RESUMEN
Chronic neutrophilic leukemia (CNL) is a rare type of myeloproliferative neoplasm (MPN). Due to its nonspecific clinical symptoms and lack of specific molecular markers, it was previously difficult to distinguish it from other diseases with increased neutrophils. However, the discovery of the CSF3R mutation in CNL 10 years ago and the update of the diagnostic criteria by the World Health Organization (WHO) in 2016 brought CNL into a new era of molecular diagnosis. Next-generation sequencing (NGS) technology has led to the identification of numerous mutant genes in CNL. While CSF3R is commonly recognized as the driver mutation of CNL, other mutations have also been detected in CNL using NGS, including mutations in other signaling pathway genes (CBL, JAK2, NARS, PTPN11) and chromatin modification genes (ASXL1, SETBP1, EZH2), DNA methylation genes (DNMT3A, TET2), myeloid-related transcription factor genes (RUNX1, GATA2), and splicing and RNA metabolism genes (SRSF2, U2AF1). The coexistence of these mutated genes and CSF3R mutations, as well as the different evolutionary sequences of clones, deepens the complexity of CNL molecular biology. The purpose of this review is to summarize the genetic research findings of CNL in the last decade, focusing on the common mutated genes in CNL and their clinical significance, as well as the clonal evolution pattern and sequence of mutation acquisition in CNL, to provide a basis for the appropriate management of CNL patients.
RESUMEN
BACKGROUND: Study of the molecular biological characteristics of chronic neutrophilic leukemia complicated with plasma cell disorder (CNL-PCD) and lymphocytic proliferative disease (CNL-LPD). METHODS: The clinical data of a patient with chronic neutrophilic leukemia complicated with monoclonal gammopathy of undetermined significance (CNL-MGUS) in our hospital were reviewed, and the Chinese and/or English literature about CNL-PCD and CNL-LPD in PubMed and the Chinese database CNKI in the past 10 years was searched to analyze the molecular biological characteristics of this disease. RESULTS: A 73-year-old male had persistent leukocytosis for 18 months. The white blood cell count was 46.77 × 109/L and primarily composed of mature neutrophils; hemoglobin: 77 g/L; platelet count: 189 × 109/L. Serum immunofixation electrophoresis showed IgG-λ monoclonal M protein. A CT scan showed splenomegaly. Next-generation sequencing (NGS) showed that CSF3R T618I, ASXL1 and RUNX1 mutations were positive. It was diagnosed as CNL-MGUS. We summarized 10 cases of CNL-PCD and 1 case of CNL-LPD who underwent genetic mutation detection reported in the literature. The CSF3R mutational frequency (7/11, 63.6%) was lower than that of isolated CNL. The ASXL1 mutations were all positive (3/3), which may represent a poor prognostic factor. The SETBP1 mutation may promote the progression of CNL-PCD. We also found JAK2, RUNX1, NRAS, etc. in CNL-PCD. CONCLUSIONS: Chronic neutrophilic leukemia may be more inclined to coexist with plasma cell disorder. The CSF3R mutation in CNL-PCD is still the most common mutated gene compared with isolated CNL. Mutations in SETBP1 and ASXL1 may be poor prognostic factors for CNL-PCD.
Asunto(s)
Leucemia Neutrofílica Crónica , Gammopatía Monoclonal de Relevancia Indeterminada , Paraproteinemias , Anciano , Subunidad alfa 2 del Factor de Unión al Sitio Principal/genética , Humanos , Leucemia Neutrofílica Crónica/complicaciones , Leucemia Neutrofílica Crónica/diagnóstico , Leucemia Neutrofílica Crónica/genética , Masculino , Gammopatía Monoclonal de Relevancia Indeterminada/complicaciones , Gammopatía Monoclonal de Relevancia Indeterminada/genética , Mutación/genética , Paraproteinemias/complicaciones , Paraproteinemias/genéticaRESUMEN
Background: Previous researches have suggested a significant connection between the gut microbiota/immune cells and morphine tolerance (MT), but there is still uncertainty regarding their causal relationship. Hence, our objective is to inverstigate this causal association and reveal the impact of gut microbiota/immune cells on the risk of developing MT using a two-sample Mendelian randomization (MR) study. Methods: We conducted a comprehensive analysis using genome-wide association study (GWAS) summary statistics for gut microbiota, immune cells, and MT. The main approach employed was the inverse variance-weighted (IVW) method in MR. To assess horizontal pleiotropy and remove outlier single-nucleotide polymorphisms (SNPs), we utilized the Mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO) technique as well as MR-Egger regression. Heterogeneity detection was performed using Cochran's Q-test. Additionally, leave-one-out analysis was carried out to determine if any single SNP drove the causal association signals. Finally, we conducted a reverse MR to evaluate the potential of reverse causation. Results: We discovered that 6 gut microbial taxa and 16 immune cells were causally related to MT (p < 0.05). Among them, 2 bacterial features and 9 immunophenotypes retained a strong causal relationship with lower risk of MT: genus. Lachnospiraceae NK4A136group (OR: 0.962, 95% CI: 0.940-0.987, p = 0.030), genus. RuminococcaceaeUCG011 (OR: 0.960, 95% CI: 0.946-0.976, p = 0.003), BAFF-R on B cell (OR: 0.972, 95% CI: 0.947-0.998, p = 0.013). Furthermore, 4 bacterial features and 7 immunophenotypes were identified to be significantly associated with MT risk: genus. Flavonifractor (OR: 1.044, 95% CI: 1.017-1.069, p = 0.029), genus. Prevotella9 (OR: 1.054, 95% CI: 1.020-1.090, p = 0.037), B cell % CD3-lymphocyte (OR: 1.976, 95% CI: 1.027-1.129, p = 0.026). The Cochrane's Q test revealed no heterogeneity (p > 0.05). Furthermore, the MR-Egger and MR-PRESSO analyses reveal no instances of horizontal pleiotropy (p > 0.05). Besides, leave-one-out analysis confirmed the robustness of MR results. After adding BMI to the multivariate MR analysis, the gut microbial taxa and immune cells exposure-outcome effect were attenuated. Conclusion: Our research confirm the potential link between gut microbiota and immune cells with MT, shedding light on the mechanism by which gut microbiota and immune cells may contribute to MT. These findings lay the groundwork for future investigations into targeted prevention strategies.