Abstract
Children with acute myeloid leukemia (AML) face a relapse of the disease in 30% of all cases. AML relapse is difficult to predict, and existing risk scales are often ineffective. Using data from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET-AML) project, we defined an expression signature based on matrix RNAs (mRNAs) and long non-coding RNAs (lncRNAs) that could predict relapse in pediatric AML patients.We used a comprehensive bioinformatics analysis that included the identification of functionally significant differentially expressed genes in AML relapse, several rounds of association with relapse-free survival (RFS) mRNAs and lncRNAs selection, and evaluation of the obtained expression signatures to predict recurrence at the primary tumor level.Two mRNAs (ENSG00000149289.11 (ZC3H12C) and ENSG00000075213.11 (SEMA3A)) and one lncRNA (ENSG00000287569.1) were associated with a decreased RFS. Models including changes in the expression of ZC3H12C and ENSG00000287569.1, as well as all three markers, demonstrated very good quality and could predict the recurrence of pediatric AML.
Published Version
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