Application of NanoString Technologies in Chronic Myeloid Leukemia, Essential Thrombocythemia, Primary Myelofibrosis,...

Background/Objectives: Chronic myeloid leukemia (CML), essential thrombocythemia (ET), primary myelofibrosis (PMF), and polycythemia vera (PV) are myeloproliferative neoplasms (MPNs) that require precise molecular characterization. Although driver mutations such as BCR-ABL1 and JAK2 are diagnostically important, they do not fully explain disease heterogeneity. The NanoString nCounter^® system enables direct multiplex gene expression analysis without RNA amplification and is suitable for degraded bone marrow specimens. This study aimed to analyze cytokine gene expression in bone marrow mononuclear cells of patients with MPNs and controls using NanoString technology, identify differentially expressed genes (DEGs) among MPN subtypes, and investigate their biological significance. Methods: Bone marrow aspirates were collected from 19 patients with MPNs (CML, ET, PMF, and PV) and 6 control patients. Mononuclear cells were isolated, and RNA expression of a 40-gene cytokine panel was analyzed using the NanoString nCounter^® system with strict quality control and normalization. DEGs were identified for each MPN subtype, followed by Gene Ontology(GO) and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway analyses. Results: CML and PV demonstrated 20 and 12 DEGs, respectively. In contrast, ET showed only one DEG (IRAK2), and PMF showed none. Functional analyses revealed enrichment of cytokine signaling, Toll-like receptor (TLR), and JAK-STAT pathways in CML, indicating immune and inflammatory dysregulation. PV DEGs were associated with TLR signaling, IL-17 pathways, and cytokine-cytokine receptor interactions, suggesting active cytokine-mediated inflammation. Conclusions: CML and PV exhibited distinct cytokine-driven transcriptional signatures, whereas ET and PMF exhibited minimal alterations. These findings support the clinical utility of NanoString technology for bone marrow specimens and highlight disease-specific immune pathways as potential diagnostic biomarkers in MPNs.