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Distinct genomic landscape of Chinese pediatric acute myeloid leukemia impacts clinical risk classification
Distinct genomic landscape of Chinese pediatric acute myeloid leukemia impacts clinical risk classification
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Distinct genomic landscape of Chinese pediatric acute myeloid leukemia impacts clinical risk classification
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Distinct genomic landscape of Chinese pediatric acute myeloid leukemia impacts clinical risk classification
Distinct genomic landscape of Chinese pediatric acute myeloid leukemia impacts clinical risk classification
Journal Article

Distinct genomic landscape of Chinese pediatric acute myeloid leukemia impacts clinical risk classification

2022
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Overview
Studies have revealed key genomic aberrations in pediatric acute myeloid leukemia (AML) based on Western populations. It is unknown to what extent the current genomic findings represent populations with different ethnic backgrounds. Here we present the genomic landscape of driver alterations of Chinese pediatric AML and discover previously undescribed genomic aberrations, including the XPO1 - TNRC18 fusion. Comprehensively comparing between the Chinese and Western AML cohorts reveal a substantially distinct genomic alteration profile. For example, Chinese AML patients more commonly exhibit mutations in KIT and CSF3R , and less frequently mutated of genes in the RAS signaling pathway. These differences in mutation frequencies lead to the detection of previously uncharacterized co-occurring mutation pairs. Importantly, the distinct driver profile is clinical relevant. We propose a refined prognosis risk classification model which better reflected the adverse event risk for Chinese AML patients. These results emphasize the importance of genetic background in precision medicine. The genomic landscape of pediatric acute myeloid leukemia (AML) has mostly been characterised for Western populations. Here, the authors identify potential driver alterations in Chinese pediatric AML, which differ from Western populations, and propose a prognostic risk classification model.