Immune-Related Genes for the Prediction of Response to Imatinib therapy in Chronic Myeloid Leukemia

Abstract Background. Chronic myeloid leukemia (CML) is a malignant hyperplastic tumor that originates from pluripotent hematopoietic stem cells in the bone marrow. The introduction of tyrosine kinase inhibitors (TKIs) has significantly enhanced the survival rate of CML patients. This study aimed to identify immune-related genes (IRGs) associated with the response to imatinib therapy in CML. Methods. We obtained gene expression profiles of CML patients treated with imatinib from the Gene Expression Omnibus (GEO) database. The patients were classified into high- and low-score groups based on their immune score, as determined by the ESTIMATE algorithm. Bioinformatics analysis was conducted to identify differentially expressed IRGs in CML. Functional enrichment analysis was performed to investigate potential mechanisms. Hub genes were identified using the weighted gene co-expression network analysis (WGCNA). The predictive value of these genes was assessed using receiver operating characteristic (ROC) analysis. Furthermore, we validated these genes in an independent cohort of patients treated with imatinib. Results. The immune score emerged as a novel predictor of response to imatinib therapy in CML. A total of 428 differentially expressed IRGs were identified. KEGG enrichment analysis revealed that the IRGs were involved in immune-related pathways, such as the T cell receptor signaling pathway and cytokine-cytokine receptor interaction. Based on five modules in WGCNA and the top-ranked degree, 10 hub genes were identified. ROC curve analysis indicated that IL10RA, SCN9A, and SLC26A11 genes may serve as potential biomarkers for predicting the response to imatinib. Conclusion. These findings enhance our understanding of the functional characteristics and immune-related molecular mechanisms involved in the response to imatinib and provide potential predictive biomarkers.