Accuracy of 94% Development of Biomarkers Predicting Treatment of Acute Myeloid Leukemia
Aug 06, 2024
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Professor Ko Young-il and Byeon Jae-min of the Department of Hematologic Oncology at Seoul National University Hospital, Professor Yoon Tae-young of the Department of Life Sciences at Seoul National University (SNU) (researcher Jeon Chang-joo), and a collaborative research team at Protina announced that they have developed a high-performance companion diagnostic biomarker that can predict the therapeutic effect of ABT-199 target anticancer drugs by analyzing the interaction between BCL2 protein and other proteins through single-molecule cointegration (SMPC) technology.
Acute myeloid leukemia (AML) is a type of blood cancer in which abnormal white blood cells in the blood or bone marrow rapidly proliferate and interfere with the production of normal blood cells, and the choice of quick and effective treatment is very important. BH3 metabolites are drugs that target BCL2 proteins and induce the death of cancer cells, especially 'ABT-199(Venetoclax)' target anticancer drugs have shown high performance in AML treatment.
However, not all patients achieved the same therapeutic effect, and there were cases where resistance developed after temporary remission, so a method to predict the effect of ABT-199 was needed in advance.
The research team developed a technology to quantitatively detect 22 different protein-protein interaction (PPI) signals by analyzing about 30,000 cells through single-molecule pull-down and co-immunoprecipitation techniques and single-molecule fluorescence imaging techniques. Through this, it is possible to accurately measure how various proteins interact with each other.
The research team confirmed that ABT-199 selectively binds to the BCL2 protein to degrade the BCL2-BAX complex, and that the activated BAX protein induces the death of cancer cells in this process. This clarified the main mechanism by which ABT-199 kills cancer cells.
The research team then obtained multidimensional PPI profile data from 32 AML patient samples and analyzed the correlation between drug responsiveness at an in vitro level. As a result, we have revealed a major protein complex that affects the sensitivity (how well it listens) and resistance (how well it resists) of ABT-199. In particular, the BCL2-BAX complex was found to be associated with the sensitivity of ABT-199 and the BCLxL-BAK complex with resistance.
Based on this data, the research team developed a 'high-performance companion diagnostic biomarker' that can predict ABT-199 drug responsiveness in individual AML patients. This biomarker can see how certain PPI signals change in the patient's cells and predict with high accuracy whether ABT-199 will work.
The research team tested the prediction accuracy of the developed biomarker at an in vitro level. As a result, the prediction accuracy (AUC-ROC) was up to 94%, which is sufficient for clinical applications. In fact, a clinical trial of 10 AML patients also successfully predicted the reactivity of 9 anticancer drugs, with 100% sensitivity and 83.3% specificity. It was confirmed that the patient's anticancer drug reactivity could be predicted with high accuracy.
Professor Yoon Tae-young (Department of Life Sciences) of Seoul National University said "The monomolecular cointegration (SMPC) technique is a tool that can accurately measure protein-protein interactions (PPIs) in various samples" It is expected that this technology will pave a new way for molecular diagnosis by understanding complex protein interaction networks"
Professor Ko Young-il (blood oncology) at Seoul National University Hospital said, "This study is a meaningful achievement that highlights the importance of ABT-199 (Venetoclax) therapy in acute myeloid leukemia, which previously lacked response prediction biomarkers. "This study based on PPI profiling will greatly contribute to the development of precision medical care for acute myeloid leukemia in the future."
The results of this study are a world-class academic journal 'Nature Bio'Nature Biomedical Engineering (IF: 29.2)' was published in the latest issue.
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