New research combining AI and multi-omics analysis to understand cancer resistance mechanisms

two prestigious research institutes, Baylor Scott and White Health and the Translational Genomics Institute (TGen), in collaboration with an Israeli start-up, today announced a new research study aimed at analyzing cancer resistance mechanisms using multiple multi-omics techniques. Oncohost.

Baylor Scott and White Health is Texas’s largest nonprofit healthcare system, serving more than 3 million Texans at 51 hospitals and over 1,100 access points. The Translational Genomics Research Institute (TGen) is a non-profit organization based in Phoenix, Arizona, dedicated to conducting groundbreaking research with life-changing results. TGen is part of City of Hope, a world-renowned independent research and treatment center for cancer, diabetes and other life-threatening diseases.

OncoHost is Precision Oncology Platformis a unique plasma-based proteomic analysis tool to guide decision-making in first-line treatment selection for cancer patients, analyze resistance mechanisms, and suggest potential therapeutic combinations to overcome this resistance. .

“It’s detective work,” Dr. Michal Harel, OncoHost’s director of science and innovation, recently told me. “There’s a lot of hidden stuff in the data. You see trends, you get hints, and this is probably generalizable and statistically significant. Then the theory and biology behind it. We’ll try to understand what it is and see if it has clinical relevance.”

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Recent results from ongoing trials of OncoHost’s platform accurately predict potential clinical benefit at 12 months based on a single, simple pre-treatment blood test, compared to existing PD-L1 biologics. It shows that it outperforms the predictive power of the marker. The platform also identifies and highlights individualized drug combinations to mitigate aggressive resistance mechanisms to overcome therapeutic resistance. OncoHost’s PROphet® platform is expected to launch in the US in the first quarter of 2023.

Last November, Harel Society for Immunotherapy of Cancer’s (SITC) 37th Annual Meeting A novel predictive model for clinical benefit of immunotherapy in patients with non-small cell lung cancer (NSCLC) that is superior to PD-L1-based predictive models.

By combining machine learning and proteomic analysis, OncoHost’s platform offers two clinical benefits, Harel says. It is a good predictor of clinical benefit at 12 months and in combination with the PD-L1 test serves as a dosing or not-dosing decision-making tool for physicians. Immunotherapy alone or in combination with chemotherapy has a significant impact on overall survival.

The new multi-year study will utilize Baylor Scott & White’s Texas Immuno-Oncology Biorepository (TIOB). TIOB collects, catalogs and preserves samples of biological materials for cancer research. Analysis, Ct-DNA, and microbiome analysis combined with bioinformatics and machine learning tools.

A comprehensive analysis is performed for lung cancer patients at various stages of the disease, analyzing factors such as host response, patient microbiome, tumor DNA, and immune system activity. The tests look at the patient’s urine, blood, stool, tissues, cells, DNA, RNA, and protein. The study will include approximately 350 patients with up to 5 years of follow-up.

In a statement, the principal investigator of the study, WW Karus Jr., director of oncology at the Baylor Scott and White Charles A. Summons Cancer Center and immunology at Baylor University Medical Center Dallas, said: The Chair, Dr. Ronan Kelly, explained the approach. “A very comprehensive profiling his process, one of the most comprehensive he’s ever had for a cancer patient.” Professor Michael Berens, Head of Cancer and Cell Biology at TGen, pointed out that “collaborations like this can take us to a higher level in the fight against cancer.” OncoHost CEO Dr. Ofer Sharon said:

“For years, precision medicine has focused on tumors and treatments. We see tumor, treatment and patient as one. Harel says.