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Abstracts : Artificial intelligence-powered spatial analysis of tumor-infiltrating lymphocytes predicts survival after immune checkpoint inhibitor therapy across multiple cancer types.

Jeanne Shen et al. — ASCO 2021

Artificial intelligence-powered spatial analysis of tumor-infiltrating lymphocytes predicts survival after immune checkpoint inhibitor therapy across multiple cancer types.


Abstract


Background :Tumor infiltrating lymphocytes (TIL) are a potential tumor-agnostic biomarker for immune checkpoint inhibitor (ICI) therapy. We previously reported the clinical application of an artificial intelligence-powered spatial TIL analyzer, Lunit SCOPE IO, for predicting ICI treatment outcomes in advanced non-small cell lung cancer (NSCLC). Here, we expand the clinical application of Lunit SCOPE IO as a tumor-agnostic ICI biomarker across multiple cancer types.


Methods : Lunit SCOPE IO was trained and validated with a 2.8 x 109 micrometer2 area and 5.9 x 106 TILs from 3,166 H&E Whole-Slide Images (WSI) of multiple cancer types, annotated by 52 board-certified pathologists. The Inflamed Score (IS) was defined as the proportion of all tumor-containing 1 mm2-size tiles within a WSI classified as being of the inflamed immune phenotype (high TIL density within cancer epithelium). We first evaluated the correlation between the IS and TMB, MSI-H, and immune cytolytic activity (GZMA and PRF1) across 22 cancer types from The Cancer Genome Atlas (TCGA, n = 7,467). Subsequently, the correlation between the IS and overall survival after ICI treatment was evaluated in a real-world dataset of patients with 9 different tumor types (n = 1,013), retrospectively collected from Stanford University Medical Center, Chonnam National University Hospital, Samsung Medical Center, and Seoul National University Bundang Hospital.


Results : Lunit SCOPE IO accurately detected CE, CS, and TILs with an area under the receiver-operating-characteristic curve of 0.970, 0.949, and 0.925, respectively. In the TCGA pan-cancer cohort, Lunit SCOPE IO’s IS correlated significantly with immune cytolytic activity (Spearman rho = 0.504, p< 0.001), TMB-high (≥ 10 mutations/Mb, fold change 1.39, p< 0.001) and MSI-H (fold change 1.45, p< 0.001). The IS-positive proportions of microsatellite-stable (MSS) and TMB-low cases were 42.5% and 17.1%, using the thresholds of IS ≥ 20% and ≥ 50% as presumptive clinical cutoffs. In the real-world ICI clinical dataset (n = 1,013), an IS ≥ 20% correlated significantly with favorable overall survival after ICI treatment (cancer type-adjusted hazard ratio [HR] 0.70, 95% confidence interval [CI] 0.59-0.83, p< 0.0001). Furthermore, this association remained significant after the exclusion of NSCLC patients (n = 519) (adjusted HR 0.68, 95% CI 0.53-0.86, p = 0.0016) indicating that the effect was not driven solely by one major tumor type.


Conclusions : The Inflamed Score (IS), as evaluated by Lunit SCOPE IO, correlates with favorable overall survival after ICI treatment across multiple tumor types. AI-powered spatial TIL analysis of the tumor microenvironment may be able to detect a significant proportion of ICI responders, and offers promise as a new companion diagnostic, particularly in patients with MSS/TMB-low tumors.

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AUTHORS

Jeanne Shen, Taebum Lee, Jun-Eul Hwang, Yoon-La Choi, Se-Hoon Lee, Hyojin Kim, Jin-haeng Chung, Stephanie Bogdan, Maggie Huang, Tyler Raclin, George A. Fisher Jr., Sergio Pereira, Seonwook Park, Minuk Ma, Donggeun Yoo, Seunghwan Shin, Kyunghyun Paeng, Chan-Young Ock, Tony S. Mok, Yung-Jue Bang

PUBLISHED
ASCO 2021

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