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Get Free AccessAbstract The ability to identify a specific type of leukemia using minimally invasive biopsies holds great promise to improve the diagnosis, treatment selection, and prognosis prediction of patients. Using genome-wide methylation profiling and machine learning methods, we investigated the utility of CpG methylation status to differentiate blood from patients with acute lymphocytic leukemia (ALL) or acute myelogenous leukemia (AML) from normal blood. We established a CpG methylation panel that can distinguish ALL and AML blood from normal blood as well as ALL blood from AML blood with high sensitivity and specificity. We then developed a methylation-based survival classifier with 23 CpGs for ALL and 20 CpGs for AML that could successfully divide patients into high-risk and low-risk groups, with significant differences in clinical outcome in each leukemia type. Together, these findings demonstrate that methylation profiles can be highly sensitive and specific in the accurate diagnosis of ALL and AML, with implications for the prediction of prognosis and treatment selection.
Hua Jiang, Zhiying Ou, Yingyi He, Meixing Yu, Shaoqing Wu, Gen Li, Jie Zhu, Ru Zhang, Jiayi Wang, Lianghong Zheng, Xiaohong Zhang, Wen-Ge Hao, Liya He, Xiaoqiong Gu, Qingli Quan, Edward Zhang, Hui Luo, Wei Wei, Zhihuan Li, Guangxi Zang, Charlotte Zhang, Tina Poon, Daniel Zhang, Ian Ziyar, Run-ze Zhang, Oulan Li, Linhai Cheng, T Shimizu, Xinping Cui, Jian Kang Zhu, Xin Sun, Kang Zhang (2020). DNA methylation markers in the diagnosis and prognosis of common leukemias. , 5(1), DOI: https://doi.org/10.1038/s41392-019-0090-5.
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Type
Article
Year
2020
Authors
32
Datasets
0
Total Files
0
Language
en
DOI
https://doi.org/10.1038/s41392-019-0090-5
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