Early prediction of recurrence risk in breast cancer patients with blood...Expect personalized response improvements
Jul 07, 2025
Domestic researchers have developed a diagnostic method that can predict breast cancer recurrence early with blood.
This technology is expected to contribute significantly to precision medical care and patient prognosis management in the future as it is applicable to patients who are difficult to treat and predict prognosis.
A research team led by Dr. Jung Young-ho and Hyun Joo-yong from the Digital Omics Research Department of the Korea Institute of Basic Science (Director Yang Sung-kwang, hereinafter referred to as KBSI) developed a new technology that can predict the recurrence of triple negative breast cancer early with a blood-based non-invasive diagnosis method with a joint research team consisting of Professor Kim Seung-il and Dr. Kim Min-woo from Yonsei University Medical School, Professor Kim Hyo-il from the Department of Mechanical Engineering and Professor Hyun Kyung-ah from Sungshin Women's University.
This study analyzed in-depth the proteins of tumor-derived extracorporealves (tdEVs) extracted from the blood of breast cancer patients, proving that four specific proteins (ECM1, MBL2, BTD, and RAB5C) are strong biomarker candidates for recurrence and prognosis of triple negative breast cancer.
Triple negative breast cancer is a type that does not have all three receptors on which target anticancer drugs work, and prognosis prediction is particularly important because the risk of metastasis and recurrence is higher than other types of breast cancer.
To overcome the limitations of the existing diagnostic method, the research team developed its own microfluidic chip-based exosome separation technology and used machine learning-based algorithms to maximize diagnostic performance. As a result, high diagnostic performance of 90% sensitivity and 95% specificity was secured in the triple negative breast cancer patient group.
In addition, the research team achieved a very high diagnostic performance indicator of AUC 0.986 in the diagnosis of triple negative breast cancer using the 'tdEV protein score' consisting of ECM1, MBL2, BTD, and RAB5C proteins.
The protein combination also showed a significant correlation in predicting recurrence risk and analyzing survival rates, demonstrating its potential for use in evaluating patient prognosis. The results of tissue immunostaining analysis also confirmed the same expression pattern as blood-based analysis, confirming the potential of this study's tdEV-based liquid biopsy diagnosis as a non-invasive and reliable cancer diagnosis and monitoring tool.
In addition, a similar level of high performance was shown in cross-validation through ELISA methods commonly used in general hospitals, increasing the possibility of application in actual clinical settings in the future.
KBSI Dr. Young-ho Jeong, who led the study, emphasized that "this study is an important case that suggests that protein-based liquid biopsy can be used for actual clinical diagnosis" and that "it will be possible to predict recurrence early in a non-invasive way, especially in patients with triple-negative breast cancer who are at high risk of recurrence after treatment, and this will enable a customized proactive response based on precision medicine."
The research was carried out with the support of the Korea Institute of Basic Science and Support's multi-omics big data convergence platform construction project, the Ministry of Science and ICT and the Korea Research Foundation support project for mid-sized researchers, the Sejong Science Fellowship project, the next-generation promising SEED technology commercialization fast-track project, and the Severance Hospital Clinical Excellence Research Fund project.
This technology is expected to contribute significantly to precision medical care and patient prognosis management in the future as it is applicable to patients who are difficult to treat and predict prognosis.
A research team led by Dr. Jung Young-ho and Hyun Joo-yong from the Digital Omics Research Department of the Korea Institute of Basic Science (Director Yang Sung-kwang, hereinafter referred to as KBSI) developed a new technology that can predict the recurrence of triple negative breast cancer early with a blood-based non-invasive diagnosis method with a joint research team consisting of Professor Kim Seung-il and Dr. Kim Min-woo from Yonsei University Medical School, Professor Kim Hyo-il from the Department of Mechanical Engineering and Professor Hyun Kyung-ah from Sungshin Women's University.
This study analyzed in-depth the proteins of tumor-derived extracorporealves (tdEVs) extracted from the blood of breast cancer patients, proving that four specific proteins (ECM1, MBL2, BTD, and RAB5C) are strong biomarker candidates for recurrence and prognosis of triple negative breast cancer.
Triple negative breast cancer is a type that does not have all three receptors on which target anticancer drugs work, and prognosis prediction is particularly important because the risk of metastasis and recurrence is higher than other types of breast cancer.
To overcome the limitations of the existing diagnostic method, the research team developed its own microfluidic chip-based exosome separation technology and used machine learning-based algorithms to maximize diagnostic performance. As a result, high diagnostic performance of 90% sensitivity and 95% specificity was secured in the triple negative breast cancer patient group.
In addition, the research team achieved a very high diagnostic performance indicator of AUC 0.986 in the diagnosis of triple negative breast cancer using the 'tdEV protein score' consisting of ECM1, MBL2, BTD, and RAB5C proteins.
The protein combination also showed a significant correlation in predicting recurrence risk and analyzing survival rates, demonstrating its potential for use in evaluating patient prognosis. The results of tissue immunostaining analysis also confirmed the same expression pattern as blood-based analysis, confirming the potential of this study's tdEV-based liquid biopsy diagnosis as a non-invasive and reliable cancer diagnosis and monitoring tool.
In addition, a similar level of high performance was shown in cross-validation through ELISA methods commonly used in general hospitals, increasing the possibility of application in actual clinical settings in the future.
KBSI Dr. Young-ho Jeong, who led the study, emphasized that "this study is an important case that suggests that protein-based liquid biopsy can be used for actual clinical diagnosis" and that "it will be possible to predict recurrence early in a non-invasive way, especially in patients with triple-negative breast cancer who are at high risk of recurrence after treatment, and this will enable a customized proactive response based on precision medicine."
The research was carried out with the support of the Korea Institute of Basic Science and Support's multi-omics big data convergence platform construction project, the Ministry of Science and ICT and the Korea Research Foundation support project for mid-sized researchers, the Sejong Science Fellowship project, the next-generation promising SEED technology commercialization fast-track project, and the Severance Hospital Clinical Excellence Research Fund project.
|
This article was translated by Naver AI translator.
