Bioinformatics Analysis of Differentially Expressed Genes and Their Functional Enrichment in Acute Myeloid Leukemia Bearing MLL Translocation

Abstract

Background: Chromosomal translocations of the mixed-lineage leukemia gene (MLL; tMLL) correlate with resistance to therapy and an extremely poor prognosis for individuals with Acute Myeloid Leukemia (AML). The underlying mechanisms are still unknown. This study aims to identify the key genes and the potential molecular mechanisms involved in MLL rearrangement in AML using a bioinformatics approach. Methods:The gene expression profiles from 15 individuals with partial tandem duplication of the MLL gene (MLL-PTD)-AML and 10 tMLL-AML samples were downloaded from the Gene Expression Omnibus (GEO) database. The Differentially Expressed Genes (DEGs) were selected and functional enrichment analyses were performed. The Protein-Protein Interaction (PPI) network was established and visualized in Cytoscape. The hub genes were identified by CytoHubba and significant modules were screened out by Molecular Complex Detection (MCODE). Results:We categorized a total of 885 DEGs comprising 330 upregulated and 555 downregulated genes. The majority of DEGs were significantly enriched for calcium ion transmembrane transport, embryonic skeletal system morphogenesis and cell proliferation processes. Several pathways were enriched, including those associated with PI3K-Akt signaling and insulin resistance. We identified 32 hub genes and screened out 2 modules. Conclusion:The genes we have identified in this study may represent potential biomarkers for MLL-rearranged AML and contribute to the development of novel therapeutic strategies.

Differential gene expression and co-regulated expression of genes in leukemia: an in-silico approach to identify potent biomarker

“…They analyzed the transcriptional profiling of human T-cell involved in the AML disease and reported CD4, NA, ADTRP genes as a diagnostic and therapeutic biomarker. Tang et al (2019) reported the five key genes: ACTR2, ARPC3, ARPC5, CTTN, and APP may be implicated in tumor progression and could potentially represent promising prognostic biomarkers and therapeutic targets for AML biomarker identification in leukemia. There are many studies that have been reported (Prada et al, 2017, Jiang et al, 2016, Sweet et al, 2013 for the identification and characterization of biomarkers for individual classes of leukemia, but the present study was carried out for the comparative analysis of biomarker profiling of major classes (AML, ALL, CML, and CLL) of leukemia.…”