Gene Co-Expression Network Analysis for Identifying Modules and Functionally Enriched Pathways in Leukemia Stem Cells

Background and Aim: Acute myeloid leukemia (AML) is a cancer of themyeloid line of blood cells, leukemia stem cells (LSCs) in AML played important roles in leukemia initiation, progression, and were consideredto be the root of chemotherapeutic drug resistance and disease relapse,in this study, we focus on the applications of differential regulatoryanalysis (DRA) based on gene coexpression network (GCN) in Leukemiastem cells research.Methods: Gene expression datasets from NCBI Gene ExpressionOmnibus (GEO) database was collected from normal hematopoieticstem and progenitor cells and acute myeloid leukemia sub-populations,Normalization was performed with rma function from the affy packagein R, Gene co-expression network and modules were constructed withthe weighted gene co-expression network analysis (WGCNA) packagein R, performed pathway enrichment analysis of selected modules byusing two network-based gene set enrichment analysis tools, KOBAS3.0 and Enrichr. This includes enrichment in predefined pathways by,for example, KEGG, and in the end Module visualization and furtheranalysis was performed with VisANT software.Results: In this study, we analyzed gene expression datasets of acutemyeloid leukemia patients and healthy controls by applying a systemsbiology approach that combines the WGCNA with functional enrichmentanalysis. Novel co-expression gene network modules associated withAML cancer stem cell were elucidated, which in turn provided a basisfor the identification of potential pathways and biomarker genes that maybe involved in the development of normal hematopoietic stem cell toLeukemia stem cells.Conclusion: LSCs in AML were considered to be the root ofchemotherapeutic drug resistance and disease relapse, Identification ofthe specific features of LSCs such as potential pathways and biomarkergenes for purpose of expanding innovative strategies in the diagnosis andtreatment of Leukemia stem cells.

کلیدواژه ها:

Acute myeloid leukemia ، Acute myeloid leukemia ، Weighted gene co-expression network analysis