Ontology highlight
ABSTRACT: Background
Identifying reliable predictive markers is important to make therapeutic decisions, and determine the prognosis for acute myeloid leukemia (AML) patients. However, approximately 50% patients could not be accurately predicted by existing risk factors. It is necessary to identify novel prognostic factors to subdivide the intermediate-risk group or patients without any cytogenetic and molecular abnormalities.Methods
Kaplan-Meier and Cox regression were used for survival analyses in three independent AML datasets. Analyses integrating both bioinformatics and ChIP-qPCR experiments were performed to explore the role of CEBPE in regulating the expression of known prognostic factors.Results
CEBPE expression was an independent predictor for both overall survival (
SUBMITTER: Li K
PROVIDER: S-EPMC6549322 | biostudies-literature | 2019 Jun
REPOSITORIES: biostudies-literature