by Ben-Gurion University of the Negev

IcAR response to fresh and fixed PDXs and generation of an IcAR score.(A) Schematic representation of the IcAR assay protocol. Following flow cytometry determination of surface expression levels of PDL1 and PDL2 and coexpression of PDL1 and PDL2 (double) in fresh PDXs (extracted from mice), the IcAR functional assay was performed on both unblocked ligands and ligands blocked using anti-PDL1, anti-PDL2, and anti-PD1 antibodies. (B) PDL1 and PDL2 levels were determined in five PDXs, and the assay results are presented as percent of surface expression of each ligand and of coexpression (double). (C) Coculture with IcAR-PD1 cells was performed for each PDX using anti-PD1 (pembrolizumab), anti-PDL1 (durvalumab), and anti-PDL2 antibodies; results are displayed as percent of response to each ligand out of the total IcAR response (unblocked). (D) Coculture with IcAR-PD1 cells was performed for each FFPE tissue sample using anti-PD1, anti-PDL1, and anti-PDL2 antibodies; results are displayed as percent of response to each ligand out of the total IcAR response (unblocked). (E) Correlation between IcAR response (namely, IL-2 levels) from fresh and fixed PDXs (n = 5). (F) Example of surface coverage of a well, measured with a JuLI Stage cell recorder, to produce normalized response per surface area. (G) Different PDXs give different scores, depending on the functionality of binding of each ligand (**P < 0.01 and ****P < 0.001). n.s., not significant. Credit: Science Advances (2023). DOI: 10.1126/sciadv.adg2809

A team of researchers from Ben-Gurion University of the Negev (BGU) has developed a groundbreaking bio-sensing technology that predicts the response of cancer patients to anti-PD1, an immune checkpoint inhibitor (ICI) therapy, with significantly greater accuracy than current methods.

The study's results were published late last week in Science Advances.

The study was led by Bar Kaufman, a talented MD-Ph.D. student, and Master's student Orli Abramov, under the guidance of Prof. Moshe Elkabets and Prof. Angel Porgador from the Faculty of Health Sciences at BGU, along with collaborators from Soroka Medical Center and Barzilai Hospital.

This bio-sensing technology, called the Immuno-checkpoint Artificial Reporter with overexpression of PD1 (IcAR-PD1), measures the binding functionality of PD1 ligands, PDL1 and PDL2, to their receptor PD1.

The researchers found that assessing the functionality of PD1 ligands was an effective predictor to identify who will positively respond to anti-PD1 and will benefit from this treatment. The anti-PD1 is the leading immunotherapy (ICI) treatment in cancer patients, thus such achievement can impact the quality of life of thousands of cancer patients worldwide every day.

The IcAR technology is a groundbreaking development that enables the measurement of the functionality, in principle, of any immuno-modulator targets in medical oncology. What that means is that doctors can now use the IcAR-PD1 technology to predict which patients will respond best to anti-PD1 therapies and tailor treatments accordingly, while sparing non-responders from ineffective treatment. In the future, this bioassay technology may help predict responses to other ICI therapies and could be used to tailor personalized ICI treatment protocols.

The major advances of the IcAR technology are the accuracy and sensitivity along with its logistical simplicity. The technology enables the screening of substantial amounts of cancer samples without requiring fresh biopsies or biological material, making it accessible for medical care in Israel and abroad. By solving the logistical bottleneck, the researchers make the diagnostic tool easier for doctors to identify potential responders.

Prof. Porgador emphasized that this diagnostic test does not require additional biopsy as it is based on the fixed tumor tissue available for cancer patients directly from the pathology unit of their medical center.

"In summary, IcAR technology is expected to be a game-changer in the world of cancer treatment diagnostics," said Prof. Elkabets, "It will enable accurate prediction of patient response to ICI therapies, and it has the potential to improve the lives of cancer patients by identifying effective treatment options in a personalized manner."

More information: Bar Kaufman et al, Functional binding of PD1 ligands predicts response to anti-PD1 treatment in patients with cancer, Science Advances (2023). DOI: 10.1126/sciadv.adg2809

Journal information: Science Advances 

Provided by Ben-Gurion University of the Negev