Gene Expression Profiling in CD34+ Cells of Patients with Chronic Myeloid Leukemia
Research Article
P: 20-27
March 2024

Gene Expression Profiling in CD34+ Cells of Patients with Chronic Myeloid Leukemia

J Ankara Univ Fac Med 2024;77(1):20-27
1. Ankara Üniversitesi Sağlık Hizmetleri Meslek Yüksekokulu, Tıbbi Laboratuvar Teknikleri, Ankara, Türkiye
2. Ankara Üniversitesi Tıp Fakültesi, Tıbbi Biyoloji Anabilim Dalı, Ankara, Türkiye
No information available.
No information available
Received Date: 17.11.2023
Accepted Date: 09.03.2024
Publish Date: 05.04.2024



Chronic myeloid leukaemia (CML) is a malignant, clonal and proliferative disease originating from haematopoietic stem cells. The aim of this study is to use bioinformatic analysis to identify potential key genes and pathways involved in CML patients in the chronic phase to investigate the molecular mechanisms of CML.

Materials and Methods:

For bioinformatic analysis, mRNA microarray data of CD34+ cells from 9 CML patients and 8 healthy individuals with accession number GSE5550 were downloaded from the Gene Expression Omnibus (GEO) database. Samples from CML patients and healthy individuals were analysed with GEO2R to find differentially expressed genes (DEGs). Gene ontology and Kyoto gene and genome encyclopedia enrichment analyses and protein-protein interaction network analysis were performed for DEGs and important CML related genes were identified.


After analysis with GEO2R, DEGs with p<0.01 and log2FC<0, log2FC>0 were selected. In the GSE5550 data set, the expression of 1894 genes increased and 796 genes decreased in CML patients compared to the healthy control group. It was observed that DEGs were enriched in pathways such as metabolic pathways, RNA transport, ribosome, protein processing in endoplasmic reticulum and Ubikitin-mediated proteolysis in the CML patient group in comparison to the healthy controls. In addition, RPL35, RPL39, RPS12, eEF1A1, RPLP1, RPL12, ODC1, PSMD7, USP14, PSMA1, GLI2, PSMC6 were identified as the most important candidate genes.


The results of our study showed that the genes and pathways identified in our study may be biomarker candidates that can be used in drug treatment to target leukaemic stem cells.

Keywords: CML, bioinformatic analysis, microarray, gene expression


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