Analysis of non-driver mutation characteristics in primary myelofibrosis

Abstract

Abstract Objective: This study aims to investigate the distribution characteristics, interrelationships, and impact on disease prognosis of non-driver mutations in patients with primary myelofibrosis (PMF). Methods: We retrospectively analyzed the clinical data of 56 newly diagnosed PMF patients who were diagnosed at Zhongnan Hospital of Wuhan University between 2018 and 2024. The mRNA expression level of the WT1 gene was detected by q-PCR, with high expression defined as >1.0%. Next-generation sequencing (NGS) technology was used to detect mutations in 25 myeloid tumor-related genes (such as JAK2, ASXL1, TET2, CARL, SF3B1, MPL, SRSF2, DNMT3A, EZH2, TP53, U2AF1 S34F, CBL, CSF3R, IDH1/2, etc.), and mutations other than JAK2 V617F, CARL, and MPL were defined as non-driving mutations. Simultaneously, clinical indicators such as patient age, myelofibrosis grade (MF grade), and platelet count (PLT) were collected. The correlation between WT1 expression level, the number of non-driving mutations, and clinical indicators was evaluated by Spearman/Pearson correlation analysis; chi-square test was used to analyze the association between categorical variables. Results: Among the 25 types of relevant gene mutations, JAK2 V617F mutations were the most frequent (40/56), followed by ASXL1 mutations (19/56). The number of non-driver mutations in the 56 patients ranged from 0 to 11, with 62.5% of patients harboring two or fewer non-driver mutations (35/56). There was no correlation between the number of non-driver mutations and JAK2 V617F mutation burden (p=0.371), but a positive correlation with the severity of myelofibrosis (MF grade) (p=0.026) and a negative correlation with platelet count (PLT) (r=-0.284, p=0.036). Meanwhile, age showed no correlation with the number of non-driver mutations (p=0.208), but was significantly positively correlated with TET2 mutations (p=0.003). WT1 expression level was negatively correlated with TET2 mutation status (r=-0.264, p=0.049) and positively correlated with the number of non-driver mutations (r=0.308, p=0.021). Conclusion: The results of this study indicate that in newly diagnosed PMF patients, non-driver mutation burden serves as an important indicator reflecting the disease state of PMF, such as fibrosis progression and thrombocytopenia, and is associated with specific molecular markers (WT1, TET2), potentially providing potential value in assessing the disease characteristics and prognosis of PMF patients. The integrated analysis of NGS technology for non-driver mutation detection can offer new molecular evidence for risk stratification and prognosis evaluation in PMF. Keywords: Myelofibrosis, Non-driver Mutations, NGS, age, WT1 expression Disclosures：No relevant conflicts of interest to declare.