“Our goal is to provide a decision-making tool for the first-line treatment of advanced NSCLC patients based on plasma-derived biomarkers obtained before treatment initiation,” said Itamar Sela, Ph.D., VP R&D at OncoHost and lead author of the study. “Our PROphet® model continues to display strong performance, with a high correlation between the predicted clinical benefit and the observed clinical benefit rate, outperforming the current PD-L1-based prediction model. We’re excited to present this accurate alternative to improve the lives of patients.”
OncoHost to Present PROphet® Biomarker Model that Accurately Predicts Clinical Benefit to ICI-Based Treatment at ASCO 2023
OncoHost, a technology company transforming the approach to precision medicine for improved patient outcomes, today announced that it will give a poster presentation demonstrating the accuracy of its PROphet® biomarker model at the upcoming American Society of Clinical Oncology (ASCO) Annual Meeting, taking place June 2-6, 2023, in Chicago, Illinois.
Initial treatment selection for advanced non-small cell lung cancer (NSCLC) patients without driver mutations is primarily based on evaluating PD-L1 expression levels in the tumor tissue. However, PD-L1 assays are only moderately predictive. In addition, guidelines for the PD-L1 ≥50% subpopulation are not definitive, enabling the use of immune checkpoint inhibitors (ICIs) either as monotherapy, or combined with chemotherapy.
OncoHost’s proprietary platform, PROphet®, is a plasma-based, proteomic pattern analysis tool whose initial offering in NSCLC uses a single blood sample to guide first-line immunotherapy decision-making. The PROphet® algorithm is trained on OncoHost’s large-scale clinical trial, PROPHETIC. To date, the trial has over 1,700 patients recruited across 40 sites worldwide, making it one of the largest prospective cohorts in the precision oncology field.
“Our goal is to provide a decision-making tool for the first-line treatment of advanced NSCLC patients based on plasma-derived biomarkers obtained before treatment initiation,” said Itamar Sela, Ph.D., VP R&D at OncoHost and lead author of the study. “Our PROphet® model continues to display strong performance, with a high correlation between the predicted clinical benefit and the observed clinical benefit rate, outperforming the current PD-L1-based prediction model. We’re excited to present this accurate alternative to improve the lives of patients.”
The researchers examined the clinical utility of combining the PROphet® output with PD-L1 levels by comparing different treatment modalities and concluded that the model output complements tissue PD-L1 expression levels as a tool to assist therapeutic decisions. Essentially, plasma proteomic profiling can provide biomarkers that accurately predict the benefit of ICI-based treatment for advanced, unresectable cancer patients.
“Traditional precision medicine searches for biomarkers at the therapy-tumor axis. By adding the patient to the equation, we’re fighting cancer through a unique, deep profiling of the patient-tumor interface,” said Dr. Ofer Sharon, CEO of OncoHost. “Our ongoing research demonstrates the clear clinical utility of our PROphet® platform, offering targeted treatment options for patients and identifying previously unanticipated targets for future interventions and clinical trials. This is a crucial time for precision oncology.”
The clinical study was conducted in collaboration with Heidelberg University’s BioMaterialBank, Roswell Park Comprehensive Cancer Center, Thomas Jefferson University, Chaim Sheba Medical Center Institute of Oncology, UC Davis Comprehensive Cancer Center, OSUCCC – James – The Ohio State University, Asklepios Lung Clinic, Hadassah Cancer Research Center and Rambam Health Care Campus.
Poster Presentation Details
Session: Lung Cancer—Non-Small Cell Metastatic
Abstract #: 9122
Poster Bd #: 110
Title: A decision-making tool for first-line treatment in advanced non–small-cell lung cancer based on plasma proteome biomarkers.
Presenter: Itamar Sela, Ph.D., VP R&D at OncoHost
Date/Time: Tuesday, June 4, 2023, 8:00 AM-11:00 AM
The abstract is available on the ASCO website here.