Open AccessIdentification of key candidate targets and pathways for the targeted treatment of leukemia stem cells of chronic myelogenous leukemia using bioinformatics analysis
Author(s) -
Li Huayao,
Liu Lijuan,
Zhuang Jing,
Liu Cun,
Zhou Chao,
Yang Jing,
Gao Chundi,
Liu Gongxi,
Sun Changgang
Publication year - 2019
Publication title -
molecular genetics and genomic medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.765
H-Index - 29
ISSN - 2324-9269
DOI - 10.1002/mgg3.851
Subject(s) - chronic myelogenous leukemia , microrna , biology , signal transduction , stem cell , leukemia , microarray analysis techniques , cancer research , biological pathway , haematopoiesis , pi3k/akt/mtor pathway , computational biology , gene , microbiology and biotechnology , genetics , gene expression
Background Chronic myelogenous leukemia (CML) is a myeloproliferative neoplasm that arises from the acquisition of constitutively active BCR‐ABL tyrosine kinase in hematopoietic stem cells. The persistence of bone marrow leukemia stem cells (LSCs) is the main cause of TKI resistance and CML relapse. Therefore, finding a key target or pathway to selectively target LSCs is of great significance for the thorough treatment of CML. Methods In this study, we aimed to identify key microRNAs, microRNA targets and pathways for the treatment of CML LSCs by integrating analyses of three microarray data profiles. We identified 51 differentially expressed microRNAs through integrated analysis of GSE90773 and performed functional gene predictions for microRNAs. Then, GSE11889 and GSE11675 were integrated to obtain differentially expressed genes (DEGs), and the overlapping DEGs were used as models to identify predictive functional genes. Finally, we identified 116 predictive functional genes. Clustering and significant enrichment analysis of 116 genes was based on function and signaling pathways. Subsequently, a protein interaction network was constructed, and module analysis and topology analysis were performed on the network. Results A total of 11 key candidate targets and 33 corresponding microRNAs were identified. The key pathways were mainly concentrated on the PI3K/AKT, Ras, JAK/STAT, FoxO and Notch signaling pathways. We also found that LSCs negatively regulated endogenous and exogenous apoptotic pathways to escape from apoptosis. Conclusion We identified key candidate targets and pathways for CML LSCs through bioinformatics methods, which improves our understanding of the molecular mechanisms of CML LSCs. These candidate genes and pathways may be therapeutic targets for CML LSCs.