MicroRNA biomarker identification for pediatric acute myeloid leukemia based on a novel bioinformatics model

Abstract

Acute myeloid leukemia (AML) in children is a complex and heterogeneous disease. The identification of reliable and stable molecular biomarkers for diagnosis, especially early diagnosis, remains a significant therapeutic challenge. Aberrant microRNA expression could be used for cancer diagnosis and treatment selection. Here, we describe a novel bioinformatics model for the prediction of microRNA biomarkers for the diagnosis of paediatric AML based on computational functional analysis of the microRNA regulatory network substructure. microRNA-196b, microRNA-155 and microRNA-25 were identified as putative diagnostic biomarkers for pediatric AML. Further systematic analysis confirmed the association of the predicted microRNAs with the leukemogenesis of AML. In vitro q-PCR experiments showed that microRNA-155 is significantly overexpressed in children with AML and microRNA-196b is significantly overexpressed in subgroups M4-M5 of the French-American-British classification system. These results suggest that microRNA-155 is a potential diagnostic biomarker for all subgroups of paediatric AML, whereas microRNA-196b is specific for subgroups M4-M5.

Differential Expression of MiR-106b-5p and MiR-200c-3p in Newly Diagnosed Versus Chronic Primary Immune Thrombocytopenia Patients Based on Systematic Analysis

“…In this work, we employed POMA to identify key miRNAs expressed in samples obtained from ITP patients that were newly diagnosed (G1) versus managing a chronic ITP condition (G2). POMA is a framework that has been used to identify candidate miRNA biomarkers for diseases by integrating microarray profiling with experimental and predicted miRNA-mRNA interactions [29, 30]. …”

“…Differentially expressed miRNAs and/or genes were then mapped to the whole network to infer specific miRNA-mRNA subnetworks [12, 20]. According to the framework, stage-specific miRNA-mRNA networks were built, and key miRNAs in the subnetworks were identified on the basis of significant differential expression of miRNAs and genes between each ITP group and the N group using improved POMA [29, 30]. We also constructed a G2’ miRNA–mRNA network based on the identification of DE-miRNAs and DE-mRNAs between G2 and G1.…”

“…Therefore, we initially employed high-throughput microarray technology to measure the expression profiles of miRNAs and genes in peripheral blood cells samples from patients with newly diagnosed ITP, those with chronic ITP, and normal controls. Then, we used the systematic Pipeline of Outlier MicroRNA Analysis (POMA) framework [29, 30] to identify candidate key miRNAs in the two ITP stages based on the miRNA and messenger RNA (mRNA) profiles obtained. Finally, we validated the aberrant expression of key miRNAs in a large sample of patients with ITP.…”

Novel Biomarker MicroRNAs for Subtyping of Acute Coronary Syndrome: A Bioinformatics Approach

“…To better understand the disease pathogenesis of these two subtypes, we applied an in-house regulatory model termed improved Pipeline of Outlier MicroRNA Analysis (POMA) [23, 24] to identify miRNAs specific to each subtype or shared by both subtypes (see Figure 1). The model focused on miRNAs' independent regulatory power and the biological functions of their targets.…”

CDH1 (E-cadherin) expression independently affects clinical outcome in acute myeloid leukemia with normal cytogenetics

“…Acute myeloid leukemia (AML), arising from the clonal transformation of hematopoietic precursors, is a heterogeneous cancer characterized by a series of cytogenetics and molecular abnormalities [1][2][3]. Over the past decades, rapid advances have been made in elucidating some of the key elements in the pathogenesis of AML.…”