OncoHost to Present Data at SITC 2021 on Predicting NSCLC Patient Response to Immunotherapy Utilizing Proteomic Profiling
BINYAMINA, Israel, Nov. 12, 2021 /PRNewswire/ — OncoHost, a global leader in next-generation precision oncology for improved personalized cancer therapy, has published a study identifying three distinct proteome subtypes that are associated with response from a cohort of non-small cell lung cancer (NSCLC) patients undergoing immunotherapy. The study was conducted using OncoHost’s first-of-its-kind, AI-based platform, PROphet®, and its research and findings will be presented as an oral presentation at the Society for Immunotherapy of Cancer’s (SITC) 36th Anniversary Annual Meeting.
Although the approval of immune checkpoint inhibitor (ICI)-based therapy has improved lung cancer outcomes, most patients still do not respond to treatment. Moreover, a growing body of evidence demonstrates that in some cases, the interplay between the treatment, tumor and host can lead to a counterintuitive effect, supporting tumor progression and spread. Understanding the biological processes that drive resistance to treatment is critical in order to improve clinical outcomes. This study seeks to take a deeper look into the host’s micro-environment to identify biomarkers for response to immunotherapy, as well as to gain insights into mechanisms of resistance to treatment and understand the resistance biology.
“By conducting plasma proteomic profiling and assessing multidimensional clinical and biological data, we have achieved success in analyzing, clustering and predicting response in NSCLC patients,” said Professor Yuval Shaked, founder and Chief Scientific Advisor at OncoHost, and Professor of Cell Biology and Cancer Science at the Technion – Israel Institute of Technology. “This research is helping us take significant strides in understanding the biological processes that are driving resistance in patients, and we are honored to play a role in the evolution of cancer care.”
The study included a cohort comprised of 143 patients from whom plasma samples were collected pre-treatment and in the early stages of treatment, along with comprehensive clinical data. Using PROphet®, OncoHost’s advanced machine learning and bioinformatics platform, researchers divided the cohort into three patient clusters, each with distinct biological and clinical characteristics. While the patients in all three clusters may have had the same diagnosis, they all fit into just one of three proteome subtypes, which are associated with their treatment responsiveness.
“Painting a distinct proteome picture, this study has shown us that PROphet® can predict response and analyze resistance for every patient, sub-grouping and differentiating them based on their resistance assessment,” said Ofer Sharon, CEO of OncoHost. “In order to provide oncologists and patients with tangible, actionable clinical insights, it’s not enough to predict which patients will be more responsive to treatment; we should also understand the reason behind it. PROphet® has allowed us to reach this deep level of resolution and insight.”
The clinical study was conducted in collaboration with Sidney Kimmel Medical College at Thomas Jefferson University, The Ohio State University Wexner Medical Center, Sheba Medical Center, the Technion Institute of Technology and Tel Aviv University. The presentation will take place at SITC on November 12, 2021, at 13:03 EST. This study will be published as a full peer-reviewed manuscript in 2022.
OncoHost combines life-science research and advanced machine learning technology to develop personalized strategies to maximize the success of cancer therapy. Utilizing proprietary proteomic analysis, the company aims to understand patients’ unique response to therapy and overcome one of the major obstacles in clinical oncology today – resistance to therapy. OncoHost’s host response profiling platform, PROphet®, analyzes proteomic changes in blood samples to monitor the dynamics of biological processes induced by the patient (i.e., the host) in response to a given cancer therapy. This proteomic profile is highly predictive of individual patient outcome, thus enabling personalized treatment planning. PROphet® also identifies potential drug targets, advancing the development of novel therapeutic strategies as well as rationally based combination therapies.
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