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

Bar Kaufman; Orli Abramov; Anna Ievko; Daria Apple; Mark Shlapobersky; Irit Allon; Yariv Greenshpan; Baisali Bhattachrya; Ofir Cohen; Tatiana Charkovsky; Alexandra Gayster; Ruthy Shaco-Levy; Keren Rouvinov; Alejandro Livoff; Moshe Elkabets; Angel Porgador

doi:10.1126/sciadv.adg2809

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

Bar Kaufman, Orli Abramov, Anna Ievko, Daria Apple, Mark Shlapobersky, Irit Allon, Yariv Greenshpan, Baisali Bhattachrya, Ofir Cohen, Tatiana Charkovsky, Alexandra Gayster, Ruthy Shaco-Levy, Keren Rouvinov, Alejandro Livoff, Moshe Elkabets, Angel Porgador

Research output: Contribution to journal › Article › peer-review

2 Scopus citations

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.

Original language	English
Article number	eadg2809
Journal	Science advances
Volume	9
Issue number	21
DOIs	https://doi.org/10.1126/sciadv.adg2809
State	Published - May 2023
Externally published	Yes

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Publisher Copyright:
© 2023 The Authors.

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Kaufman, B., Abramov, O., Ievko, A., Apple, D., Shlapobersky, M., Allon, I., Greenshpan, Y., Bhattachrya, B., Cohen, O., Charkovsky, T., Gayster, A., Shaco-Levy, R., Rouvinov, K., Livoff, A., Elkabets, M., & Porgador, A. (2023). Functional binding of PD1 ligands predicts response to anti-PD1 treatment in patients with cancer. Science advances, 9(21), Article eadg2809. https://doi.org/10.1126/sciadv.adg2809

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title = "Functional binding of PD1 ligands predicts response to anti-PD1 treatment in patients with cancer",

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.",

author = "Bar Kaufman and Orli Abramov and Anna Ievko and Daria Apple and Mark Shlapobersky and Irit Allon and Yariv Greenshpan and Baisali Bhattachrya and Ofir Cohen and Tatiana Charkovsky and Alexandra Gayster and Ruthy Shaco-Levy and Keren Rouvinov and Alejandro Livoff and Moshe Elkabets and Angel Porgador",

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Kaufman, B, Abramov, O, Ievko, A, Apple, D, Shlapobersky, M, Allon, I, Greenshpan, Y, Bhattachrya, B, Cohen, O, Charkovsky, T, Gayster, A, Shaco-Levy, R, Rouvinov, K, Livoff, A, Elkabets, M & Porgador, A 2023, 'Functional binding of PD1 ligands predicts response to anti-PD1 treatment in patients with cancer', Science advances, vol. 9, no. 21, eadg2809. https://doi.org/10.1126/sciadv.adg2809

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AU - Kaufman, Bar

AU - Abramov, Orli

AU - Ievko, Anna

AU - Apple, Daria

AU - Shlapobersky, Mark

AU - Allon, Irit

AU - Greenshpan, Yariv

AU - Bhattachrya, Baisali

AU - Cohen, Ofir

AU - Charkovsky, Tatiana

AU - Gayster, Alexandra

AU - Shaco-Levy, Ruthy

AU - Rouvinov, Keren

AU - Livoff, Alejandro

AU - Elkabets, Moshe

AU - Porgador, Angel

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

Abstract

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