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Functional binding of PD1 ligands predicts response to anti-PD1 treatment in cancer patients

Authors :
Bar Kaufman
Orli Abramov
Anna Yevko
Daria Apple
Mark Shlapobersky
Yariv Greenshpan
Ruthy Shaco-Levy
Keren Roubinov
Alejandro Liboff
Moshe Elkabets
Angel Porgador
Publication Year :
2023
Publisher :
Cold Spring Harbor Laboratory, 2023.

Abstract

Accurate predictive biomarkers of response to immune checkpoint inhibitors (ICIs) are required for better stratifying cancer patients 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 PDL1 and PDL2 binding functionality in tumor cell lines, patient-derived xenografts, and in fixed-tissue tumor samples obtained from cancer patients. In a retrospective clinical study, we found that the functionality of PDL1 and PDL2 predicts response to anti-PD1, and 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.TeaserPositive clinical response of cancer patients to anti-PD1 therapy can be predicted by measuring the binding activity of PDL1 and PDL2.

Details

Database :
OpenAIRE
Accession number :
edsair.doi...........9ff1211146631540556dc67d154f48cb
Full Text :
https://doi.org/10.1101/2023.02.09.527671