Science Advances · 2023 · 40 citations · 30 references
MedicineImmunologyOncologyCancer ImmunologyImmunotherapyMolecular OncologyCancer BiomarkersCancer ImmunotherapyCheckpoint Inhibitor TherapyImmune Checkpoint InhibitorsImmune CheckpointsImmuno-oncology BiomarkersCheckpoint Inhibitor Response PredictionImmune Checkpoint BiomarkersImmune Checkpoint Inhibitor BiomarkersImmune Checkpoint Inhibitor ResponseImmune Checkpoint LigandsLigand Binding AffinityPredictive Biomarker DiscoveryProgrammed Death-ligand 1 Biomarker
Accurate predictive biomarkers of response to immune checkpoint inhibitors (ICIs) are required for better stratifying patients with cancer to ICI treatments. Here, we present a new concept for a bioassay to predict the response to anti-PD1 therapies, which is based on measuring the binding functionality of PDL1 and PDL2 to their receptor, PD1. In detail, we developed a cell-based reporting system, called the immuno-checkpoint artificial reporter with overexpression of PD1 (IcAR-PD1) and evaluated the functionality of PDL1 and PDL2 binding in tumor cell lines, patient-derived xenografts, and fixed-tissue tumor samples obtained from patients with cancer. In a retrospective clinical study, we found that the functionality of PDL1 and PDL2 predicts response to anti-PD1 and that the functionality of PDL1 binding is a more effective predictor than PDL1 protein expression alone. Our findings suggest that assessing the functionality of ligand binding is superior to staining of protein expression for predicting response to ICIs.
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Tumor mutational load predicts survival after immunotherapy across multiple cancer types
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Medicine, Cancer Biology, Oncology +14
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