Bioinformatics analysis and identification of hub genes and immune-related molecular mechanisms in chronic myeloid leukemia

被引:6
|
作者
Yao, Fangyi [1 ]
Zhao, Cui [1 ]
Zhong, Fangmin [1 ]
Qin, Tingyu [1 ]
Li, Shuqi [1 ]
Liu, Jing [1 ]
Huang, Bo [1 ]
Wang, Xiaozhong [1 ]
机构
[1] Nanchang Univ, Dept Clin Lab, Jiangxi Prov Key Lab Lab Med, Affiliated Hosp 2, Nanchang, Jiangxi, Peoples R China
来源
PEERJ | 2022年 / 10卷
基金
中国国家自然科学基金;
关键词
Chronic myeloid leukemia; Differentially expressed gene; Network analysis; Diagnostic value; CHRONIC MYELOGENOUS LEUKEMIA; ACUTE LYMPHOBLASTIC-LEUKEMIA; CELLS;
D O I
10.7717/peerj.12616
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Background: Chronic myeloid leukemia (CML) is a malignant hyperplastic tumor of the bone marrow originating from pluripotent hematopoietic stem cells. The advent of tyrosine kinase inhibitors (TKIs) has greatly improved the survival rate of patients with CML. However, TKI-resistance leads to the disease recurrence and progression. This study aimed to identify immune-related genes (IRGs) associated with CML progression. Methods: We extracted the gene's expression profiles from the Gene Expression Omnibus (GEO). Bioinformatics analysis was used to determine the differentially expressed IRGs of CML and normal peripheral blood mononuclear cells (PBMCs). Functional enrichment and gene set enrichment analysis (GSEA) were used to explore its potential mechanism. Hub genes were identified using Molecular Complex Detection (MCODE) and the CytoHubba plugin. The hub genes' diagnostic value was evaluated using the receiver operating characteristic (ROC). The relative proportions of infiltrating immune cells in each CML sample were evaluated using CIBERSORT. Quantitative real-time PCR (RT-qPCR) was used to validate the hub gene expression in clinical samples. Results: A total of 31 differentially expressed IRGs were identified. GO analyses revealed that the modules were typically enriched in the receptor ligand activity, cytokine activity, and endopeptidase activity. KEGG enrichment analysis of IRGs revealed that CML involved Th17 cell differentiation, the NF-kappa B signaling pathway, and cytokine-cytokine receptor interaction. A total of 10 hub genes were selected using the PPI network. GSEA showed that these hub genes were related to the gamma-interferon immune response, inflammatory response, and allograft rejection. ROC curve analysis suggested that six hub genes may be potential biomarkers for CML diagnosis. Further analysis indicated that immune cells were associated with the pathogenesis of CML. The RT-qPCR results showed that proteinase 3 (PRTN3), cathepsin G (CTSG), matrix metalloproteinase 9 (MMP9), resistin (RETN), eosinophil derived neurotoxin (RNase2), eosinophil cationic protein (ECP, RNase3) were significantly elevated in CML patients' PBMCs compared with healthy controls. Conclusion: These results improved our understanding of the functional characteristics and immune-related molecular mechanisms involved in CML progression and provided potential diagnostic biomarkers and therapeutic targets.
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页数:23
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