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

Abstract

Chronic myeloid leukemia (CML) is a malignant hyperplastic tumor that originats from pluripotent hematopoietic stem cells in the bone marrow. The introduction of tyrosine kinase inhibitors (TKIs) has significantly improved the survival rates of CML patients. This study aimed to identify immune-related genes (IRGs) associated with the response to imatinib therapy in CML. Gene expression profiles from imatinib-treated CML patients were obtained from the Gene Expression Omnibus (GEO) database and categorized into high- and low-score groups based on immune scores calculated using the ESTIMATE algorithm. Subsequent bioinformatics analysis identified 428 differentially expressed IRGs in the CML context. Functional enrichment analysis revealed that these genes were involved in immune-related pathways, including T cell receptor signaling and cytokine-cytokine receptor interaction. Finally, based on five modules in weighted gene co-expression network analysis (WGCNA) and the top-ranked degree, 10 hub genes were identified. Receiver operating characteristic (ROC) analysis in two GEO datasets identified IL10RA, SCN9A, and SLC26A11 as potential biomarkers for predicting imatinib response. We further validated these biomarkers in an independent clinical cohort of 60 CML patients treated with imatinib. Results from quantitative real-time (qRT) PCR revealed high expression of IL10RA and SLC26A11 in responders, while SCN9A showed low expression. All three genes had an AUC greater than 0.75, confirming their potential as predictive biomarkers. These findings deepen our understanding of functional characteristics and immune-related molecular mechanisms underlying imatinib response and offer promising predictive biomarkers.

Keywords: chronic myeloid leukemia (CML); imatinib; immune scores; tyrosine kinase inhibitor (TKI).