At the WSI level, there was significant positive correlation between tumor proportion score (TPS) as determined by the AI model and control TPS analyzed by pathologists ( P < .001). Overall, 44.0% of tumors were inflamed, 37.1% were immune-excluded, and 18.9% were immune-desert. Incidence of inflamed IP in patients with programmed death ligand-1 TPS at < 1%, 1%-49%, and ≥ 50% was 31.7%, 42.5%, and 56.8%, respectively. Median progression-free survival and overall survival were, respectively, 4.1 months and 24.8 months with inflamed IP, 2.2 months and 14.0 months with immune-excluded IP, and 2.4 months and 10.6 months with immune-desert IP. CONCLUSION The AI-powered spatial analysis of TIL correlated with tumor response and progression-free survival of ICI in advanced NSCLC. This is potentially a supplementary biomarker to TPS as determined by a pathologist.

BackgroundTumor mutation burden (TMB) is an important biomarker to predict response to anti-PD-L1 treatment across cancer types. TruSight Oncology 500 (TSO500) is currently used globally as a routine assay for TMB.MethodsBetween 2019 and 2021, 1744 patients with cancer received TSO500 assay as part of a real-world clinical practice at the Samsung Medical Center, and 426 received anti-PD-(L)1 treatment. Correlations between TMB and clinical outcomes of anti-PD-(L)1 were analyzed. Digital spatial profiling (DSP) was used to investigate the tumor immune environment’s influence on the treatment response to anti-PD-(L)1 in high TMB (TMB-H) patients (n=8).ResultsThe incidence of TMB-H (≥10 mutations (mt)/megabase (Mb)) was 14.7% (n=257). Among TMB-H patients, the most common cancer type was colorectal cancer (n=108, 42.0%), followed by gastric cancer (GC; n=49, 19.1%), bladder cancer (n=21, 8.2%), cholangiocarcinoma (n=21, 8.2%), non-small cell lung cancer (n=17, 6.6%), melanoma (n=8, 3.1%), gallbladder cancer (GBC; n=7, 2.7%), and others (n=26, 10.1%). The response rate to anti-PD-(L)1 therapy was substantially higher in GC (71.4% vs 25.8%), GBC (50.0% vs 12.5%), head and neck cancer (50.0% vs 11.1%), and melanoma (71.4% vs 50.7%) among TMB-H patients when compared with low TMB (TMB-L) (<10 mt/Mb) patients with statistical significance. Additional analysis of patients with TMB ≥16 mt/Mb demonstrated prolonged survival after anti-PD-(L)1 therapy compared with patients with TMB-L (not reached vs 418 days, p=0.03). The benefit of TMB ≥16 mt/Mb was greater when combined with microsatellite status and PD-L1 expression profiles. Among the TMB-H patients, those who responded to anti-PD-L1 therapy had numerous active immune cells that infiltrated the tumor regions during the DSP analysis. Natural killer cells (p=0.04), cytotoxic T cells (p<0.01), memory T cells (p<0.01), naïve memory T cells (p<0.01), and proteins related to T-cell proliferation (p<0.01) were observed in a responder group compared with a non-responder group. In contrast, exhausted T-cell and M2 macrophage counts were increased in the non-responder group.ConclusionsThe overall incidence of TMB status was analyzed by the TSO500 assay, and TMB-H was observed in 14.7% of the pan-cancer population. In a real-world setting, TMB-H identified by a target sequencing panel seemed to predict response to anti-PD-(L)1 therapy, especially in patients with a higher proportion of immune cells enriched in the tumor region.

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