Upregulation of <i>FHL1</i>, <i>SPNS3</i>, and <i>MPZL2</i> predicts poor prognosis in pediatric acute myeloid leukemia patients with <i>FLT3-ITD</i> mutation

Abstract

Chromosomal translocations and gene mutations are characteristics of the genomic profile of acute myeloid leukemia (AML). We aim to identify a gene signature associated with poor prognosis in AML patients with <i>FLT3-ITD</i> compared to AML patients with <i>NPM1/CEBPA</i> mutations. RNA-sequencing (RNA-Seq) count data were downloaded from the UCSC Xena browser. Samples were grouped by their mutation status into high and low-risk groups. Differential gene expression (DGE), machine learning (ML) and survival analyses were performed. A total of 471 differentially expressed genes (DEGs) were identified, of which 16 DEGs were used as features for the prediction of mutation status. An accuracy of 92% was obtained from the ML model. <i>FHL1</i>, <i>SPNS3</i>, and <i>MPZL2</i> were found to be associated with overall survival in <i>FLT3-ITD</i> samples. <i>FLT3-ITD</i> mutation confers an indicative gene expression profile different from <i>NPM1/CEBPA</i> mutation, and the expression of <i>FHL1</i>, <i>SPSN3</i>, and <i>MPZL2</i> can serve as prognostic indicators of unfavorable disease.