ObjectiveTo systematically review the correlation between DNMT3a mutation and peripheral blood cell count on the time of diagnosis for adult primary acute myeloid leukemia (AML). MethodsLiterature search in the databases such as PubMed, ScienceDirect, EBSCO, Web of Science, CNKI, VIP and WanFang Data was performed to collect the case-control studies about the correlation between the DNMT3a mutations and adult AML up to December 2012. Two reviewers independently screened the literature according to the inclusion and exclusion criteria, extracted the data, and assessed the methodological quality of the included studies, and then RevMan 5.0 software was conducting for metaanalysis. ResultsA total of 10 studies involving 2 704 patients were included. The results of meta-analyses showed that:the levels of peripheral blood WBC, HGB and PLT of the DNMT3a-mutated group were significantly higher than those of the DNMT3a-wildtype group for the initial visit of adult primary AML patients (all P values < 0.05). ConclusionThe peripheral blood cell counts of the DNMT3a-mutated group are higher than those of the DNMT3a-wildtype group for the initial visit of adult primary AML patients, indicating DNMT3a mutation might contribute to promote cell proliferation, and this helps us better understand the role of DNMT3a mutation in the development of AML.
Objective To investigate the expression levels of fatty acid metabolism-related genes in acute myeloid leukemia (AML) and construct a prognostic risk regression model for AML. Methods Gene expression data from control groups and AML patients were downloaded from the GTEx database and The Cancer Genome Atlas (TCGA) database, followed by screening for differentially expressed genes (DEGs) between AML patients and controls. Fatty acid metabolism-related genes were obtained from the MSigDB database. The intersection of DEGs and fatty acid metabolism-related genes yielded fatty acid metabolism-associated DEGs. A protein-protein interaction network was constructed using the STRING database. Hub genes were analyzed via random forest, Kaplan-Meier survival, and Cox proportional hazards regression based on TCGA clinical data to establish a prognostic model and evaluate their diagnostic and prognostic significance. Immune cell infiltration differences between high- and low-risk groups were assessed using CIBERSORT algorithms to explore immune microenvironment variations and correlations with risk scores. Results A total of 60 fatty acid metabolism-related DEGs were identified. Further screening revealed 15 hub genes, among which four genes (HPGDS, CYP4F2, ACSL1, and EHHADH) were selected via integrated random forest, Cox regression, and Kaplan-Meier analyses to construct an AML prognostic lipid metabolism gene signature. Heatmaps demonstrated statistically significant differences in tumor-infiltrating immune cell proportions between risk groups. Conclusion The constructed lipid metabolism gene prognostic model may serve as a biomarker for overall survival in AML patients and provide new insights for immunotherapy drug development.