ArticleScience advances2023
Functional binding of PD1 ligands predicts response to anti-PD1 treatment in patients with cancer.
Article in Science advances, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 38 citations in OpenAlex.
- Cancer therapy-induced ototoxicity: Current challenges and emerging management strategies.Animal models and experimental medicine · 2026Review
- Clinical significance and functional characterization of RRN3 in gastric cancer: insights from pan-cancer analysis and experimental validation.Frontiers in oncology · 2026Article
- PABPC1 expression in papillary renal cell carcinoma and its significance for survival outcomes.Journal, genetic engineering & biotechnology · 2025Article
- Synthetic signaling platform uncovers and rewires cellular responses to PD-1 perturbation.bioRxiv : the preprint server for biology · 2025Article
- N-glycosylation of PD-L1 modulates the efficacy of immune checkpoint blockades targeting PD-L1 and PD-1.Molecular cancer · 2025Article
- Worldwide Innovative Network (WIN) Consortium in Personalized Cancer Medicine: Bringing next-generation precision oncology to patients.Oncotarget · 2025Article
- A Comprehensive Pan-cancer Analysis Identified that TRIB3 was Associated with Immune Cell Infiltration and Poor Prognosis.Current pharmaceutical biotechnology · 2025Article
- PD1 ligand functionality a biomarker of response to anti PD1 treatment in patients with HNSCC.NPJ precision oncology · 2024Article
- A novel pan-PI3K inhibitor KTC1101 synergizes with anti-PD-1 therapy by targeting tumor suppression and immune activation.Molecular cancer · 2024Article
Corrections and comments
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Authors and funding
16 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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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