PROTEINA Co., Ltd., in partnership with Seoul National University (SNU) and Seoul National University Hospital (SNUH), has announced groundbreaking research published in Nature Biomedical Engineering. The study introduces a novel method for personalizing treatment for acute myeloid leukemia (AML) patients by utilizing protein-protein interaction (PPI) profiling to predict drug response.
Critical Need for Personalized AML Treatment
For AML patients, achieving complete remission during initial treatment is crucial, yet nearly 90% do not survive without it. ABT-199, combined with hypomethylating agents, has shown promise by targeting the BCL2 protein, a key factor in cancer progression. However, patient selection is challenging due to varying dependencies on BCL2 signaling.
Innovative PPI Profiling Technique
The research team from PROTEINA, SNU, and SNUH developed the single-molecule pull-down and co-immunoprecipitation (SMPC) technique. This method measures over 20 different PPIs and protein expression levels from clinical specimens, using just 1 ml of body fluid such as blood or bone marrow aspirate.
The SMPC technique identifies key PPI links essential for leukemia cell survival under ABT-199 treatment. The resulting prediction model, with an AUROC value of 0.94, accurately identifies patients likely to respond to ABT-199 therapy.
Key Findings and Clinical Implications
The study highlights the BCL2-BAX complex’s role in AML cell survival under ABT-199-induced apoptotic stress, while the BCLxL-BAK complex is associated with resistance. This discovery underscores the drug’s selective action.
The PPI profiling of samples from 32 AML patients identified significant PPIs correlating with drug responsiveness. The developed biomarker predicted drug response with 100% sensitivity and 83.3% specificity in 9 out of 10 patients.
Future Directions and Clinical Validation
PROTEINA has acquired venetoclax response prediction technology and patents from SNU and SNUH. The company is now collaborating with Professor Janghee Woo of Emory University School of Medicine for global clinical validation. “We are excited to embark on this large-scale clinical validation, a crucial step in expanding our platform technology’s role in precision medicine,” said Hongwon Lee, Chief Technology Officer at PROTEINA.
Support and Acknowledgements
This research was funded by the National Research Foundation of South Korea (NRF) [grant number NRF-2021R1A3B1071354], the Bio Medical Technology Development Program of the NRF [grant number NRF-2018M3A9E2023523], and the Korea Health Technology R&D Project of the Korea Health Industry Development Institute (KHIDI) [grant number HI14C1277].
