Targeting the core regulatory network of stemness in an in vitro AML model using a GRN approach

Recent advances in hemato-oncology research have provided the chance to construct more personalized and pathophysiology-targeted therapeutic strategies. Despite the use of vigorous chemotherapy, relapse after remission and refractoriness to induction chemotherapy remain as the most common therapeutic failures in acute myelogenous leukemia (AML). It seems that a rare population of cells called Leukemia stem cells (LSCs), are responsible for initiating therapy resistance and relapse. Therefore, in this study we aimed to identify a precise list of biomarkers and target genes, which may play an effective role in targeting these cells. Gene Regulatory Network (GRN) is an adequate bioinformatics tool used in mapping gene interactions and also, pinpointing key genes which may regulate the stemness core in LSCs. In this study, our aim was to identify key genes which may be regulating the stemness core in LSCs. In this study, 4 main steps were preformed: 1) Data collection: a data set of 495 Gene expression profiles (GSE76009) was obtained from GEO database. 2) Differentially expression analysis was performed between two defined groups of LSC+ and LSC- using limma package in R Software (3.4.2 version) with the following cut off; FC1.3, Adj.p-val < 0.05. 3) Network Reconstruction was conducted using ARACNE algorithm and Cytoscape software.4) Network analysis, in this stage hub genes were attained and confirmed in literature. Using this bioinformatics approach, we were able to attain a list of candidate genes which may have a significant role in regulating the stemness core in LSCs.

کلیدواژه ها:

Personalized medicine ، AML ، Leukemia stemcells ، Bioinformatics ، Gene regulatory network